Iterative Learning Control For Time Delay Systems

It is a common phenomenon that time delays exist in many practice engineering. In this thesis, we design a few iterative learning controllers for some kinds of time delay systems and present the corresponding theory analysis and simulation study. This paper is organized as follows:In the first chapter, we introduce the research significance of iterative learning control for time delay systems, together with the current development situation of this field all over the world.In the second chapter, the convergence of different learning algorithms are respectively discussed for iterative learning control systems with time delay. In section 2.1, we study the convergence of open-closed-loop PID-type learning algorithm for iterative learning control systems with time delay in state, and obtain some useful criteria viaλ-norm, Bellman-Gronwall theorem and some inequality. In section 2.2, similar to the idea of section 2.1, we investigate the convergence of D-type learning algorithm for iterative learning control systems with time delay in control, and get some useful criteria. Finally, numerical simulations are given to show the algorithm's efficiency.In the third chapter, based on the method of information synthesis, by using the definition of (λ,ξ)-norm and the property of inequality, the convergence of 2-order D-type learning algorithm is studied for iterative learning control systems with time delay.In the forth chapter, adaptive neural network iterative learning control scheme is presented for a class of single-input-single-output (SISO) nonlinear time-delay systems. Unknown nonlinear function vectors and unknown nonlinear time-delay functions are approximated by two neural networks, respectively, such that the requirements on the unknown nonlinear functions and the unknown nonlinear time-delay functions are relaxed. The neural network learning laws and control laws are designed by using appropriate Lyapunov-Krasovskii function and backstepping technology. Furthermore, based on Lyapunov theory, all signals in the closed loop system are guaranteed to be semiglobally uniformly ultimately bounded and the output of the system is proved to converge to a small neighborhood of the desired trajectory. At the last chapter, we give a premature explanation and vista by synthesizing the above analysis.