Dong Hwa Kim | HanBat National University (original) (raw)

Papers by Dong Hwa Kim

Computational Science - ICCS 2004, 2004

Dead time processes exist widely in many types of systems such as chemical processes, and the mai... more Dead time processes exist widely in many types of systems such as chemical processes, and the main steam temperature control system of the thermal power plant. A PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests a tuning method of the PID Controller for a process with long dead time using an immune algorithm typed neural network, through computer simulation. Tuning results of immune algorithms based neural network are compared with the results of genetic algorithm.

Lecture Notes in Computer Science, 2004

The purpose of introducing a combined cycle with gas turbine in power plants is to reduce losses ... more The purpose of introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. This paper focuses on the characteristic comparison of the PID controller, the 2-DOF PID controllers, and the modified 2-DOF PID controller, in order to design an optimal controller which can be operated on the Gun-san gas turbine generating plant in Gun-san, Korea. The designed controllers, using various methods based on this transfer function and data have been compared to the Gun-san gas turbine system for the start-up procedure and this parameter could be used for the tuning problem.

The PSO conducts searches using a population of particles which correspond to individuals in GA. ... more The PSO conducts searches using a population of particles which correspond to individuals in GA. A population of particles is randomly generated initially. Each particle represents a potential solution and has a position represented by a position vector. A swarm of particles moves through the problem space, with the moving velocity of each particle represented by a velocity vector. At each time step, a function representing a quality measure is calculated by using as input. Each particle keeps track of its own best position, which is associated with the best fitness it has achieved so far in a vector. Furthermore, the best position among all the particles obtained so far in the population is kept track as output. In addition to this global version, another local version of PSO keeps track of the best position among all the topological neighbors of a particle. At each time step, by using the individual best position, and global best position, a new velocity for particle is updated by...

ABSTRACT: This paper focuses on design of nonlinear power plant controller using immune based mul... more ABSTRACT: This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

This paper represents that auto tuning of 2-DOF PID Controller can be effectively performed by im... more This paper represents that auto tuning of 2-DOF PID Controller can be effectively performed by immune algorithms. A number of tuning approaches for PID controllers are considered in the context of intelligent tuning methods. However, in the case of 2-DOF PID Controller, quite a few tuning based on the classical approach such a trial and error has been suggested. Also, a general view is provided that they are the special cases of either the linear model or the single control system. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provide optimal solution. Simulation results reveal that immune algorithms based tuning are an effective approaches to search for optimal or near optimal control. I.

Applied Soft Computing, 2011

This paper deals with hybrid system (GA-BF) based on the conventional GA (Genetic Algorithm) and ... more This paper deals with hybrid system (GA-BF) based on the conventional GA (Genetic Algorithm) and BF (Bacterial Foraging) which is the social foraging behavior of bacteria. A variety of test function is introduced and simulated to illustrate the characteristics and performance by mutation, crossover, variation of step size, variation of chemotactic step, and variation of lifetime of bacteria in the proposed hybrid system GA-BF. The simulated results represent that the proposed method is highly satisfactory. This approach provides us with novel hybrid model based on foraging behavior and also with a possible new connection between evolutionary forces in social foraging and distributed nongradient optimization algorithm design for global optimization over noisy surfaces.

Citeseer, 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes bacteria foraging algorithm based optimal learning fuzzy-neural network (BA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by bacteria foraging algorithm. The learning algorithm of the BA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, bacteria foraging algorithm is used for tuning of membership functions of the proposed model.

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy -neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model. Keyword:Fuzzy neural network; Immune algorithm; Multiobjective control; Optimzation.

Information Sciences, 2007

The social foraging behavior of Escherichia coli bacteria has been used to solve optimization pro... more The social foraging behavior of Escherichia coli bacteria has been used to solve optimization problems. This paper proposes a hybrid approach involving genetic algorithms (GA) and bacterial foraging (BF) algorithms for function optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the lifetime of the bacteria. The proposed algorithm is then used to tune a PID controller of an automatic voltage regulator (AVR). Simulation results clearly illustrate that the proposed approach is very efficient and could easily be extended for other global optimization problems.

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes particle swarm optimization algorithm based optimal learning fuzzy-neural network (PSOA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by particle swarm optimization algorithm. The learning algorithm of the PSOA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, particle swarm optimization algorithm is used for tuning of membership functions of the proposed model.

control, multivariable DCS control. Abstract—Process systems such as the raw water and chemical i... more control, multivariable DCS control. Abstract—Process systems such as the raw water and chemical injection line in purification, the flow line of the waste water system, and the feed water, or the circulation system of a power plant system must be controlled accurately, because the system's performance and the energy saving rate in the whole system depend on the control method and precision. Generally, a PI controller is used in these systems, but it is very difficult to find an optimum parameter for the controller, because of the coupling action among loops and the disturbance in the system loop. There are few experimental systems or educational courses for such processes. This paper introduces an experimental method and educational course into the curriculum, to build up effective instruction of this complicated multivariable porcess system. Also, this paper proposes a new control method that changes the fluid system of a multivariable control loop and applies a NN-Tuning 2-DOF...

This paper suggests that the immune network algorithm based on fuzzy set can effectively be used ... more This paper suggests that the immune network algorithm based on fuzzy set can effectively be used in tuning of a PID controller for multivariable process or nonlinear process. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through t he stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used the fuzzy set in order that the stimulation and suppression relationship between antibody and antigen can be more adaptable controlled against the external condition, including noise or disturbance of plant. The immune network based on fuzzy set suggested here is applied for the PID controller tuning of multivariable process with two inputs and one output and is simulated. The result of study shows the artificial immune based on fuzzy set can effectively be used to tune the nonlinear process or the multivariable process, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods, against the noise or disturbance, various inputs, and coupling action between loops.

IAES International Journal of Robotics and Automation (IJRA), 2020

This study introduces the control method of duct cleaning robot that enables real-time position t... more This study introduces the control method of duct cleaning robot that enables real-time position tracking and self-driving over L-shaped and T-shaped duct sections. The developed robot has three legs and is designed to flexibly respond to duct sizes. The position of the robot inside the duct is identified using the UWB communication module and the location estimation algorithm. Although UWB communication has relatively large distance error within the metal, the positional error was reduced by introducing appropriate filters to estimate the robot position accurately. TCP/IP communication allows commands to be sent between the PC and the robot and to receive live images of the camera attached to the robot. Using Haar-like and classifiers, the robot can recognize the type of duct that is difficult to overcome, such as L-shaped and T-shaped duct, and it moves successfully inside the duct according to the corresponding moving algorithms.

International Journal of Control, Automation and Systems, 2011

Journal of Advanced Computational Intelligence and Intelligent Informatics, 2005

We propose a design approach to PID controllers with resistance to external disturbance in motor-... more We propose a design approach to PID controllers with resistance to external disturbance in motor-controlled systems using a bacterial foraging-based optimal algorithm. PID controllers are used to operate AC motor drives because of their practical implementation and simple structure. Inexperienced personnel find it difficult, however, to achieve optimal PID gain because this is manually tuned by trial and error in industrial environments full of disturbances. To design disturbance-resistance tuning, we use disturbance-resistance conditions based on H∞ and calculcate response the performance based on bacterial foraging for the PID controller as an integral of time-weighted squared error. Hence, parameters for the PID controller are selected by our bacterial foraging-based optimal algorithm to obtain the required response.

2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, 2014

This lecture deals with intelligent method based emotional actuator design approaches. Emotional ... more This lecture deals with intelligent method based emotional actuator design approaches. Emotional intelligence has been described as the capacity to monitor and regulate one's own feeling and others' feelings, and to use feelings to guide thought and action by Salovey and Mayer in 1990. In light of the above agent definitions, we may have a different decision because entity whose state includes not only mental components of belief, capabilities, choices, and commitments, but emotional components of mood, preference, attitude, and feeling. Here, technologies for emotionally oriented control strategies or actuator design or programming architectures should be allowed to compute with consistency and appropriate relatedness between emotion and intellect. From the biological information processing view, emotional intelligence may be practically defined as the ability to use "emotional knowledge" in the mapping from percepts to actions. Recently, theoretically or neurologically we have commonly been researching that most artificial intelligences have come from emulating activities in bio areas or mathematical tools.

2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), 2010

Traditionally intelligence systems are popular in robotics, decision-making, multimedia processin... more Traditionally intelligence systems are popular in robotics, decision-making, multimedia processing, data mining etc. Recently, green technology and CO 2 gas reduction issues have been a major issue, paving the way for artificial intelligence researchers to formulate effective solutions. Therefore, there are good prospects for researchers to study green technology and C0 2 gas reduction problems because those issues are directly affecting our daily life. Energy saving and development, power management for renewable energy sources are very important for green technology and CO 2 gas reduction. This paper describes our application methods studied up to now for evaluating green technology.

Lecture Notes in Computer Science, 2004

A PID Controller has been used to operate this system because of its implementational advantages.... more A PID Controller has been used to operate this system because of its implementational advantages. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the PID Controller with disturbance rejection using immune network algorithm. To decide the performance of response, an ITSE (Integral of time weighted squared error) is used in this paper. 2 Control Characteristics of Thermal Power Plant for Controller Design A thermal power plant is mainly composed of one boiler whose steam output feeds one or two turbine, driving an electric generator. There can be many available models for each subsystem with a varying degree of complexity and accuracy. The models

The Scientific World Journal, 2013

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective... more The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results sug...

Up to the present time, PID Controller has been widely used to control industrial process loops b... more Up to the present time, PID Controller has been widely used to control industrial process loops because of its implementational advantages. However, it is very difficult to achieve an optimal PID gain with no experience, since the parameters of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the PID controller using gain/phase margin and immune algorithm. After deciding optimal gain/phase margin specifications for the given process, the gains of PID controller using fitness value of immune algorithm depending on error between optimal gain/phase margin and the gain/phase margin obtained by tuning is tuned for the required response. To improve effectiveness of the suggested scheme, simulation results are compared with the FNN (Fuzzy Neural Network) based responses and illustrate more desirable performance.

Computational Science - ICCS 2004, 2004

Dead time processes exist widely in many types of systems such as chemical processes, and the mai... more Dead time processes exist widely in many types of systems such as chemical processes, and the main steam temperature control system of the thermal power plant. A PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests a tuning method of the PID Controller for a process with long dead time using an immune algorithm typed neural network, through computer simulation. Tuning results of immune algorithms based neural network are compared with the results of genetic algorithm.

Lecture Notes in Computer Science, 2004

The purpose of introducing a combined cycle with gas turbine in power plants is to reduce losses ... more The purpose of introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. This paper focuses on the characteristic comparison of the PID controller, the 2-DOF PID controllers, and the modified 2-DOF PID controller, in order to design an optimal controller which can be operated on the Gun-san gas turbine generating plant in Gun-san, Korea. The designed controllers, using various methods based on this transfer function and data have been compared to the Gun-san gas turbine system for the start-up procedure and this parameter could be used for the tuning problem.

The PSO conducts searches using a population of particles which correspond to individuals in GA. ... more The PSO conducts searches using a population of particles which correspond to individuals in GA. A population of particles is randomly generated initially. Each particle represents a potential solution and has a position represented by a position vector. A swarm of particles moves through the problem space, with the moving velocity of each particle represented by a velocity vector. At each time step, a function representing a quality measure is calculated by using as input. Each particle keeps track of its own best position, which is associated with the best fitness it has achieved so far in a vector. Furthermore, the best position among all the particles obtained so far in the population is kept track as output. In addition to this global version, another local version of PSO keeps track of the best position among all the topological neighbors of a particle. At each time step, by using the individual best position, and global best position, a new velocity for particle is updated by...

ABSTRACT: This paper focuses on design of nonlinear power plant controller using immune based mul... more ABSTRACT: This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

This paper represents that auto tuning of 2-DOF PID Controller can be effectively performed by im... more This paper represents that auto tuning of 2-DOF PID Controller can be effectively performed by immune algorithms. A number of tuning approaches for PID controllers are considered in the context of intelligent tuning methods. However, in the case of 2-DOF PID Controller, quite a few tuning based on the classical approach such a trial and error has been suggested. Also, a general view is provided that they are the special cases of either the linear model or the single control system. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provide optimal solution. Simulation results reveal that immune algorithms based tuning are an effective approaches to search for optimal or near optimal control. I.

Applied Soft Computing, 2011

This paper deals with hybrid system (GA-BF) based on the conventional GA (Genetic Algorithm) and ... more This paper deals with hybrid system (GA-BF) based on the conventional GA (Genetic Algorithm) and BF (Bacterial Foraging) which is the social foraging behavior of bacteria. A variety of test function is introduced and simulated to illustrate the characteristics and performance by mutation, crossover, variation of step size, variation of chemotactic step, and variation of lifetime of bacteria in the proposed hybrid system GA-BF. The simulated results represent that the proposed method is highly satisfactory. This approach provides us with novel hybrid model based on foraging behavior and also with a possible new connection between evolutionary forces in social foraging and distributed nongradient optimization algorithm design for global optimization over noisy surfaces.

Citeseer, 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes bacteria foraging algorithm based optimal learning fuzzy-neural network (BA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by bacteria foraging algorithm. The learning algorithm of the BA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, bacteria foraging algorithm is used for tuning of membership functions of the proposed model.

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy -neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model. Keyword:Fuzzy neural network; Immune algorithm; Multiobjective control; Optimzation.

Information Sciences, 2007

The social foraging behavior of Escherichia coli bacteria has been used to solve optimization pro... more The social foraging behavior of Escherichia coli bacteria has been used to solve optimization problems. This paper proposes a hybrid approach involving genetic algorithms (GA) and bacterial foraging (BF) algorithms for function optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the lifetime of the bacteria. The proposed algorithm is then used to tune a PID controller of an automatic voltage regulator (AVR). Simulation results clearly illustrate that the proposed approach is very efficient and could easily be extended for other global optimization problems.

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of ling... more Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes particle swarm optimization algorithm based optimal learning fuzzy-neural network (PSOA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by particle swarm optimization algorithm. The learning algorithm of the PSOA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, particle swarm optimization algorithm is used for tuning of membership functions of the proposed model.

control, multivariable DCS control. Abstract—Process systems such as the raw water and chemical i... more control, multivariable DCS control. Abstract—Process systems such as the raw water and chemical injection line in purification, the flow line of the waste water system, and the feed water, or the circulation system of a power plant system must be controlled accurately, because the system's performance and the energy saving rate in the whole system depend on the control method and precision. Generally, a PI controller is used in these systems, but it is very difficult to find an optimum parameter for the controller, because of the coupling action among loops and the disturbance in the system loop. There are few experimental systems or educational courses for such processes. This paper introduces an experimental method and educational course into the curriculum, to build up effective instruction of this complicated multivariable porcess system. Also, this paper proposes a new control method that changes the fluid system of a multivariable control loop and applies a NN-Tuning 2-DOF...

This paper suggests that the immune network algorithm based on fuzzy set can effectively be used ... more This paper suggests that the immune network algorithm based on fuzzy set can effectively be used in tuning of a PID controller for multivariable process or nonlinear process. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through t he stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used the fuzzy set in order that the stimulation and suppression relationship between antibody and antigen can be more adaptable controlled against the external condition, including noise or disturbance of plant. The immune network based on fuzzy set suggested here is applied for the PID controller tuning of multivariable process with two inputs and one output and is simulated. The result of study shows the artificial immune based on fuzzy set can effectively be used to tune the nonlinear process or the multivariable process, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods, against the noise or disturbance, various inputs, and coupling action between loops.

IAES International Journal of Robotics and Automation (IJRA), 2020

This study introduces the control method of duct cleaning robot that enables real-time position t... more This study introduces the control method of duct cleaning robot that enables real-time position tracking and self-driving over L-shaped and T-shaped duct sections. The developed robot has three legs and is designed to flexibly respond to duct sizes. The position of the robot inside the duct is identified using the UWB communication module and the location estimation algorithm. Although UWB communication has relatively large distance error within the metal, the positional error was reduced by introducing appropriate filters to estimate the robot position accurately. TCP/IP communication allows commands to be sent between the PC and the robot and to receive live images of the camera attached to the robot. Using Haar-like and classifiers, the robot can recognize the type of duct that is difficult to overcome, such as L-shaped and T-shaped duct, and it moves successfully inside the duct according to the corresponding moving algorithms.

International Journal of Control, Automation and Systems, 2011

Journal of Advanced Computational Intelligence and Intelligent Informatics, 2005

We propose a design approach to PID controllers with resistance to external disturbance in motor-... more We propose a design approach to PID controllers with resistance to external disturbance in motor-controlled systems using a bacterial foraging-based optimal algorithm. PID controllers are used to operate AC motor drives because of their practical implementation and simple structure. Inexperienced personnel find it difficult, however, to achieve optimal PID gain because this is manually tuned by trial and error in industrial environments full of disturbances. To design disturbance-resistance tuning, we use disturbance-resistance conditions based on H∞ and calculcate response the performance based on bacterial foraging for the PID controller as an integral of time-weighted squared error. Hence, parameters for the PID controller are selected by our bacterial foraging-based optimal algorithm to obtain the required response.

2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, 2014

This lecture deals with intelligent method based emotional actuator design approaches. Emotional ... more This lecture deals with intelligent method based emotional actuator design approaches. Emotional intelligence has been described as the capacity to monitor and regulate one's own feeling and others' feelings, and to use feelings to guide thought and action by Salovey and Mayer in 1990. In light of the above agent definitions, we may have a different decision because entity whose state includes not only mental components of belief, capabilities, choices, and commitments, but emotional components of mood, preference, attitude, and feeling. Here, technologies for emotionally oriented control strategies or actuator design or programming architectures should be allowed to compute with consistency and appropriate relatedness between emotion and intellect. From the biological information processing view, emotional intelligence may be practically defined as the ability to use "emotional knowledge" in the mapping from percepts to actions. Recently, theoretically or neurologically we have commonly been researching that most artificial intelligences have come from emulating activities in bio areas or mathematical tools.

2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), 2010

Traditionally intelligence systems are popular in robotics, decision-making, multimedia processin... more Traditionally intelligence systems are popular in robotics, decision-making, multimedia processing, data mining etc. Recently, green technology and CO 2 gas reduction issues have been a major issue, paving the way for artificial intelligence researchers to formulate effective solutions. Therefore, there are good prospects for researchers to study green technology and C0 2 gas reduction problems because those issues are directly affecting our daily life. Energy saving and development, power management for renewable energy sources are very important for green technology and CO 2 gas reduction. This paper describes our application methods studied up to now for evaluating green technology.

Lecture Notes in Computer Science, 2004

A PID Controller has been used to operate this system because of its implementational advantages.... more A PID Controller has been used to operate this system because of its implementational advantages. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the PID Controller with disturbance rejection using immune network algorithm. To decide the performance of response, an ITSE (Integral of time weighted squared error) is used in this paper. 2 Control Characteristics of Thermal Power Plant for Controller Design A thermal power plant is mainly composed of one boiler whose steam output feeds one or two turbine, driving an electric generator. There can be many available models for each subsystem with a varying degree of complexity and accuracy. The models

The Scientific World Journal, 2013

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective... more The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results sug...

Up to the present time, PID Controller has been widely used to control industrial process loops b... more Up to the present time, PID Controller has been widely used to control industrial process loops because of its implementational advantages. However, it is very difficult to achieve an optimal PID gain with no experience, since the parameters of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the PID controller using gain/phase margin and immune algorithm. After deciding optimal gain/phase margin specifications for the given process, the gains of PID controller using fitness value of immune algorithm depending on error between optimal gain/phase margin and the gain/phase margin obtained by tuning is tuned for the required response. To improve effectiveness of the suggested scheme, simulation results are compared with the FNN (Fuzzy Neural Network) based responses and illustrate more desirable performance.