Iterative Learning Control Algorithm And Its Application In Wind Power Control System

Iterative Learning Control is an intelligent control algorithm in a strict mathematical description of the branch, which in non-linear, unknown model of the control system has a unique advantage in industrial robots, CNC machine tools, such as duplication of operational characteristics of the field very good application prospects. As a result of this algorithm is simple and effective, in recent years by researchers from all walks of life concerns, the study would normally include the composition of studying law, convergence, robustness, and learning speed of the initial value problem.Iterative Learning Control for a certain exercise to repeat the nature of the charged object, you can achieve a limited range on the complete track. Charged through the system control to the system output with a given trajectory deviation signal to rectify the non-ideal control signal, producing a new control signal, allowing the system to improve tracking performance.Its basic thought is: In view of the nature of sports has to repeat the object, using the last iteration when the input information and output of error correction to fix iteration control signal, in the given time interval, the implementation the unknown object to arbitrary precision tracking the expectations of a given trajectory. Paper's main innovation lies in the fact that for wind power control system for wind energy conversion system in part of an improved Iterative Learning Control algorithm, using the algorithm of Iterative Learning Control, the system's actual output can better convergence ideal output of the system. Further theories proved that the new algorithm convergence, and give an analysis of simulation results.The major research content of this paper is as follows:1. It outlines the principle, the main research contents, and other control algorithm comparison of the iterative learning control algorithm. Moreover, it gives necessary basic math knowledge for the iterative learning control algorithms.2. For open-loop P-type learning law, closed-loop D-type learning law and open and closed-loop PD-type learning law, it proposes algorithm design, proves convergence and gives conditions for convergence. For each of the basic iterative learning algorithm, some simulation studies are done with about two examples respectively. And analysis of simulation results verifies that the algorithm is feasible and effective.3. With application-specific engineering background and the former knowledge about the basic iterative learning control algorithm, a new iterative learning control algorithm is proposed. Then, the paper proves its convergence, discusses the iterative learning control in the wind power generation control system engineering applications and so on.4. On the basis of current research about Iterative Learning Control, the paper discusses the study methods of such control problems, and summarizes the research direction and research prospects.