IEEE/CAA J. Autom. Sinica - Academia.edu (original) (raw)
Papers by IEEE/CAA J. Autom. Sinica
IEEE/CAA Journal of Automatica Sinica, 2023
CONTROL systems are everywhere – chemical plants, energy systems, manufacturing, homes and buildi... more CONTROL systems are everywhere – chemical plants, energy systems, manufacturing, homes and buildings, automobiles and trains, medical devices, cellular telephones and internet, aircraft and spacecraft. Recent developments in these fields bring up the systems with the unprecedented scope, scale and complexity such as cyber-physical and human systems, and the required control task becomes more challenging than ever [1], demanding high performance on the complex systems at low costs. Nowadays, the technical competition has focused on high performance area. High performance products sell in markets in place of low ones. High performance products rely on high performance control in the end.
IEEE/CAA Journal of Automatica Sinica, 2023
PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, ha... more PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, has posted a paper on arXiv [1] that hints at the possibility that he may have solved the Landau-Siegel zeros conjecture. He has claimed that he has disproved a weaker version of the Landau-Siegel zeroes conjecture, an important problem related to the hypothesis. The conjecture is that there are solutions to the zeta function that do not assume the form prescribed by the Riemann hypothesis. Inspired by his work, in this Perspective, we would like to discuss about the distribution of zeros of quasi-polynomials for linear time-invariant (LTI) systems with time delays.
IEEE/CAA Journal of Automatica Sinica, 2023
SINCE the 18th century, fossil energy in the form of coal, oil, and natural gas has been used on ... more SINCE the 18th century, fossil energy in the form of coal, oil, and natural gas has been used on a large scale. These fossil fuels have provided a vast amount of energy, such as electricity, heat, and gas, for industrial production and have been a major contributor to the development of the world economy [1]. However, electricity, heat and gas are currently managed by different operators, the lack of cooperation among which leads to a great deal of redundancy in energy distribution as well as unnecessary energy waste. Moreover, the extensive use of fossil energy has brought with it a series of problems such as environmental pollution, ecological crisis, energy shortages, etc., [2]. These problems have attracted a lot of attention from researchers, policy makers, and both national and international organizations [3]. Sustainable development of energy has always been a significant topic in the last decades [4]. Efficiently coordinating power supplies and demands by utilizing advanced information and communication technologies will be a way to alleviate the above-mentioned increasingly serious energy issues.
IEEE/CAA Journal of Automatica Sinica, 2023
THE well-known ancient Chinese philosopher Lao Tzu (老子) or Laozi (6th 4th century BC during the S... more THE well-known ancient Chinese philosopher Lao Tzu (老子) or Laozi (6th 4th century BC during the Spring and Autumn period) started his classic Tao Teh Ching《道德经》or Dao De Jing (see Fig. 1) with six Chinese characters: "道(Dao) 可(Ke) 道(Dao) 非(Fei) 常(Chang) 道(Dao)", which has been traditionally interpreted as "道可道, 非常道" or "The Dao that can be spoken is not the eternal Dao". However, mordern archaeological discoveries in 1973 and 1993 at Changsha, Hunan, and Jingmen, Hubei, China, have respectively indicated a new, yet more natural and simple interpretation: "道, 可道, 非常道", or "The Dao, The Speakable Dao, The Eternal Dao".
IEEE/CAA Journal of Automatica Sinica, 2023
CHATGPT, one of the leading Large Language Models (LLMs), has acquired linguistic capabilities su... more CHATGPT, one of the leading Large Language Models (LLMs), has acquired linguistic capabilities such as text comprehension and logical reasoning, enabling it to engage in natural conversations with humans. As illustrated in "What Does ChatGPT Say: The DAO from Algorithmic Intelligence to Linguistic Intelligence" [1], there are three levels of intelligence : 1) Algorithmic Intelligence (AI), 2) Linguistic Intelligence (LI), 3) Imaginative Intelligence (Ⅱ). ChatGPT is a powerful demonstration of Linguistic Intelligence, another milestone after AlphaGo for Algorithmic Intelligence [1]–[3]. We believe the next breakthrough in intelligence should be Imaginative Intelligence for artistic creation.
This perspective prescribed a pathway to achieve Ⅱ for artistic works through Parallel Art, in which LLMs like ChatGPT can serve as linguistics-based artistic knowledge foundation models and text-based human-machine interfaces for humanin-the-loop learning. Multi-modal artistic knowledge foundation models are constructed to perform linguistic, vision, and decision-making tasks of artistic creation in the human-cyberphysical hybrid creative systems. Besides, a case study of textbased painting imagination using ChatGPT is presented.
IEEE/CAA Journal of Automatica Sinica, 2023
THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algo... more THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algorithmic Intelligence to Linguistic Intelligence where interactive activities between actual and artificial, real and virtual, human and machine play an active and important role online and in real-time. At IEEE/CAA JAS, we are interested in investigating the impact and significance of this new era on industrial development, especially control and automation for manufacturing and production.
IEEE/CAA Journal of Automatica Sinica, 2023
POWERED by the rapid development of Internet, the penetration of the Internet of Things, the emer... more POWERED by the rapid development of Internet, the penetration of the Internet of Things, the emergence of big data, and the rise of social media, more and more complex systems are exhibiting the characteristics of social, physical, and information fusion. These systems are known as cyber-physical-social systems (CPSS) [1], [2]. These CPSS face unprecedented challenges in design, analysis, management, control and integration due to their involvement with human and social factors [3], [4]. To cope with this challenge, there are two main approaches to CPSS research.
IEEE/CAA Journal of Automatica Sinica, 2023
DO we need a fundamental change in our professional culture and knowledge foundation for control ... more DO we need a fundamental change in our professional culture and knowledge foundation for control and automation? If so, what are necessary and critical steps we must take to ensure such a change would take place effectively and efficiently, or more general, smoothly and sustainably?
This question has started circulating in my mind two decades ago right after my first two decades of research and development in automation, robotics, intelligent control, and artificial intelligence. By the end of the 20th century, the effort of achieving the initial goal of intelligent control for complex systems, such as intelligent robotic systems and smart human-machine interaction, as envisioned by its pioneers, such as K. S. Fu [1] and G. N. Saridis [2], had seemed run into and stopped by an invisible wall, as witnessed by the fact that the well-known flagship academic gathering in the field, the annual IEEE International Symposium on Intelligent Control (IEEE ISIC), was losing steam after a decade’s rapid rising since 1985 [3]. For those of you interested, related historical reviews and future perspectives can be found in [3]–[5].
IEEE/CAA Journal of Automatica Sinica, 2023
The big hit of ChatGPT makes it imperative to contemplate the practical applications of big or fo... more The big hit of ChatGPT makes it imperative to contemplate the practical applications of big or foundation models [1]–[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications. To this end, here we would like to address the issues related to building knowledge factories with knowledge machines for knowledge workers by knowledge automation, that would effectively integrate the advanced foundation models, scenarios engineering, and human-oriented operating systems (HOOS) technologies for managing digital, robotic, and biological knowledge workers, and enabling decision-making, resource coordination, and task execution through three operational modes of autonomous, parallel, and expert/emergency, to achieve intelligent production meeting the goal of “6S”: Safety, Security, Sustainability, Sensitivity, Service, and Smartness [6]–[10].
IEEE/CAA Journal of Automatica Sinica, 2023
We are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish. [1]-... more We are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish. [1]-[3]. In this new epoch, the collaboration of data and knowledge, humans and machines, actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation, unveiling an open future full of boundless possibilities. However, the value of dispersed data extends far beyond passive storage and application. Instead, it has become an incentive and driving force that connects different workers in different worlds, forming a more powerful network of knowledge. No longer monopolized by a select few organizations or companies, the community-driven data sharing and exchange enable every individual to participate and contribute [4]-[6]. The diversification, sharing and integration of data create numerous avenues for learning, exploration, and innovation.
IEEE/CAA Journal of Automatica Sinica, 2023
Recently, generative AI (GenAI) has shown its great potential for promoting the development of in... more Recently, generative AI (GenAI) has shown its great potential for promoting the development of industries, economies, and societies [6]. The advent of new generation AI technique with its human-like ability has been recognized as a game-changer for sustainable development [7]. Specifically, this emerging technology can be leveraged to understand human requirements for delivering a desirable solution, adapt to different environmental conditions for comprehensive decision-making, and provide equal access for mitigating inequality [8]. The pioneering AI technology GPT has shown great promise in finance [9] and catalyst [10] with human-like text generated based on a large language model (LLM). The advent of generative pre-trained transformer 4 (GPT4) has exhibited powerful human-level performance in real-world scenarios with dramatic parameters, thereby extracting more features to overcome more challenges by understanding human requirements, adapting to different environment conditions, and providing equality access.
IEEE/CAA Journal of Automatica Sinica, 2023
This letter contributes to designing a resilient event-triggered controller for connected automat... more This letter contributes to designing a resilient event-triggered controller for connected automated vehicles under cyber attacks, including denial-of-service (DoS) and deception attacks. To characterize the effect of DoS attacks, the effective intervals of the attack are redivided based on the sampling period. Then, a resilient distributed event-triggering mechanism is proposed to compensate for the sabotage of DoS attacks and reduce the amount of transmitted data. Since the communication channel transmits the data only at the trigger instant, deception attacks may occur at this instant and be transmitted to each vehicle in superposition with the normal signal. Therefore, we construct stochastic models satisfying Bernoulli distribution to describe the false information injected by the attackers. Based on the above framework, an attack-resilient control strategy is proposed to resist the impact of cyber attacks. Then, sufficient conditions are established to achieve stability of vehicular platoons, and a co-design strategy regarding the control gain and triggering parameter matrices is given. Finally, the simulation results are provided to substantiate the effectiveness of the proposed method.
IEEE/CAA Journal of Automatica Sinica, 2023
In this paper, the networked control problem under event-triggered schemes is considered for a cl... more In this paper, the networked control problem under event-triggered schemes is considered for a class of continuous-time linear systems with random impulses. In order to save communication costs and lighten communication burden, a dynamic event-triggered scheme whose threshold parameter is dynamically adjusted by a given evolutionary rule, is employed to manage the transmission of data packets. Moreover, the evolution of the threshold parameter only depends on the sampled measurement output, and hence eliminates the influence of impulsive signals on the event-triggered mechanism. Then, with the help of a stochastic analysis method and Lyapunov theory, the existence conditions of desired controller gains are received to guarantee the corresponding input-to-state stability of the addressed system. Furthermore, according to the semi-definite programming property, the desired controller gains are calculated by resorting to the solution of three linear matrix inequalities. In the end, the feasibility and validity of the developed control strategy are verified by a simulation example.
IEEE/CAA Journal of Automatica Sinica, 2023
Most existing domain adaptation (DA) methods aim to explore favorable performance under complicat... more Most existing domain adaptation (DA) methods aim to explore favorable performance under complicated environments by sampling. However, there are three unsolved problems that limit their efficiencies: i) they adopt global sampling but neglect to exploit global and local sampling simultaneously; ii) they either transfer knowledge from a global perspective or a local perspective, while overlooking transmission of confident knowledge from both perspectives; and iii) they apply repeated sampling during iteration, which takes a lot of time. To address these problems, knowledge transfer learning via dual density sampling (KTL-DDS) is proposed in this study, which consists of three parts: i) Dual density sampling (DDS) that jointly leverages two sampling methods associated with different views, i.e., global density sampling that extracts representative samples with the most common features and local density sampling that selects representative samples with critical boundary information; ii) Consistent maximum mean discrepancy (CMMD) that reduces intra- and cross-domain risks and guarantees high consistency of knowledge by shortening the distances of every two subsets among the four subsets collected by DDS; and iii) Knowledge dissemination (KD) that transmits confident and consistent knowledge from the representative target samples with global and local properties to the whole target domain by preserving the neighboring relationships of the target domain. Mathematical analyses show that DDS avoids repeated sampling during the iteration. With the above three actions, confident knowledge with both global and local properties is transferred, and the memory and running time are greatly reduced. In addition, a general framework named dual density sampling approximation (DDSA) is extended, which can be easily applied to other DA algorithms. Extensive experiments on five datasets in clean, label corruption (LC), feature missing (FM), and LC&FM environments demonstrate the encouraging performance of KTL-DDS.
IEEE/CAA Journal of Automatica Sinica, 2023
The secure dominating set (SDS), a variant of the dominating set, is an important combinatorial s... more The secure dominating set (SDS), a variant of the dominating set, is an important combinatorial structure used in wireless networks. In this paper, we apply algorithmic game theory to study the minimum secure dominating set (MinSDS) problem in a multi-agent system. We design a game framework for SDS and show that every Nash equilibrium (NE) is a minimal SDS, which is also a Pareto-optimal solution. We prove that the proposed game is an exact potential game, and thus NE exists, and design a polynomial-time distributed local algorithm which converges to an NE in O (n) rounds of interactions. Extensive experiments are done to test the performance of our algorithm, and some interesting phenomena are witnessed.
IEEE/CAA Journal of Automatica Sinica, 2023
This paper presents a subspace identification method for closed-loop systems with unknown determi... more This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances. To deal with the unknown deterministic disturbances, two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are known. For closed-loop identification, CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique projection. In addition, a proper Bernstein polynomial order can be determined using the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.
IEEE/CAA Journal of Automatica Sinica, 2023
Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL fr... more Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL framework, where the dynamic environment and reward sparsity can cause conventional learning algorithms to fail. Reward shaping is a practical approach to improving sample efficiency by embedding human domain knowledge into the learning process. Existing reward shaping methods for goal-conditioned RL are typically built on distance metrics with a linear and isotropic distribution, which may fail to provide sufficient information about the ever-changing environment with high complexity. This paper proposes a novel magnetic field-based reward shaping (MFRS) method for goal-conditioned RL tasks with dynamic target and obstacles. Inspired by the physical properties of magnets, we consider the target and obstacles as permanent magnets and establish the reward function according to the intensity values of the magnetic field generated by these magnets. The nonlinear and anisotropic distribution of the magnetic field intensity can provide more accessible and conducive information about the optimization landscape, thus introducing a more sophisticated magnetic reward compared to the distance-based setting. Further, we transform our magnetic reward to the form of potential-based reward shaping by learning a secondary potential function concurrently to ensure the optimal policy invariance of our method. Experiments results in both simulated and real-world robotic manipulation tasks demonstrate that MFRS outperforms relevant existing methods and effectively improves the sample efficiency of RL algorithms in goal-conditioned tasks with various dynamics of the target and obstacles.
IEEE/CAA Journal of Automatica Sinica, 2023
In the era of big data, there is an urgent need to establish data trading markets for effectively... more In the era of big data, there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data. Data security and data pricing, however, are still widely regarded as major challenges in this respect, which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms. In this context, data recording and trading are conducted separately within two separate blockchains: the data blockchain (DChain) and the value blockchain (VChain). This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market. Moreover, pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users. Specifically, in regular data trading on VChain-S2D, two auction models are employed according to the demand scale, for dealing with users’ strategic bidding. The incentive-compatible Vickrey-Clarke-Groves (VCG) model is deployed to the low-demand trading scenario, while the nearly incentive-compatible monopolistic price (MP) model is utilized for the high-demand trading scenario. With temporary data trading on VChain-D2S, a reverse auction mechanism namely two-stage obscure selection (TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies. Furthermore, experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.
IEEE/CAA Journal of Automatica Sinica, 2023
This paper addresses distributed adaptive optimal resource allocation problems over weight-balanc... more This paper addresses distributed adaptive optimal resource allocation problems over weight-balanced digraphs. By leveraging state-of-the-art adaptive coupling designs for multiagent systems, two adaptive algorithms are proposed, namely a directed-spanning-tree-based algorithm and a node-based algorithm. The benefits of these algorithms are that they require neither sufficiently small or unitary step sizes, nor global knowledge of Laplacian eigenvalues, which are widely required in the literature. It is shown that both algorithms belong to a class of uncertain saddle-point dynamics, which can be tackled by repeatedly adopting the Peter-Paul inequality in the framework of Lyapunov theory. Thanks to this new viewpoint, global asymptotic convergence of both algorithms can be proven in a unified way. The effectiveness of the proposed algorithms is validated through numerical simulations and case studies in IEEE 30-bus and 118-bus power systems.
IEEE/CAA Journal of Automatica Sinica, 2023
Inspired by the integrated guidance and control design for endo-atmospheric aircraft, the integra... more Inspired by the integrated guidance and control design for endo-atmospheric aircraft, the integrated position and attitude control of spacecraft has attracted increasing attention and gradually induced a wide variety of study results in last over two decades, fully incorporating control requirements and actuator characteristics of space missions. This paper presents a novel and comprehensive survey to the coupled position and attitude motions of spacecraft from the perspective of dynamics and control. To this end, a systematic analysis is firstly conducted in details to show the position and attitude mutual couplings of spacecraft. Particularly, in terms of the time discrepancy between spacecraft position and attitude motions, space missions can be categorized into two types: space proximity operation and space orbital maneuver. Based on this classification, the studies on the coupled dynamic modeling and the integrated control design for position and attitude motions of spacecraft are sequentially summarized and analyzed. On the one hand, various coupled position and dynamic formulations of spacecraft based on various mathematical tools are reviewed and compared from five aspects, including mission applicability, modeling simplicity, physical clearance, information matching and expansibility. On the other hand, the development of the integrated position and attitude control of spacecraft is analyzed for two space missions, and especially, five distinctive development trends are captured for space operation missions. Finally, insightful prospects on future development of the integrated position and attitude control technology of spacecraft are proposed, pointing out current primary technical issues and possible feasible solutions.
IEEE/CAA Journal of Automatica Sinica, 2023
CONTROL systems are everywhere – chemical plants, energy systems, manufacturing, homes and buildi... more CONTROL systems are everywhere – chemical plants, energy systems, manufacturing, homes and buildings, automobiles and trains, medical devices, cellular telephones and internet, aircraft and spacecraft. Recent developments in these fields bring up the systems with the unprecedented scope, scale and complexity such as cyber-physical and human systems, and the required control task becomes more challenging than ever [1], demanding high performance on the complex systems at low costs. Nowadays, the technical competition has focused on high performance area. High performance products sell in markets in place of low ones. High performance products rely on high performance control in the end.
IEEE/CAA Journal of Automatica Sinica, 2023
PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, ha... more PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, has posted a paper on arXiv [1] that hints at the possibility that he may have solved the Landau-Siegel zeros conjecture. He has claimed that he has disproved a weaker version of the Landau-Siegel zeroes conjecture, an important problem related to the hypothesis. The conjecture is that there are solutions to the zeta function that do not assume the form prescribed by the Riemann hypothesis. Inspired by his work, in this Perspective, we would like to discuss about the distribution of zeros of quasi-polynomials for linear time-invariant (LTI) systems with time delays.
IEEE/CAA Journal of Automatica Sinica, 2023
SINCE the 18th century, fossil energy in the form of coal, oil, and natural gas has been used on ... more SINCE the 18th century, fossil energy in the form of coal, oil, and natural gas has been used on a large scale. These fossil fuels have provided a vast amount of energy, such as electricity, heat, and gas, for industrial production and have been a major contributor to the development of the world economy [1]. However, electricity, heat and gas are currently managed by different operators, the lack of cooperation among which leads to a great deal of redundancy in energy distribution as well as unnecessary energy waste. Moreover, the extensive use of fossil energy has brought with it a series of problems such as environmental pollution, ecological crisis, energy shortages, etc., [2]. These problems have attracted a lot of attention from researchers, policy makers, and both national and international organizations [3]. Sustainable development of energy has always been a significant topic in the last decades [4]. Efficiently coordinating power supplies and demands by utilizing advanced information and communication technologies will be a way to alleviate the above-mentioned increasingly serious energy issues.
IEEE/CAA Journal of Automatica Sinica, 2023
THE well-known ancient Chinese philosopher Lao Tzu (老子) or Laozi (6th 4th century BC during the S... more THE well-known ancient Chinese philosopher Lao Tzu (老子) or Laozi (6th 4th century BC during the Spring and Autumn period) started his classic Tao Teh Ching《道德经》or Dao De Jing (see Fig. 1) with six Chinese characters: "道(Dao) 可(Ke) 道(Dao) 非(Fei) 常(Chang) 道(Dao)", which has been traditionally interpreted as "道可道, 非常道" or "The Dao that can be spoken is not the eternal Dao". However, mordern archaeological discoveries in 1973 and 1993 at Changsha, Hunan, and Jingmen, Hubei, China, have respectively indicated a new, yet more natural and simple interpretation: "道, 可道, 非常道", or "The Dao, The Speakable Dao, The Eternal Dao".
IEEE/CAA Journal of Automatica Sinica, 2023
CHATGPT, one of the leading Large Language Models (LLMs), has acquired linguistic capabilities su... more CHATGPT, one of the leading Large Language Models (LLMs), has acquired linguistic capabilities such as text comprehension and logical reasoning, enabling it to engage in natural conversations with humans. As illustrated in "What Does ChatGPT Say: The DAO from Algorithmic Intelligence to Linguistic Intelligence" [1], there are three levels of intelligence : 1) Algorithmic Intelligence (AI), 2) Linguistic Intelligence (LI), 3) Imaginative Intelligence (Ⅱ). ChatGPT is a powerful demonstration of Linguistic Intelligence, another milestone after AlphaGo for Algorithmic Intelligence [1]–[3]. We believe the next breakthrough in intelligence should be Imaginative Intelligence for artistic creation.
This perspective prescribed a pathway to achieve Ⅱ for artistic works through Parallel Art, in which LLMs like ChatGPT can serve as linguistics-based artistic knowledge foundation models and text-based human-machine interfaces for humanin-the-loop learning. Multi-modal artistic knowledge foundation models are constructed to perform linguistic, vision, and decision-making tasks of artistic creation in the human-cyberphysical hybrid creative systems. Besides, a case study of textbased painting imagination using ChatGPT is presented.
IEEE/CAA Journal of Automatica Sinica, 2023
THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algo... more THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algorithmic Intelligence to Linguistic Intelligence where interactive activities between actual and artificial, real and virtual, human and machine play an active and important role online and in real-time. At IEEE/CAA JAS, we are interested in investigating the impact and significance of this new era on industrial development, especially control and automation for manufacturing and production.
IEEE/CAA Journal of Automatica Sinica, 2023
POWERED by the rapid development of Internet, the penetration of the Internet of Things, the emer... more POWERED by the rapid development of Internet, the penetration of the Internet of Things, the emergence of big data, and the rise of social media, more and more complex systems are exhibiting the characteristics of social, physical, and information fusion. These systems are known as cyber-physical-social systems (CPSS) [1], [2]. These CPSS face unprecedented challenges in design, analysis, management, control and integration due to their involvement with human and social factors [3], [4]. To cope with this challenge, there are two main approaches to CPSS research.
IEEE/CAA Journal of Automatica Sinica, 2023
DO we need a fundamental change in our professional culture and knowledge foundation for control ... more DO we need a fundamental change in our professional culture and knowledge foundation for control and automation? If so, what are necessary and critical steps we must take to ensure such a change would take place effectively and efficiently, or more general, smoothly and sustainably?
This question has started circulating in my mind two decades ago right after my first two decades of research and development in automation, robotics, intelligent control, and artificial intelligence. By the end of the 20th century, the effort of achieving the initial goal of intelligent control for complex systems, such as intelligent robotic systems and smart human-machine interaction, as envisioned by its pioneers, such as K. S. Fu [1] and G. N. Saridis [2], had seemed run into and stopped by an invisible wall, as witnessed by the fact that the well-known flagship academic gathering in the field, the annual IEEE International Symposium on Intelligent Control (IEEE ISIC), was losing steam after a decade’s rapid rising since 1985 [3]. For those of you interested, related historical reviews and future perspectives can be found in [3]–[5].
IEEE/CAA Journal of Automatica Sinica, 2023
The big hit of ChatGPT makes it imperative to contemplate the practical applications of big or fo... more The big hit of ChatGPT makes it imperative to contemplate the practical applications of big or foundation models [1]–[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications. To this end, here we would like to address the issues related to building knowledge factories with knowledge machines for knowledge workers by knowledge automation, that would effectively integrate the advanced foundation models, scenarios engineering, and human-oriented operating systems (HOOS) technologies for managing digital, robotic, and biological knowledge workers, and enabling decision-making, resource coordination, and task execution through three operational modes of autonomous, parallel, and expert/emergency, to achieve intelligent production meeting the goal of “6S”: Safety, Security, Sustainability, Sensitivity, Service, and Smartness [6]–[10].
IEEE/CAA Journal of Automatica Sinica, 2023
We are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish. [1]-... more We are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish. [1]-[3]. In this new epoch, the collaboration of data and knowledge, humans and machines, actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation, unveiling an open future full of boundless possibilities. However, the value of dispersed data extends far beyond passive storage and application. Instead, it has become an incentive and driving force that connects different workers in different worlds, forming a more powerful network of knowledge. No longer monopolized by a select few organizations or companies, the community-driven data sharing and exchange enable every individual to participate and contribute [4]-[6]. The diversification, sharing and integration of data create numerous avenues for learning, exploration, and innovation.
IEEE/CAA Journal of Automatica Sinica, 2023
Recently, generative AI (GenAI) has shown its great potential for promoting the development of in... more Recently, generative AI (GenAI) has shown its great potential for promoting the development of industries, economies, and societies [6]. The advent of new generation AI technique with its human-like ability has been recognized as a game-changer for sustainable development [7]. Specifically, this emerging technology can be leveraged to understand human requirements for delivering a desirable solution, adapt to different environmental conditions for comprehensive decision-making, and provide equal access for mitigating inequality [8]. The pioneering AI technology GPT has shown great promise in finance [9] and catalyst [10] with human-like text generated based on a large language model (LLM). The advent of generative pre-trained transformer 4 (GPT4) has exhibited powerful human-level performance in real-world scenarios with dramatic parameters, thereby extracting more features to overcome more challenges by understanding human requirements, adapting to different environment conditions, and providing equality access.
IEEE/CAA Journal of Automatica Sinica, 2023
This letter contributes to designing a resilient event-triggered controller for connected automat... more This letter contributes to designing a resilient event-triggered controller for connected automated vehicles under cyber attacks, including denial-of-service (DoS) and deception attacks. To characterize the effect of DoS attacks, the effective intervals of the attack are redivided based on the sampling period. Then, a resilient distributed event-triggering mechanism is proposed to compensate for the sabotage of DoS attacks and reduce the amount of transmitted data. Since the communication channel transmits the data only at the trigger instant, deception attacks may occur at this instant and be transmitted to each vehicle in superposition with the normal signal. Therefore, we construct stochastic models satisfying Bernoulli distribution to describe the false information injected by the attackers. Based on the above framework, an attack-resilient control strategy is proposed to resist the impact of cyber attacks. Then, sufficient conditions are established to achieve stability of vehicular platoons, and a co-design strategy regarding the control gain and triggering parameter matrices is given. Finally, the simulation results are provided to substantiate the effectiveness of the proposed method.
IEEE/CAA Journal of Automatica Sinica, 2023
In this paper, the networked control problem under event-triggered schemes is considered for a cl... more In this paper, the networked control problem under event-triggered schemes is considered for a class of continuous-time linear systems with random impulses. In order to save communication costs and lighten communication burden, a dynamic event-triggered scheme whose threshold parameter is dynamically adjusted by a given evolutionary rule, is employed to manage the transmission of data packets. Moreover, the evolution of the threshold parameter only depends on the sampled measurement output, and hence eliminates the influence of impulsive signals on the event-triggered mechanism. Then, with the help of a stochastic analysis method and Lyapunov theory, the existence conditions of desired controller gains are received to guarantee the corresponding input-to-state stability of the addressed system. Furthermore, according to the semi-definite programming property, the desired controller gains are calculated by resorting to the solution of three linear matrix inequalities. In the end, the feasibility and validity of the developed control strategy are verified by a simulation example.
IEEE/CAA Journal of Automatica Sinica, 2023
Most existing domain adaptation (DA) methods aim to explore favorable performance under complicat... more Most existing domain adaptation (DA) methods aim to explore favorable performance under complicated environments by sampling. However, there are three unsolved problems that limit their efficiencies: i) they adopt global sampling but neglect to exploit global and local sampling simultaneously; ii) they either transfer knowledge from a global perspective or a local perspective, while overlooking transmission of confident knowledge from both perspectives; and iii) they apply repeated sampling during iteration, which takes a lot of time. To address these problems, knowledge transfer learning via dual density sampling (KTL-DDS) is proposed in this study, which consists of three parts: i) Dual density sampling (DDS) that jointly leverages two sampling methods associated with different views, i.e., global density sampling that extracts representative samples with the most common features and local density sampling that selects representative samples with critical boundary information; ii) Consistent maximum mean discrepancy (CMMD) that reduces intra- and cross-domain risks and guarantees high consistency of knowledge by shortening the distances of every two subsets among the four subsets collected by DDS; and iii) Knowledge dissemination (KD) that transmits confident and consistent knowledge from the representative target samples with global and local properties to the whole target domain by preserving the neighboring relationships of the target domain. Mathematical analyses show that DDS avoids repeated sampling during the iteration. With the above three actions, confident knowledge with both global and local properties is transferred, and the memory and running time are greatly reduced. In addition, a general framework named dual density sampling approximation (DDSA) is extended, which can be easily applied to other DA algorithms. Extensive experiments on five datasets in clean, label corruption (LC), feature missing (FM), and LC&FM environments demonstrate the encouraging performance of KTL-DDS.
IEEE/CAA Journal of Automatica Sinica, 2023
The secure dominating set (SDS), a variant of the dominating set, is an important combinatorial s... more The secure dominating set (SDS), a variant of the dominating set, is an important combinatorial structure used in wireless networks. In this paper, we apply algorithmic game theory to study the minimum secure dominating set (MinSDS) problem in a multi-agent system. We design a game framework for SDS and show that every Nash equilibrium (NE) is a minimal SDS, which is also a Pareto-optimal solution. We prove that the proposed game is an exact potential game, and thus NE exists, and design a polynomial-time distributed local algorithm which converges to an NE in O (n) rounds of interactions. Extensive experiments are done to test the performance of our algorithm, and some interesting phenomena are witnessed.
IEEE/CAA Journal of Automatica Sinica, 2023
This paper presents a subspace identification method for closed-loop systems with unknown determi... more This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances. To deal with the unknown deterministic disturbances, two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are known. For closed-loop identification, CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique projection. In addition, a proper Bernstein polynomial order can be determined using the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.
IEEE/CAA Journal of Automatica Sinica, 2023
Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL fr... more Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL framework, where the dynamic environment and reward sparsity can cause conventional learning algorithms to fail. Reward shaping is a practical approach to improving sample efficiency by embedding human domain knowledge into the learning process. Existing reward shaping methods for goal-conditioned RL are typically built on distance metrics with a linear and isotropic distribution, which may fail to provide sufficient information about the ever-changing environment with high complexity. This paper proposes a novel magnetic field-based reward shaping (MFRS) method for goal-conditioned RL tasks with dynamic target and obstacles. Inspired by the physical properties of magnets, we consider the target and obstacles as permanent magnets and establish the reward function according to the intensity values of the magnetic field generated by these magnets. The nonlinear and anisotropic distribution of the magnetic field intensity can provide more accessible and conducive information about the optimization landscape, thus introducing a more sophisticated magnetic reward compared to the distance-based setting. Further, we transform our magnetic reward to the form of potential-based reward shaping by learning a secondary potential function concurrently to ensure the optimal policy invariance of our method. Experiments results in both simulated and real-world robotic manipulation tasks demonstrate that MFRS outperforms relevant existing methods and effectively improves the sample efficiency of RL algorithms in goal-conditioned tasks with various dynamics of the target and obstacles.
IEEE/CAA Journal of Automatica Sinica, 2023
In the era of big data, there is an urgent need to establish data trading markets for effectively... more In the era of big data, there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data. Data security and data pricing, however, are still widely regarded as major challenges in this respect, which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms. In this context, data recording and trading are conducted separately within two separate blockchains: the data blockchain (DChain) and the value blockchain (VChain). This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market. Moreover, pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users. Specifically, in regular data trading on VChain-S2D, two auction models are employed according to the demand scale, for dealing with users’ strategic bidding. The incentive-compatible Vickrey-Clarke-Groves (VCG) model is deployed to the low-demand trading scenario, while the nearly incentive-compatible monopolistic price (MP) model is utilized for the high-demand trading scenario. With temporary data trading on VChain-D2S, a reverse auction mechanism namely two-stage obscure selection (TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies. Furthermore, experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.
IEEE/CAA Journal of Automatica Sinica, 2023
This paper addresses distributed adaptive optimal resource allocation problems over weight-balanc... more This paper addresses distributed adaptive optimal resource allocation problems over weight-balanced digraphs. By leveraging state-of-the-art adaptive coupling designs for multiagent systems, two adaptive algorithms are proposed, namely a directed-spanning-tree-based algorithm and a node-based algorithm. The benefits of these algorithms are that they require neither sufficiently small or unitary step sizes, nor global knowledge of Laplacian eigenvalues, which are widely required in the literature. It is shown that both algorithms belong to a class of uncertain saddle-point dynamics, which can be tackled by repeatedly adopting the Peter-Paul inequality in the framework of Lyapunov theory. Thanks to this new viewpoint, global asymptotic convergence of both algorithms can be proven in a unified way. The effectiveness of the proposed algorithms is validated through numerical simulations and case studies in IEEE 30-bus and 118-bus power systems.
IEEE/CAA Journal of Automatica Sinica, 2023
Inspired by the integrated guidance and control design for endo-atmospheric aircraft, the integra... more Inspired by the integrated guidance and control design for endo-atmospheric aircraft, the integrated position and attitude control of spacecraft has attracted increasing attention and gradually induced a wide variety of study results in last over two decades, fully incorporating control requirements and actuator characteristics of space missions. This paper presents a novel and comprehensive survey to the coupled position and attitude motions of spacecraft from the perspective of dynamics and control. To this end, a systematic analysis is firstly conducted in details to show the position and attitude mutual couplings of spacecraft. Particularly, in terms of the time discrepancy between spacecraft position and attitude motions, space missions can be categorized into two types: space proximity operation and space orbital maneuver. Based on this classification, the studies on the coupled dynamic modeling and the integrated control design for position and attitude motions of spacecraft are sequentially summarized and analyzed. On the one hand, various coupled position and dynamic formulations of spacecraft based on various mathematical tools are reviewed and compared from five aspects, including mission applicability, modeling simplicity, physical clearance, information matching and expansibility. On the other hand, the development of the integrated position and attitude control of spacecraft is analyzed for two space missions, and especially, five distinctive development trends are captured for space operation missions. Finally, insightful prospects on future development of the integrated position and attitude control technology of spacecraft are proposed, pointing out current primary technical issues and possible feasible solutions.