Real-time multiple-parameter tuning of PPF controllers for smart structures by genetic algorithms

摘要

This paper is concerned with the real-time automatic tuning of the multi-input multi-ouput positive positioin feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters whithout failling into local minimums thus rendering globally optimal solutions. The previous realemploy the MIMO PPF controller since it can enhance the damping value of a target mode witout affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control; thus it involves many parameters. The bounds of the control parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.