Su Weidong - Academia.edu (original) (raw)
Papers by Su Weidong
This paper is devoted to the problem of designing a sparsely distributed sliding mode control for... more This paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note employs a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the H 2 control. We then use this novel scheme to provide an innovative less-complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach. keywords Networked control systems, H 2-based optimal sparse sliding mode control, distributed control systems, linear matrix inequality.
The Journal of Biomedical Research
This survey was designed to assess the sanitation status of hospitals and the compliance of hospi... more This survey was designed to assess the sanitation status of hospitals and the compliance of hospital staff to disinfection strategies within the past 11 years. A total of 199 provincial affiliated tertiary or secondary public hospitals from 2007 to 2017 were investigated and seven critical categories, namely indoor air, work surface, hand hygiene, ultraviolet (UV) irradiation intensity, use of disinfectants, sterilization of medical items, and effects of steam sterilizer, were monitored. The average qualified rates were (94.74±3.54)% (810/855), (97.25±1.65)% (1 876/1 929), (87.57±4.60)% (2 508/2 864), (95.00±4.50)% (1 196/1 259), and (98.76±1.14)% (1 599/1 619) for indoor air, work surface, hand hygiene, UV irradiation intensity, and sterilization of medical items, respectively. In terms of other categories, a few samples were not qualified: 3/1 575 for use of disinfectants and 1/243 for effects of steam sterilizer. The hospital disinfection monitoring and supervision program effectively improved the effectiveness of disinfection. Routine monitoring and supervision must be conducted to ensure a safe hospital treatment environment.
IEEE Communications Letters, 2013
2008 10th International Conference on Control, Automation, Robotics and Vision, 2008
This paper proposes an integral controller design scheme for nonlinear systems based on optimal c... more This paper proposes an integral controller design scheme for nonlinear systems based on optimal control and the passivity theorem in order to suppress the effect of external disturbances. The main strategy is to augment an optimal controller with a PI type controller. To guarantee the proposed controller has a desired stability margin, the passivity-based design method is introduced. Here, the inverse optimal control technique is employed to avoid the need of solving a Hamilton-Jacobi equation. An illustrative example is given to show the design procedure and the controller effectiveness.
IEEE Transactions on Automatic Control, 2015
Working with the 1D form of 2D systems is an alternative strategy to reduce the inherent complexi... more Working with the 1D form of 2D systems is an alternative strategy to reduce the inherent complexity of 2D systems and their applications. To achieve the 1D form of 2D systems, different from the so-called WAM model, a new row (column) process was proposed recently. The controllability analysis of this new 1D form is explored in this paper. Two new notions of controllability named WAM-controllability and directional controllability for the underlying 2D systems are defined. Corresponding conditions on the WAM-controllability and directional controllability are derived, which are particularly useful for the control problems of 2D systems via 1D framework. According to the presented directional controllability, a directional minimum energy control input is derived for 2D systems. A numerical example demonstrates the applicability of the analysis presented in this note.
2010 11th International Conference on Control Automation Robotics & Vision, 2010
Teaching multivariable control usually involves a certain level of mathematical sophistication an... more Teaching multivariable control usually involves a certain level of mathematical sophistication and hence requires some labaratorial exemplification of the material given in formal lectures. This paper reports on a hands-on approach to multivariable control education via the implementation of a model predictive controller on a two-input, two output coupled drive apparatus. This scaled-down system represents many industrial processes while provides an excellent setup for demonstrating the cross-coupled effects in multi-input multi-output systems. Here, a model predictive controller (MPC) is developed and implemented on the basis of a constrained optimization problem to show control performance via the belt tension and velocity outputs, demonstrate the decoupling capability, and also illustrate such issues as control input saturation, the selection of operating point, reference inputs, and system robustness to external disturbance and varying parameters. The implementation is based on Labview and MATLAB Model Predictive Control Toolbox.
2012 IEEE Congress on Evolutionary Computation, 2012
Clustering can be especially effective where the data is irregular, noisy and/or not differentiab... more Clustering can be especially effective where the data is irregular, noisy and/or not differentiable. A major obstacle for many clustering techniques is that they are computationally expensive, hence limited to smaller data volume and dimension. We propose a lightweight swarm clustering solution called Rapid Centroid Estimation (RCE). Based on our experiments, RCE has significantly quickened optimization time of its predecessors, Particle Swarm Clustering (PSC) and Modified Particle Swarm Clustering (mPSC). Our experimental results show that on benchmark datasets, RCE produces generally better clusters compared to PSC, mPSC, K-means and Fuzzy C-means. Compared with K-means and Fuzzy C-means which produces clusters with 62% and 55% purities on average respectively, thyroid dataset has successfully clustered on average 71% purity in 14.3 seconds.
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
The paper proposes a robust online adaptive neural network control scheme for an automated treadm... more The paper proposes a robust online adaptive neural network control scheme for an automated treadmill system. The proposed control scheme is based on Feedback-Error Learning Approach (FELA), by using which the plant Jacobian calculation problem is avoided. Modification of the learning algorithm is proposed to solve the overtraining issue, guaranteeing to system stability and system convergence. As an adaptive neural network controller can adapt itself to deal with system uncertainties and external disturbances, this scheme is very suitable for treadmill exercise regulation when the model of the exerciser is unknown or inaccurate. In this study, exercise intensity (measured by heart rate) is regulated by simultaneously manipulating both treadmill speed and gradient in order to achieve fast tracking for which a single input multi output (SIMO) adaptive neural network controller has been designed. Real-time experiment result confirms that robust performance for nonlinear multivariable system under model uncertainties and unknown external disturbances can indeed be achieved.
Acta Mechanica Sinica, 1998
In this paper, we discuss the topological structures of the vortex filaments and vortex tubes wit... more In this paper, we discuss the topological structures of the vortex filaments and vortex tubes with an exact solution of a straight spiral vortex tube. We find that there are some confusions about the calculation of the helicities of a knotted vortex filament and some linked vortex filaments by using different methods. We explain how to unify these methods and give the right results.
This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry c... more This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results.
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
The paper proposes a robust online adaptive neural network control scheme for an automated treadm... more The paper proposes a robust online adaptive neural network control scheme for an automated treadmill system. The proposed control scheme is based on Feedback-Error Learning Approach (FELA), by using which the plant Jacobian calculation problem is avoided. Modification of the learning algorithm is proposed to solve the overtraining issue, guaranteeing to system stability and system convergence. As an adaptive neural network controller can adapt itself to deal with system uncertainties and external disturbances, this scheme is very suitable for treadmill exercise regulation when the model of the exerciser is unknown or inaccurate. In this study, exercise intensity (measured by heart rate) is regulated by simultaneously manipulating both treadmill speed and gradient in order to achieve fast tracking for which a single input multi output (SIMO) adaptive neural network controller has been designed. Real-time experiment result confirms that robust performance for nonlinear multivariable system under model uncertainties and unknown external disturbances can indeed be achieved.
This paper presents the design of a variable inductor with a rotational magnetic core whose posit... more This paper presents the design of a variable inductor with a rotational magnetic core whose position is controlled in a closed-loop system. This magnetic structure facilitates the impedance changes which may be used for load balancing, harmonics elimination, transient response improvement, and as a controlled reactor in static VAr compensation (SVC). The design of the inductor and analysis of its impedance change caused by positioning a movable element are carried out by using the finite element method. As a result, the variation range of the impedance is determined. The proposed variable inductor is compared with a typical SVC reactor. The results show good performances in static var compensation with higher reliability and no harmonics generated. For closed-loop control, a secondorder sliding mode controller is designed for position control of the rotating core via a DC motor. Simulation results of the proposed system present highly robust and accurate responses without control chattering in face of nonlinearities and disturbances.
2012 IEEE Congress on Evolutionary Computation, 2012
ABSTRACT Clustering can be especially effective where the data is irregular, noisy and/or not dif... more ABSTRACT Clustering can be especially effective where the data is irregular, noisy and/or not differentiable. A major obstacle for many clustering techniques is that they are computationally expensive, hence limited to smaller data volume and dimension. We propose a lightweight swarm clustering solution called Rapid Centroid Estimation (RCE). Based on our experiments, RCE has significantly quickened optimization time of its predecessors, Particle Swarm Clustering (PSC) and Modified Particle Swarm Clustering (mPSC). Our experimental results show that on benchmark datasets, RCE produces generally better clusters compared to PSC, mPSC, K-means and Fuzzy C-means. Compared with K-means and Fuzzy C-means which produces clusters with 62% and 55% purities on average respectively, thyroid dataset has successfully clustered on average 71% purity in 14.3 seconds.
This paper is devoted to the problem of designing a sparsely distributed sliding mode control for... more This paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note employs a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the H 2 control. We then use this novel scheme to provide an innovative less-complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach. keywords Networked control systems, H 2-based optimal sparse sliding mode control, distributed control systems, linear matrix inequality.
The Journal of Biomedical Research
This survey was designed to assess the sanitation status of hospitals and the compliance of hospi... more This survey was designed to assess the sanitation status of hospitals and the compliance of hospital staff to disinfection strategies within the past 11 years. A total of 199 provincial affiliated tertiary or secondary public hospitals from 2007 to 2017 were investigated and seven critical categories, namely indoor air, work surface, hand hygiene, ultraviolet (UV) irradiation intensity, use of disinfectants, sterilization of medical items, and effects of steam sterilizer, were monitored. The average qualified rates were (94.74±3.54)% (810/855), (97.25±1.65)% (1 876/1 929), (87.57±4.60)% (2 508/2 864), (95.00±4.50)% (1 196/1 259), and (98.76±1.14)% (1 599/1 619) for indoor air, work surface, hand hygiene, UV irradiation intensity, and sterilization of medical items, respectively. In terms of other categories, a few samples were not qualified: 3/1 575 for use of disinfectants and 1/243 for effects of steam sterilizer. The hospital disinfection monitoring and supervision program effectively improved the effectiveness of disinfection. Routine monitoring and supervision must be conducted to ensure a safe hospital treatment environment.
IEEE Communications Letters, 2013
2008 10th International Conference on Control, Automation, Robotics and Vision, 2008
This paper proposes an integral controller design scheme for nonlinear systems based on optimal c... more This paper proposes an integral controller design scheme for nonlinear systems based on optimal control and the passivity theorem in order to suppress the effect of external disturbances. The main strategy is to augment an optimal controller with a PI type controller. To guarantee the proposed controller has a desired stability margin, the passivity-based design method is introduced. Here, the inverse optimal control technique is employed to avoid the need of solving a Hamilton-Jacobi equation. An illustrative example is given to show the design procedure and the controller effectiveness.
IEEE Transactions on Automatic Control, 2015
Working with the 1D form of 2D systems is an alternative strategy to reduce the inherent complexi... more Working with the 1D form of 2D systems is an alternative strategy to reduce the inherent complexity of 2D systems and their applications. To achieve the 1D form of 2D systems, different from the so-called WAM model, a new row (column) process was proposed recently. The controllability analysis of this new 1D form is explored in this paper. Two new notions of controllability named WAM-controllability and directional controllability for the underlying 2D systems are defined. Corresponding conditions on the WAM-controllability and directional controllability are derived, which are particularly useful for the control problems of 2D systems via 1D framework. According to the presented directional controllability, a directional minimum energy control input is derived for 2D systems. A numerical example demonstrates the applicability of the analysis presented in this note.
2010 11th International Conference on Control Automation Robotics & Vision, 2010
Teaching multivariable control usually involves a certain level of mathematical sophistication an... more Teaching multivariable control usually involves a certain level of mathematical sophistication and hence requires some labaratorial exemplification of the material given in formal lectures. This paper reports on a hands-on approach to multivariable control education via the implementation of a model predictive controller on a two-input, two output coupled drive apparatus. This scaled-down system represents many industrial processes while provides an excellent setup for demonstrating the cross-coupled effects in multi-input multi-output systems. Here, a model predictive controller (MPC) is developed and implemented on the basis of a constrained optimization problem to show control performance via the belt tension and velocity outputs, demonstrate the decoupling capability, and also illustrate such issues as control input saturation, the selection of operating point, reference inputs, and system robustness to external disturbance and varying parameters. The implementation is based on Labview and MATLAB Model Predictive Control Toolbox.
2012 IEEE Congress on Evolutionary Computation, 2012
Clustering can be especially effective where the data is irregular, noisy and/or not differentiab... more Clustering can be especially effective where the data is irregular, noisy and/or not differentiable. A major obstacle for many clustering techniques is that they are computationally expensive, hence limited to smaller data volume and dimension. We propose a lightweight swarm clustering solution called Rapid Centroid Estimation (RCE). Based on our experiments, RCE has significantly quickened optimization time of its predecessors, Particle Swarm Clustering (PSC) and Modified Particle Swarm Clustering (mPSC). Our experimental results show that on benchmark datasets, RCE produces generally better clusters compared to PSC, mPSC, K-means and Fuzzy C-means. Compared with K-means and Fuzzy C-means which produces clusters with 62% and 55% purities on average respectively, thyroid dataset has successfully clustered on average 71% purity in 14.3 seconds.
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
The paper proposes a robust online adaptive neural network control scheme for an automated treadm... more The paper proposes a robust online adaptive neural network control scheme for an automated treadmill system. The proposed control scheme is based on Feedback-Error Learning Approach (FELA), by using which the plant Jacobian calculation problem is avoided. Modification of the learning algorithm is proposed to solve the overtraining issue, guaranteeing to system stability and system convergence. As an adaptive neural network controller can adapt itself to deal with system uncertainties and external disturbances, this scheme is very suitable for treadmill exercise regulation when the model of the exerciser is unknown or inaccurate. In this study, exercise intensity (measured by heart rate) is regulated by simultaneously manipulating both treadmill speed and gradient in order to achieve fast tracking for which a single input multi output (SIMO) adaptive neural network controller has been designed. Real-time experiment result confirms that robust performance for nonlinear multivariable system under model uncertainties and unknown external disturbances can indeed be achieved.
Acta Mechanica Sinica, 1998
In this paper, we discuss the topological structures of the vortex filaments and vortex tubes wit... more In this paper, we discuss the topological structures of the vortex filaments and vortex tubes with an exact solution of a straight spiral vortex tube. We find that there are some confusions about the calculation of the helicities of a knotted vortex filament and some linked vortex filaments by using different methods. We explain how to unify these methods and give the right results.
This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry c... more This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results.
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
The paper proposes a robust online adaptive neural network control scheme for an automated treadm... more The paper proposes a robust online adaptive neural network control scheme for an automated treadmill system. The proposed control scheme is based on Feedback-Error Learning Approach (FELA), by using which the plant Jacobian calculation problem is avoided. Modification of the learning algorithm is proposed to solve the overtraining issue, guaranteeing to system stability and system convergence. As an adaptive neural network controller can adapt itself to deal with system uncertainties and external disturbances, this scheme is very suitable for treadmill exercise regulation when the model of the exerciser is unknown or inaccurate. In this study, exercise intensity (measured by heart rate) is regulated by simultaneously manipulating both treadmill speed and gradient in order to achieve fast tracking for which a single input multi output (SIMO) adaptive neural network controller has been designed. Real-time experiment result confirms that robust performance for nonlinear multivariable system under model uncertainties and unknown external disturbances can indeed be achieved.
This paper presents the design of a variable inductor with a rotational magnetic core whose posit... more This paper presents the design of a variable inductor with a rotational magnetic core whose position is controlled in a closed-loop system. This magnetic structure facilitates the impedance changes which may be used for load balancing, harmonics elimination, transient response improvement, and as a controlled reactor in static VAr compensation (SVC). The design of the inductor and analysis of its impedance change caused by positioning a movable element are carried out by using the finite element method. As a result, the variation range of the impedance is determined. The proposed variable inductor is compared with a typical SVC reactor. The results show good performances in static var compensation with higher reliability and no harmonics generated. For closed-loop control, a secondorder sliding mode controller is designed for position control of the rotating core via a DC motor. Simulation results of the proposed system present highly robust and accurate responses without control chattering in face of nonlinearities and disturbances.
2012 IEEE Congress on Evolutionary Computation, 2012
ABSTRACT Clustering can be especially effective where the data is irregular, noisy and/or not dif... more ABSTRACT Clustering can be especially effective where the data is irregular, noisy and/or not differentiable. A major obstacle for many clustering techniques is that they are computationally expensive, hence limited to smaller data volume and dimension. We propose a lightweight swarm clustering solution called Rapid Centroid Estimation (RCE). Based on our experiments, RCE has significantly quickened optimization time of its predecessors, Particle Swarm Clustering (PSC) and Modified Particle Swarm Clustering (mPSC). Our experimental results show that on benchmark datasets, RCE produces generally better clusters compared to PSC, mPSC, K-means and Fuzzy C-means. Compared with K-means and Fuzzy C-means which produces clusters with 62% and 55% purities on average respectively, thyroid dataset has successfully clustered on average 71% purity in 14.3 seconds.