Fuzzy sliding mode control design for a class of disturbed systems

Abstract

This paper discusses the problem of the fuzzy sliding mode control for a class of disturbed systems. First, a fuzzy auxiliary controller is constructed based on a feedback signal not only to estimate the unknown control term, but also participates in the sliding mode control due to the fuzzy rule employed. Then, we extend our theory into the cases, where some kind of system information can not be obtained, for better use of our theoretical results in real engineering. Finally, some typical numerical examples are included to demonstrate the effectiveness and advantage of the designed sliding mode controller. © 2013 The Franklin Institute

Super-Twisting-Algorithm-Based Terminal Sliding Mode Control for a Bioreactor System

“…Consider a Lyapunov function candidate = (1/2) 2 for and substitute given in (12) into (13). Then the time derivative of along the trajectory of system (6)…”

“…To demonstrate the effectiveness of the proposed scheme in the study, in this section, three control laws: conventional sliding mode (labeled SMC), terminal sliding mode (labeled TSMC), and super-twisting-algorithm-based terminal sliding mode (labeled STA+TSMC) control laws, as given by (12), (16), and (20)- (21), respectively, are employed for a bioreactor system (1) to fulfill the tracking task. The relevant parameters ( = 0.02 and = 0.48) of a bioreactor system can be referred to in [60].…”

Robust Backstepping Sliding Mode Controller Investigation for a Port Plate Position Servo System Based on an Extended States Observer

“…For control problems with parameter uncertainty and external disturbances, many scholars have made use of modern control theory to conduct research . For example, adaptive control, sliding mode control (SMC), backstepping control, and so forth. These are effective methods to solve the control problem of nonlinear systems, however a single algorithm has its own shortcomings and it is difficult to solve the influence of the model uncertainty and external disturbance for hydraulic systems.…”

Fractional Order Synchronous Reluctance Motor: Analysis, Chaos Control and FPGA Implementation

“…Synchronization of chaotic systems deals with asymptotically synchronizing the state trajectories of a pair of chaotic systems called master and slave systems. Many control techniques have been developed for the chaos synchronization of integer-order chaotic systems such as active control [14][15][16], adaptive control [17][18][19], sliding mode control [20][21][22][23][24][25][26][27][28], backstepping control [29,30], fuzzy control [31,32], etc. On the other hand, there are some approaches to control nonlinear dynamical systems using the Markov chain [33,34].…”