An integral terminal sliding mode controller is proposed in order to control chaos in a rod-type plasma torch system.In this method, a new sliding surface is defined based on a combination of the conventional sliding ...An integral terminal sliding mode controller is proposed in order to control chaos in a rod-type plasma torch system.In this method, a new sliding surface is defined based on a combination of the conventional sliding surface in terminal sliding mode control and a nonlinear function of the integral of the system states. It is assumed that the dynamics of a chaotic system are unknown and also the system is exposed to disturbance and unstructured uncertainty. To achieve a chattering-free and high-speed response for such an unknown system, an adaptive neuro-fuzzy inference system is utilized in the next step to approximate the unknown part of the nonlinear dynamics. Then, the proposed integral terminal sliding mode controller stabilizes the approximated system based on Lyapunov＇s stability theory. In addition, a Bee algorithm is used to select the coefficients of integral terminal sliding mode controller to improve the performance of the proposed method. Simulation results demonstrate the improvement in the response speed, chattering rejection, transient response,and robustness against uncertainties.展开更多
This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sl...This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.展开更多
文摘An integral terminal sliding mode controller is proposed in order to control chaos in a rod-type plasma torch system.In this method, a new sliding surface is defined based on a combination of the conventional sliding surface in terminal sliding mode control and a nonlinear function of the integral of the system states. It is assumed that the dynamics of a chaotic system are unknown and also the system is exposed to disturbance and unstructured uncertainty. To achieve a chattering-free and high-speed response for such an unknown system, an adaptive neuro-fuzzy inference system is utilized in the next step to approximate the unknown part of the nonlinear dynamics. Then, the proposed integral terminal sliding mode controller stabilizes the approximated system based on Lyapunov＇s stability theory. In addition, a Bee algorithm is used to select the coefficients of integral terminal sliding mode controller to improve the performance of the proposed method. Simulation results demonstrate the improvement in the response speed, chattering rejection, transient response,and robustness against uncertainties.
文摘This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.
