Fuzzy Fault-tolerant Guaranteed Cost Control Of Nonlinear Systems

With the development of science and technology, the industrial equipment becomes more complicated. And the reliability of the equipment, especially for the large-scale complicated equipment, is attracted more and more attention. If any components fail and can't be disposed in time when the equipment is running, it will result in great economic loss. The artificial intelligent control based on knowledge takes bright future for the above problems. Fuzzy control is an important artificial intelligent control. In this paper, we concentrate on the design of fault-tolerant guaranteed cost controller of nonlinear systems with actuators fault is suggested. The main contents are as follows:1. Based on T-S fuzzy model, the concept of the so-called parallel distributed compensation (PDC) is employed to design fault-tolerant guaranteed cost controller of the continuous and discrete nonlinear systems. A sufficient condition for the existence of guaranteed controller is given. Under the condition, the controller not only provides the asymptotic stability of the closed loop system but also guarantees the performance at an adequate level. Simulation results show the effectiveness of the proposed method.2. Based on T-S model, a sufficient condition for the existence of fault-tolerant guaranteed cost controller of the continuous and discrete nonlinear systems with state delay. Under the condition, the controller not only provides the asymptotic stability of the closed-loop system but also guarantees the performance at an adequate level. Simulation results show the effectiveness of the proposed method.3. Based on T-S model, a sufficient condition for the existence of fault-tolerant guaranteed cost controller of the continuous and discrete nonlinear systems with control and state delays. Under the condition, the controller not only provides the asymptotic stability of the closed-loop system but also guarantees the performance at an adequate level. Numerical examples demonstrate the effectiveness of the proposed method.