The Research And Application Of One New Type Of RTD-A Controller

RTD-A controller(Robustness, Tracking ,Disturbance rejection -overall Aggressiveness)is one new type of controlling scheme, which has simple structure but excellent performance ,such as explicit significance of parameters, easy to be implemented and strong robustness, etc. This new kind of controller consists of three key parts: model identification, modeling error prediction update, and control action computation. And at present , the research about RTD-A controller is just limited into single variable systems. So it takes a large part in this paper to discuss the expansion application of RTD-A controller in multi-variable system . Furthermore, the second major task of the problem about how to tune and optimize the parameters of controller is also presented and resolved in this paper .In the organization of this paper, it is divided into three large parts. The first part is a brief introduction of single variable RTD-A controller ,which includes the basic principle of RTD-A, significance of its four tuning parameters and their effects on the controller, and then the performance of RTD-A controller is verified through the comparison with internal model PID controller(IMC-PID).The second major part emphasizes the application of RTD-A in multi-variable system. On the basis of single variable RTD-A controller , a new RTD-A controller for multi-variable system is presented and condition to the solution of control action is also deducted from the point of mathematic in this paper. Simulation results proves it has good performances in set-point tracking, disturbance rejection and robustness with the comparison of single variable RTD-A and decoupling IMC-PID under the same condition.The last part is about parameters optimization of RTD-A, for which the algorithm of Particle Swarm Optimization(PSO) is introduced. The basic principle of PSO is surrounded by searching the best solution through the efforts of every single particle. The successful application of PSO resolves the problem of tuning parameters and simulation proves it has good optimization effect and feasibility.