Control System Correction Design Based On Time-Frequency Domain Index And The Visualizationplatform Research

In practical engineering control, because of many reasons, the system could not frequently meet the performance requirements. Then, some links had to be designed, which should to be included into the system, so that the system could meet the performance requirements. This process was the system calibration design.System calibration design was a process of trial and error. It required constantly adjust the corrector’s parameters. In the process of the testing and adjusting, even if you had a wealth of experience, you still needed to carry on a large amount of complicated calculation. Finally the corrector’s correction effect needed to be tested by checking the system. If failed, the corrector’s parameters should be re testing and adjusting.According to the problem that the parameters of control system’s corrector fitting the system’s time-frequency domain performance requirements, A correction method which was based on Adaptive Particle Swarm Optimization algorithm was proposed. In the process of designing the corrector, firstly, a multilevel corrector which would be connected to the uncorrected system through series was introduced. Then, the optimization model that had been included the object function and constrain condition was established. The object function was the time domain integral of the error indicator. Constrain condition consisted of system’s gain margin, phase margin and other frequency index. Afterward, in the MATLAB environment, Adaptive Particle Swarm Optimization algorithm had to be connected with Simulink simulation technology, and the parameters of the control system’s corrector had to be optimized. After that, correcting control system could have to be implemented. According to the testing, this method is simple and excellent. The performance of the corrector which was designed by the method was much more excellent.Finally, in order to further simplify the process of designing control system’s corrector which was based on Adaptive Particle Swarm Optimization algorithm, correcting system’s visual interface design had been completed. By using the MATLAB software, the process of correcting system had become more clearly and intuitive. At the same time, the efficiency of control system correction design was greatly improved.