Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical sy...Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method.展开更多
In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） contr...In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.展开更多
The accurate model is the most important and basic condition for the application of advanced process control, but the conventional methods do not provide satisfactory results in the case of unstable processes. To effe...The accurate model is the most important and basic condition for the application of advanced process control, but the conventional methods do not provide satisfactory results in the case of unstable processes. To effec-tively control these processes, a novel identification method (Model Parameters and Initial States Identification si-multaneously in closed loop —MPISI) is proposed. The model parameters and initial states of state equation can be simultaneously identified using this method. The results of simulation and application show that this method has the advantageous of disturbance-rejection and robustness. This method proposes a novel way for the optimization and the advanced control of the process systems.展开更多
This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and incre...This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink?. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.展开更多
This study proposes a hybrid controller by combining a proportional-integral-derivative （PID） control and a model reference adaptive control （MRAC）, which named as PID ＋ MRAC controller. The convergence performan...This study proposes a hybrid controller by combining a proportional-integral-derivative （PID） control and a model reference adaptive control （MRAC）, which named as PID ＋ MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID ＋ MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID ＋MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.展开更多
Standard genetic algorithms （SGAs） are investigated to optimise discrete-time proportional-integral-derivative （PID） con- troller parameters, by three tuning approaches, for a multivariable glass furnace process w...Standard genetic algorithms （SGAs） are investigated to optimise discrete-time proportional-integral-derivative （PID） con- troller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms （SGAs） are used to identify control oriented models of the plant which are subsequently used for controller optimisa- tion. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction.展开更多
Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling...Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.展开更多
In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking performance.Despite existing optimisations,tracking in complex environments remains insufficient.To address ...In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking performance.Despite existing optimisations,tracking in complex environments remains insufficient.To address this issue,the authors propose a tailored visual navigation tracking system for crowded scenes.For target disappearance,an autonomous navigation strategy based on target coordinates,utilising a path memory bank for intelligent search and re‐tracking is introduced.This significantly enhances tracking success.To handle target occlusion,the system relies on appearance features extracted by a target detection network and a feature memory bank for enhanced sensitivity.Servo control technology ensures robust target tracking by fully utilising appearance information and motion characteristics,even in occluded scenarios.Comprehensive testing on the OTB100 dataset validates the system's effectiveness in addressing target tracking challenges in diverse crowded environments,affirming algorithm robustness.展开更多
In this paper, graphical-user-interface （GUI） software for simulation and fuzzy-logic control of a remotely operated vehicle （ROV） using MATLABTM GUI Designing Environment is proposed. The proposed ROV＇s GUI plat...In this paper, graphical-user-interface （GUI） software for simulation and fuzzy-logic control of a remotely operated vehicle （ROV） using MATLABTM GUI Designing Environment is proposed. The proposed ROV＇s GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative （PID） and sliding-mode controller （SMC） systematically and interactively. External disturbance such as sea current can he added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.展开更多
The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sources such as solar and wind necessitate the use of an efficient load frequency control(LFC...The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sources such as solar and wind necessitate the use of an efficient load frequency control(LFC)technique.Therefore,a hybrid version of two metaheuristic algorithms(arithmetic optimization and African vulture’s optimization algorithm)is developed.It is called the‘arithmetic optimized African vulture’s optimization algorithm(AOAVOA)’.This algorithm is used to tune a novel type-2 fuzzy-based proportional–derivative branched with dual degree-of-freedom proportional–integral–derivative controller for the LFC of a three-area hybrid deregulated power system.Thermal,electric vehicle(EV),and DRG sources(including a solar panel and a wind turbine system)are con-nected in area-1.Area-2 involves thermal and gas-generating units(GUs),while thermal and geothermal units are linked in area-3.Practical restrictions such as thermo-boiler dynamics,thermal-governor dead-band,and genera-tion rate constraints are also considered.The proposed LFC method is compared to other controllers and optimizers to demonstrate its superiority in rejecting step and random load disturbances.By functioning as energy storage ele-ments,EVs and DRG units can enhance dynamic responses during peak demand.As a result,the effect of the afore-mentioned units on dynamic reactions is also investigated.To validate its effectiveness,the closed-loop system is subjected to robust stability analysis and is compared to various existing control schemes from the literature.It is determined that the suggested AOAVOA improves fitness by 40.20%over the arithmetic optimizer(AO),while fre-quency regulation is improved by 4.55%over an AO-tuned type-2 fuzzy-based branched controller.展开更多
文摘Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method.
文摘In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.
基金Supported by the Common Project Plan of Beijing Municipal Education Commission (No.100100435).
文摘The accurate model is the most important and basic condition for the application of advanced process control, but the conventional methods do not provide satisfactory results in the case of unstable processes. To effec-tively control these processes, a novel identification method (Model Parameters and Initial States Identification si-multaneously in closed loop —MPISI) is proposed. The model parameters and initial states of state equation can be simultaneously identified using this method. The results of simulation and application show that this method has the advantageous of disturbance-rejection and robustness. This method proposes a novel way for the optimization and the advanced control of the process systems.
文摘This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink?. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.
文摘This study proposes a hybrid controller by combining a proportional-integral-derivative （PID） control and a model reference adaptive control （MRAC）, which named as PID ＋ MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID ＋ MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID ＋MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.
文摘Standard genetic algorithms （SGAs） are investigated to optimise discrete-time proportional-integral-derivative （PID） con- troller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms （SGAs） are used to identify control oriented models of the plant which are subsequently used for controller optimisa- tion. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction.
基金Work supported by the Lancaster University,UK and Jiangsu Provincial Laboratory of Advanced Robotics,SooChow University,ChinaProject(BK2009509) supported by the Natural Science Foundation of Jiangsu Province,China+1 种基金Project(K5117827) supported by the Scientific Research Foundation for the Returned Scholars,Ministry of Education of ChinaProject(Q3117918) supported by the Scientific Research Foundation for Young Teachers of Soochow University,China
文摘Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.
基金Key Discipline Project of Smart Animal Husbandry,Grant/Award Number:XJXK202201Henan Province Science and Technology Research Projects,Grant/Award Number:232102210101。
文摘In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking performance.Despite existing optimisations,tracking in complex environments remains insufficient.To address this issue,the authors propose a tailored visual navigation tracking system for crowded scenes.For target disappearance,an autonomous navigation strategy based on target coordinates,utilising a path memory bank for intelligent search and re‐tracking is introduced.This significantly enhances tracking success.To handle target occlusion,the system relies on appearance features extracted by a target detection network and a feature memory bank for enhanced sensitivity.Servo control technology ensures robust target tracking by fully utilising appearance information and motion characteristics,even in occluded scenarios.Comprehensive testing on the OTB100 dataset validates the system's effectiveness in addressing target tracking challenges in diverse crowded environments,affirming algorithm robustness.
基金Supported by the Newcastle University’s Project Account:C0570D2330
文摘In this paper, graphical-user-interface （GUI） software for simulation and fuzzy-logic control of a remotely operated vehicle （ROV） using MATLABTM GUI Designing Environment is proposed. The proposed ROV＇s GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative （PID） and sliding-mode controller （SMC） systematically and interactively. External disturbance such as sea current can he added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.
文摘The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sources such as solar and wind necessitate the use of an efficient load frequency control(LFC)technique.Therefore,a hybrid version of two metaheuristic algorithms(arithmetic optimization and African vulture’s optimization algorithm)is developed.It is called the‘arithmetic optimized African vulture’s optimization algorithm(AOAVOA)’.This algorithm is used to tune a novel type-2 fuzzy-based proportional–derivative branched with dual degree-of-freedom proportional–integral–derivative controller for the LFC of a three-area hybrid deregulated power system.Thermal,electric vehicle(EV),and DRG sources(including a solar panel and a wind turbine system)are con-nected in area-1.Area-2 involves thermal and gas-generating units(GUs),while thermal and geothermal units are linked in area-3.Practical restrictions such as thermo-boiler dynamics,thermal-governor dead-band,and genera-tion rate constraints are also considered.The proposed LFC method is compared to other controllers and optimizers to demonstrate its superiority in rejecting step and random load disturbances.By functioning as energy storage ele-ments,EVs and DRG units can enhance dynamic responses during peak demand.As a result,the effect of the afore-mentioned units on dynamic reactions is also investigated.To validate its effectiveness,the closed-loop system is subjected to robust stability analysis and is compared to various existing control schemes from the literature.It is determined that the suggested AOAVOA improves fitness by 40.20%over the arithmetic optimizer(AO),while fre-quency regulation is improved by 4.55%over an AO-tuned type-2 fuzzy-based branched controller.
