Satisfactory Control And Estimation Of Linear Periodic Multirate Systems

This dissertation deals mainly with the problems of Satisfactory Control and Estimation for linear periodic multirate systems, which are problems that occur in many control applications such as objective track and digital communication. And the minimum optional control method has to give way to the satisfactory control design approach because this approach is not crazing for one synthesis requirement optimization but eager to all requirements to meet at the same time without optimization. On the base of Lyapunov stabilization theory, covariance control theory and H_ robust control theory, Satisfying Control theory for linear periodic systems under constrains of circular pole index, steady variance index and (or) H- index is set up by state feedback and state estimator etc. An effective controller or filter design method for the periodic systems with constrains of consistent indices is given via LMI technique.The dissertation consists of an introduction and five parts. The first part is periodic feedback and periodic serial adjusting control in linear systems. It has been showed precise zero and pole placement at the same time via periodic state feedback and a parameterized family of linear tune invariant plants with one uncertainty zero and desired gain margin requirement are stabilized.The second part is studied on ranges of H- index that is consistent with state or filter error variance index for interval systems via state feedback and state estimation.The third part is studied on variance index and H2/ H. index that consistent with assignable pole index for linear periodic multi-rate systems via state feedback.The forth part is studied on variance index and H. index that consistent with assignable pole index for linear periodic state-estimation systems.The last one is an engineering example for periodic multi-rate track systems. For the problem of objective trace identify a periodic multirate Kalman filter approach is developed on the basis of Kalman filter and relativity of state variance and this approach is simulated in tracking one helicopter trace and some useful results have been achieved through comparing it with usual Kalman filter.