The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimiz...The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimization relationship. The use of six fuzzy logic controllers(6FLCs) is proposed for dynamic control genetic operating parameters of a symbolic-coded GA. This paper uses AGA based on 6FLCs to deal with the travelling salesman problem (TSP). Experimental results show that AGA based on 6FLCs is more efficient than a standard GA in solving combinatorial optimization problems similar to TSP.展开更多
A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip ...A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.展开更多
To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output err...To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.展开更多
In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control...In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control from Lyapunov stability theory. The proposed approach offers a systematic design procedure for stabilizing a large class of chaotic systems in the literature about chaos research. The simulation results on Rossler＇s system verify the effectiveness of the proposed methods.展开更多
Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic character...Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.展开更多
On the simple continuously variable transmission （CVT） driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-t...On the simple continuously variable transmission （CVT） driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.展开更多
Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time...Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time-varying parameters. Traditional control method has some limitation. In order to help the hydraulic servo system of the quadruped robot to adapt to harsh environments, and to obtain high control quality and control precision, an incremental fuzzy adaptive PID controller based on position feedback is designed to solve the related technical problems. Matlab/Simulink sim- ulation and experimental results show that the incremental fuzzy adaptive PID controller improves the dynamic performance of the system, enhances the respond speed and precision of the hydraulic ser- vo system, and has some theory significance and practical value.展开更多
This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the...This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.展开更多
A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the tr...A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the traditional fuzzy membership. Adaptive law of the adjustable parameters 6 is also determined. The directly adaptive fuzzy ACC controller is designed based on Matlab fuzzy toolbox. Matlab-Simulink is adopted to test the function of the adaptive fuzzy ACC controller. The control system is established using a 7 DOF vehicle dynamics model. Simulation results indicate that the principle of the method is correct and it performs well both in cruise and distance keeping.展开更多
The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller an...The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.展开更多
Based on Matlab/Simulink and Fuzzy Logic toolboxes, the altitude control system is designed and simulated. The validity of conventional PID control method and adaptive fuzzy PID control method is compared. It can be d...Based on Matlab/Simulink and Fuzzy Logic toolboxes, the altitude control system is designed and simulated. The validity of conventional PID control method and adaptive fuzzy PID control method is compared. It can be drawn out that the adaptive fuzzy PID control method is superior to the conventional PID in rising time and overshoot etc. The effectiveness of a fuzzy PID controller shows potential application in the future, especially in the presence of model uncertainty or changing dynamics and time-varying parameters.展开更多
The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite. The ba...The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite. The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.展开更多
Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in Ind...Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.展开更多
In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as sync...In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as synchronization errors, are employed to approximate the unknown nonlinear functions. Based on the fractional Lyapunov stability criterion, an adaptive fuzzy synchronization controller is designed, and the stability of the closed-loop system, the convergence of the synchronization error, as well as the boundedness of all signals involved can be guaranteed. To update the fuzzy parameters, fractional-order adaptations laws are proposed. Just like the stability analysis in integer-order systems, a quadratic Lyapunov function is used in this paper. Finally, simulation examples are given to show the effectiveness of the proposed method.展开更多
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee...Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.展开更多
This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability(ISS) the...This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability(ISS) theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques,a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently,a ship's linear track-keeping control can be implemented. Simulation results using Dalian Maritime University's ocean-going training ship 'YULONG' are presented to validate the effectiveness of the proposed algorithm.展开更多
After heat is metered in each house unit,the heating system is regulated by variable flow.The temperature of the return w ater is controlled to regulate the flow to realize the temperature regulation.According to the ...After heat is metered in each house unit,the heating system is regulated by variable flow.The temperature of the return w ater is controlled to regulate the flow to realize the temperature regulation.According to the characteristics of the temperature control w ith big inertia,pure time-delay and degeneration,a fuzzy adaptive PID controller is designed w ith the advantages of the fuzzy control and PID algorithm,and the simulation model is established according to the characteristics of heating metering system.Simulation results show that the fuzzy adaptive PID controller proposed has small overshoot,short oscillation cycle,high precision and strong anti-jamming capability in comparison w ith conventional PID controller,w hich could meet the requirement of the dynamic and steady-state performance of the heating process.展开更多
Novel neuro-fuzzy techniques are used to dynamically control parameter settings ofgenetic algorithms (GAs).The benchmark routine is an adaptive genetic algorithm (AGA) that uses afuzzy knowledge-based system to contro...Novel neuro-fuzzy techniques are used to dynamically control parameter settings ofgenetic algorithms (GAs).The benchmark routine is an adaptive genetic algorithm (AGA) that uses afuzzy knowledge-based system to control GA parameters.The self-learning ability of the cerebellar modelariculation controller (CMAC) neural network makes it possible for on-line learning the knowledge onGAs throughout the run.Automatically designing and tuning the fuzzy knowledge-base system,neuro-fuzzy techniques based on CMAC can find the optimized fuzzy system for AGA by the renhanced learningmethod.The Results from initial experiments show a Dynamic Parametric AGA system designed by theproposed automatic method and indicate the general applicability of the neuro-fuzzy AGA to a widerange of combinatorial optimization.展开更多
This study presents an adaptive fuzzy neural network (FNN) control system for the ship steering autopilot. For the Norrbin ship steering mathematical model with the nonlinear and uncertain dynamic characteristics, an ...This study presents an adaptive fuzzy neural network (FNN) control system for the ship steering autopilot. For the Norrbin ship steering mathematical model with the nonlinear and uncertain dynamic characteristics, an adaptive FNN control system is designed to achieve high-precision track control via the backstepping approach. In the adaptive FNN control system, a FNN backstepping controller is a principal controller which includes a FNN estimator used to estimate the uncertainties, and a robust controller is designed to compensate the shortcoming of the FNN backstepping controller. All adaptive learning algorithms in the adaptive FNN control system are derived from the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. The effectiveness of the proposed adaptive FNN control system is verified by simulation results.展开更多
The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is des...The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is designed, in which the sus pension travel output of the adaptive LQG control system is taken as the tracking objective. The simulation results prove that the suspension travel and vertical acceleration can be tracked simultaneously with the simple fuzzy controller, and the tracking effect of fuzzy control is better than that of the PID controller.展开更多
文摘The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimization relationship. The use of six fuzzy logic controllers(6FLCs) is proposed for dynamic control genetic operating parameters of a symbolic-coded GA. This paper uses AGA based on 6FLCs to deal with the travelling salesman problem (TSP). Experimental results show that AGA based on 6FLCs is more efficient than a standard GA in solving combinatorial optimization problems similar to TSP.
文摘A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.
文摘To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.
基金Project supported by the Natural Science Foundation of Yangzhou University of China （Grant No KK0513109）.
文摘In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control from Lyapunov stability theory. The proposed approach offers a systematic design procedure for stabilizing a large class of chaotic systems in the literature about chaos research. The simulation results on Rossler＇s system verify the effectiveness of the proposed methods.
基金supported by Naval Weapons and Equipment Pre-Research Project(Grant No.3020801010105).
文摘Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.
文摘On the simple continuously variable transmission （CVT） driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.
基金Supported by the Ministerial Level Advanced Research Foundation(65822576)
文摘Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time-varying parameters. Traditional control method has some limitation. In order to help the hydraulic servo system of the quadruped robot to adapt to harsh environments, and to obtain high control quality and control precision, an incremental fuzzy adaptive PID controller based on position feedback is designed to solve the related technical problems. Matlab/Simulink sim- ulation and experimental results show that the incremental fuzzy adaptive PID controller improves the dynamic performance of the system, enhances the respond speed and precision of the hydraulic ser- vo system, and has some theory significance and practical value.
基金Project supported by the Young Talents Natural Science Foundation for Universities of Anhui Province,China(Grant No.2012SQRL179)
文摘This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.
基金Sponsored by the National Natural Science Foundation of China (501222155)
文摘A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the traditional fuzzy membership. Adaptive law of the adjustable parameters 6 is also determined. The directly adaptive fuzzy ACC controller is designed based on Matlab fuzzy toolbox. Matlab-Simulink is adopted to test the function of the adaptive fuzzy ACC controller. The control system is established using a 7 DOF vehicle dynamics model. Simulation results indicate that the principle of the method is correct and it performs well both in cruise and distance keeping.
文摘The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.
基金Sponsored by the Ministerial Level Foundation(K130506)
文摘Based on Matlab/Simulink and Fuzzy Logic toolboxes, the altitude control system is designed and simulated. The validity of conventional PID control method and adaptive fuzzy PID control method is compared. It can be drawn out that the adaptive fuzzy PID control method is superior to the conventional PID in rising time and overshoot etc. The effectiveness of a fuzzy PID controller shows potential application in the future, especially in the presence of model uncertainty or changing dynamics and time-varying parameters.
文摘The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite. The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.
基金partially funded by Department of Science and Technology (DST), Govt. of Indiaproject SR/ FTP/ETA-61/2010
文摘Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11401243 and 61403157)the Foundation for Distinguished Young Talents in Higher Education of Anhui Province,China(Grant No.GXYQZD2016257)+3 种基金the Fundamental Research Funds for the Central Universities of China(Grant No.GK201504002)the Natural Science Foundation for the Higher Education Institutions of Anhui Province of China(Grant Nos.KJ2015A256 and KJ2016A665)the Natural Science Foundation of Anhui Province,China(Grant No.1508085QA16)the Innovation Funds of Graduate Programs of Shaanxi Normal University,China(Grant No.2015CXB008)
文摘In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as synchronization errors, are employed to approximate the unknown nonlinear functions. Based on the fractional Lyapunov stability criterion, an adaptive fuzzy synchronization controller is designed, and the stability of the closed-loop system, the convergence of the synchronization error, as well as the boundedness of all signals involved can be guaranteed. To update the fuzzy parameters, fractional-order adaptations laws are proposed. Just like the stability analysis in integer-order systems, a quadratic Lyapunov function is used in this paper. Finally, simulation examples are given to show the effectiveness of the proposed method.
基金Supported by Basic Research Foundation of National Defence (No. B0203-031)
文摘Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.
基金Supported by the National Natural Science Foundation of China under Grant No. 10572094.
文摘This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability(ISS) theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques,a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently,a ship's linear track-keeping control can be implemented. Simulation results using Dalian Maritime University's ocean-going training ship 'YULONG' are presented to validate the effectiveness of the proposed algorithm.
基金Project Supported by Education Department of Liaoning Province(LT2012005)
文摘After heat is metered in each house unit,the heating system is regulated by variable flow.The temperature of the return w ater is controlled to regulate the flow to realize the temperature regulation.According to the characteristics of the temperature control w ith big inertia,pure time-delay and degeneration,a fuzzy adaptive PID controller is designed w ith the advantages of the fuzzy control and PID algorithm,and the simulation model is established according to the characteristics of heating metering system.Simulation results show that the fuzzy adaptive PID controller proposed has small overshoot,short oscillation cycle,high precision and strong anti-jamming capability in comparison w ith conventional PID controller,w hich could meet the requirement of the dynamic and steady-state performance of the heating process.
文摘Novel neuro-fuzzy techniques are used to dynamically control parameter settings ofgenetic algorithms (GAs).The benchmark routine is an adaptive genetic algorithm (AGA) that uses afuzzy knowledge-based system to control GA parameters.The self-learning ability of the cerebellar modelariculation controller (CMAC) neural network makes it possible for on-line learning the knowledge onGAs throughout the run.Automatically designing and tuning the fuzzy knowledge-base system,neuro-fuzzy techniques based on CMAC can find the optimized fuzzy system for AGA by the renhanced learningmethod.The Results from initial experiments show a Dynamic Parametric AGA system designed by theproposed automatic method and indicate the general applicability of the neuro-fuzzy AGA to a widerange of combinatorial optimization.
基金Supported by Doctoral Bases Foundation of the Educational Committee of P. R. China under Grant No. 20030151005 and the Ministry of Communication of P. R. China under Grant No. 200332922505.
文摘This study presents an adaptive fuzzy neural network (FNN) control system for the ship steering autopilot. For the Norrbin ship steering mathematical model with the nonlinear and uncertain dynamic characteristics, an adaptive FNN control system is designed to achieve high-precision track control via the backstepping approach. In the adaptive FNN control system, a FNN backstepping controller is a principal controller which includes a FNN estimator used to estimate the uncertainties, and a robust controller is designed to compensate the shortcoming of the FNN backstepping controller. All adaptive learning algorithms in the adaptive FNN control system are derived from the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. The effectiveness of the proposed adaptive FNN control system is verified by simulation results.
基金Sponsored by Ministerial Level Equipment Pre-research Foundation(623010202 .4)
文摘The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is designed, in which the sus pension travel output of the adaptive LQG control system is taken as the tracking objective. The simulation results prove that the suspension travel and vertical acceleration can be tracked simultaneously with the simple fuzzy controller, and the tracking effect of fuzzy control is better than that of the PID controller.
