In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a mo...In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been substituted for by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.展开更多
Fuzzy Logic System (FLS) can be utilized to approxi-mate complex uncertain nonlinear dynamic systems. Inthis paper, an adaptive fuzzy Sliding Mode Control(SMC) scheme is proposed where FLS is used as an ap-proximation...Fuzzy Logic System (FLS) can be utilized to approxi-mate complex uncertain nonlinear dynamic systems. Inthis paper, an adaptive fuzzy Sliding Mode Control(SMC) scheme is proposed where FLS is used as an ap-proximation of the unknown systems. In order to reducethe approximation errors between the true nonlinearmodel and FLS, an adaptive law is presented. The sta-bility of the controlled system is proved by using Lya-punov stability theory. The proposed control scheme isapplied to an inverted pendulum system to show its effec-tiveness.展开更多
Direct adaptive fuzzy sliding mode control design for discrete non-affine nonlinear systems is presented for trajectory tracking problems with disturbance. To obtain adaptiveness and eliminate chattering of sliding mo...Direct adaptive fuzzy sliding mode control design for discrete non-affine nonlinear systems is presented for trajectory tracking problems with disturbance. To obtain adaptiveness and eliminate chattering of sliding mode control, a dynamic fuzzy logical system is used to implement an equivalent control, in which the parameters are self-tuned online. Stability of the sliding mode control is validated using the Lyapunov analysis theory. The overall system is adaptive, asymptotically stable, and chattering-free. A numerical simulation and an application to a robotic arm with two degrees of freedom further verify the good performance of the control design.展开更多
By using the exponential reaching law technology,a sliding mode controller was designed for Lorenz chaotic system subject to an unknown external disturbance.On this basis,considering the unknown disturbance,an adaptiv...By using the exponential reaching law technology,a sliding mode controller was designed for Lorenz chaotic system subject to an unknown external disturbance.On this basis,considering the unknown disturbance,an adaptive law was introduced to adaptively estimate the parameters of the disturbance bounds.Furthermore,to eliminate the chattering resulting from the discontinuous switch controller and to guarantee system transient performance,a new adaptive fuzzy sliding mode controller was designed.The results of the simulation show the effectiveness of the proposed control scheme.展开更多
This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extr...This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extra hardware nor huge memory space are not required but it only requires active phase measurements. Furthermore, PI （proportional integral） and adaptive FLPI （fuzzy logic PI） controllers are suggested to operate individually along with the SMO （sliding mode observer） to cover a full speed range of sensorless controller. Both controller schemes operate in PWM （pulse width modulation） control mode. The proposed observer is implemented and tested using a digital signal processor. All results obtained with both simulation and experimental investigations corroborate the superior performance of the adaptive fuzzy logic controller （FLPI） when compared with those of PI controller.展开更多
Energy production from renewable sources offers an efficient alternative non-polluting and sustainable solution. Among renewable energies, solar energy represents the most important source, the most efficient and the ...Energy production from renewable sources offers an efficient alternative non-polluting and sustainable solution. Among renewable energies, solar energy represents the most important source, the most efficient and the least expensive compared to other renewable sources. Electric power generation systems from the sun’s energy typically characterized by their low efficiency. However, it is known that photovoltaic pumping systems are the most economical solution especially in rural areas. This work deals with the modeling and the vector control of a solar photovoltaic (PV) pumping system. The main objective of this study is to improve optimization techniques that maximize the overall efficiency of the pumping system. In order to optimize their energy efficiency whatever, the weather conditions, we inserted between the inverter and the photovoltaic generator (GPV) a maximum power point adapter known as Maximum Power Point Tracking (MPPT). Among the various MPPT techniques presented in the literature, we adopted the adaptive neuro-fuzzy controller (ANFIS). In addition, the performance of the sliding vector control associated with the neural network was developed and evaluated. Finally, simulation work under Matlab / Simulink was achieved to examine the performance of a photovoltaic conversion chain intended for pumping and to verify the effectiveness of the speed control under various instructions applied to the system. According to the study, we have done on the improvement of sliding mode control with neural network. Note that the sliding-neuron control provides better results compared to other techniques in terms of improved chattering phenomenon and less deviation from its reference.展开更多
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
文摘In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been substituted for by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.
基金This work was supported by China Postdoctoral Science Foundation and Hebei Provincial Natural Science Foundation(698004).
文摘Fuzzy Logic System (FLS) can be utilized to approxi-mate complex uncertain nonlinear dynamic systems. Inthis paper, an adaptive fuzzy Sliding Mode Control(SMC) scheme is proposed where FLS is used as an ap-proximation of the unknown systems. In order to reducethe approximation errors between the true nonlinearmodel and FLS, an adaptive law is presented. The sta-bility of the controlled system is proved by using Lya-punov stability theory. The proposed control scheme isapplied to an inverted pendulum system to show its effec-tiveness.
基金Project supported by the National Natural Science Foundation of China （No. 61304024）, the Science and Technology Project of Hebei Province, China （No. 15272118）, and the Fundamental Research Funds for the Central Universities, China （No. 3142015101）
文摘Direct adaptive fuzzy sliding mode control design for discrete non-affine nonlinear systems is presented for trajectory tracking problems with disturbance. To obtain adaptiveness and eliminate chattering of sliding mode control, a dynamic fuzzy logical system is used to implement an equivalent control, in which the parameters are self-tuned online. Stability of the sliding mode control is validated using the Lyapunov analysis theory. The overall system is adaptive, asymptotically stable, and chattering-free. A numerical simulation and an application to a robotic arm with two degrees of freedom further verify the good performance of the control design.
基金supported by the National Natural Science Foundation of China (Grant No.69874008).
文摘By using the exponential reaching law technology,a sliding mode controller was designed for Lorenz chaotic system subject to an unknown external disturbance.On this basis,considering the unknown disturbance,an adaptive law was introduced to adaptively estimate the parameters of the disturbance bounds.Furthermore,to eliminate the chattering resulting from the discontinuous switch controller and to guarantee system transient performance,a new adaptive fuzzy sliding mode controller was designed.The results of the simulation show the effectiveness of the proposed control scheme.
文摘This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extra hardware nor huge memory space are not required but it only requires active phase measurements. Furthermore, PI （proportional integral） and adaptive FLPI （fuzzy logic PI） controllers are suggested to operate individually along with the SMO （sliding mode observer） to cover a full speed range of sensorless controller. Both controller schemes operate in PWM （pulse width modulation） control mode. The proposed observer is implemented and tested using a digital signal processor. All results obtained with both simulation and experimental investigations corroborate the superior performance of the adaptive fuzzy logic controller （FLPI） when compared with those of PI controller.
文摘Energy production from renewable sources offers an efficient alternative non-polluting and sustainable solution. Among renewable energies, solar energy represents the most important source, the most efficient and the least expensive compared to other renewable sources. Electric power generation systems from the sun’s energy typically characterized by their low efficiency. However, it is known that photovoltaic pumping systems are the most economical solution especially in rural areas. This work deals with the modeling and the vector control of a solar photovoltaic (PV) pumping system. The main objective of this study is to improve optimization techniques that maximize the overall efficiency of the pumping system. In order to optimize their energy efficiency whatever, the weather conditions, we inserted between the inverter and the photovoltaic generator (GPV) a maximum power point adapter known as Maximum Power Point Tracking (MPPT). Among the various MPPT techniques presented in the literature, we adopted the adaptive neuro-fuzzy controller (ANFIS). In addition, the performance of the sliding vector control associated with the neural network was developed and evaluated. Finally, simulation work under Matlab / Simulink was achieved to examine the performance of a photovoltaic conversion chain intended for pumping and to verify the effectiveness of the speed control under various instructions applied to the system. According to the study, we have done on the improvement of sliding mode control with neural network. Note that the sliding-neuron control provides better results compared to other techniques in terms of improved chattering phenomenon and less deviation from its reference.
