Robust global fast terminal sliding mode controller for rigid robotic manipulators

A global fast terminal sliding mode controller (GFTSMC) is proposed for a-link rigid robot manipulators by employing the fast terminal sliding mode control concept" in both the reaching phase and the sliding phase. Under the control, the system states will reach the terminal sliding manifold in a desired finite time and then converge to the origin along the sliding manifold in a specified finite time, resulting in reduced steady tracking error in comparison with the linear sliding mode controller. The proposed sliding mode controller is continuous and therefore is chattering-free. An example is shown to demonstratethe effectiveness of the controller

A fuzzy neural network approximator with fast terminal sliding mode and its applications

This paper presents a new training method for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions. Fast terminal sliding mode combining the finite time convergent property of terminal attractor and exponential convergent property of linear system has faster convergence to the origin in finite time. The proposed training algorithm uses the principle ofthe fast terminal sliding mode into the conventional gradient descent learning algorithm. The Lyapunov stability analysis in this paper guarantees that the approximation is stable and converges to the optimal approximation function with improved speed instead of finite time convergence to unknown function. The proposed FNN approximator is then applied in the control of an unstable nonlinear system and the Duffing system. The simulation results demonstrate the effectiveness of the proposed method

Modeling-error based adaptive fuzzy sliding mode control for trajectory-tracking of nonlinear systems

A novel adaptive fuzzy sliding mode control design is developed for trajectory tracking of a class of nonlinear systems in this paper. This control design uses the modelling error to adaptively estimate the deterministic uncertainties as well as the control gain based on the fuzzy systems approach. By this design, the bounds of the uncertainties are not required to be known in advance, and the robust stability of closed loop systems is analysed in the Lyapunov sense. Simulation results are given to demonstrate the improved performance

Continuous finite-time control for robotic manipulators with terminal sliding modes

A new continuous finite-time control scheme (or trajectory-tracking problem ofrobotic manipulators is proposed using terminal sliding mode (TSM). The finite-time convergence property of TSM is applied in both the reaching phase and the sliding phase ofthe sliding mode control system. As a result; the closed-loop system is globally finite-time stable and the trajectory-tracking objective is achieved in finite time. The resulting control law is continuous therefore chattering-free. Furthermore. it overcomes the common singularity problem in TSM Theoretical analysis shows that the proposed control strategy has stronger robustness and disturbance-attenuation ability compared with the conventional boundary-layer method. Simulation results are given to illustrate the effectiveness ofthe proposed algorithm

A fuzzy neural network approximator with fast terminal sliding mode and its applications

This paper presents a new training method for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions. Fast terminal sliding mode combining the 3nite time convergent property of terminal attractor and exponential convergent property oflinear system has faster convergence to the origin in 3nite time. The proposed training algorithm uses the principle ofthe fast terminal sliding mode into the conventional gradient descent learning algorithm. The Lyapunov stability analysis in this paper guarantees that the approximation is stable and converges to the optimal approximation function with improved speed instead of3nite time convergence to unknown function. The proposed FNN approximator is then applied in the control ofan unstable nonlinear system and the Du5ng system. The simulation results demonstrate the effectiveness of the proposed method

Indirect adaptive fuzzy control of nonlinear systems with terminal sliding modes

A global fast terminal sliding mode controller with fast terminal adaptive fuzzy approximator is proposed for general single input single output nonlinear systems. The finite time convergence property of the fast terminal sliding mode is used in the design of the controller. It is applied not only in the reaching phase and the sliding phase of the sliding mode control system, but also in the adaptive fuzzy approximator for the unknown nonlinear system. Stability of the control system and convergence of the approximation are proved