Research On Robust PID Control System

PID controller was widely used in the real industrial processes, especially in the processing control systems, because of its simplicity, reliability ,easy implement and good robustness. But the control object in industrial processing control was often time-delaying nonlinear and has a certain degree of uncertainty. In this way, the fixed parameters of regular PID controllers can hardly achieve satisfactory control effects. Robust PID controller was of great significance for enhancing the endurance of PID controller to uncertainty, which was robustness. Complete differential PID was mostly adopted in researching of the robust PID control system. As we all knew, the differential action of the complete differential PID controller had nearly no effect as which last only one period, so that the advance control of error can't be achieved. At the same time, the oversize amplitude of the period would make the computer data easily overflowed and even bring adverse effects to the implementation of the system. In order to overcome these disadvantages, it is necessary to study Robust Incomplete Differential PID controller. The main results are summarized as follows.Firstly, incomplete differential PID controller was introduced. On basis of it, Genetic algorithm, by which Robust Incomplete Differential PID controller was designed, optimized the parameters of the controller which made the system a perfect control effect.Using the Youla parameterization theory, Pade approximation and sensitivityminimization, the H_∞-based robust incomplete differential PID controller, containingonly one turning parameter which facilitated it's turning process, were designed and the parameter expression were presented. The system based on robust PID controller possessed high robustness, as considering the robust of the system while designing.Simulation on the industrial process with uncertainty was carried out by using the two methods above. The research proved that the robust PID controllers had been designed were of high robustness, which met the need of real industry and improved the performance of the control system.