The Controller Design Of Networked Control Systems Based On Iterative Optimization Algorithm

Networked control systems(NCSs)is the system that feedback control loop communicate through a real-time network.The controller design of NCSs has been an active research topic in the area of control and have already gained some achievements.In this paper,we mainly consider the designer of stabilizing controller of NCSs based on hyper-sampling mode,a sampling mode induced by scheduling of real-time systems under constrained(calculation and communication ones)resources and recently proposed in the literature.More precisely,we propose an approach named iterative optimization algorithm with the help of the analytic of asymptotic behavior to design the feedback gain matrix K by analyzing the asymptotic behavior of the critical characteristic roots with respect to the elements of the feedback gain matrix such that the stabilizing region under the hyper-sampling mode can be as large as possible.The main works are given as follows:(1)This thesis studies the designer of controller based on regular sampling theorem.We first treat the regular sampling theorem as a special case of the hyper-sampling mode and then deduce the theoretical formulae by the using of the necessary and sufficient stability criteria for discrete systems to determine the feedback gain matrix K.we can next determine the feedback gain matrix K to acquire the stabilizing region under the standard sampling mode with the help of LMI toolbox.It should be emphasized that this approach to obtain the stabilizing region is a kind of analytic method without any conservatism.(2)The hyper-sampling mode provides with a more flexible sampling mechanism.But it is difficult to design the stabilizing controller directly especially when sub-sampling periods increased as the stabilizing condition is a nonlinear matrix inequality due to the parameter coupling of sub-sampling periods and the elements of the feedback gain matrix K.While it is not easy to equivalently transform it into a linear one,we recommend the analytic of asymptotic behavior which is relatively a new technique and have solved lots of complex problem in the area of control,and then we propose an iterative optimization algorithm under the basic idea of analytic of asymptotic behavior to successfully design the NCSs controller under the hyper-sampling mode.Eventually,An illustrative example shows that the iterative optimization algorithm to design the controller of NCSs under hyper-sampling mode is feasible.(3)Finally,an experimental platform based on a data acquisition(DAQ)card is established to verify the method proposed above.The experimental platform consists of four primary component:a DC brush motor,a DAQ card,a DC tachogenerator and the corresponding driving circuits.Based on the model of this experimental platform,we design the controller following the previous theoretical steps.Finally,the simulation and experiment all validate the feasibility of the approach proposed above.Therefore,the verification of the theory is completed.In this paper,we mainly focus on proposing an iterative optimization algorithm under the analytic of curve's asymptotic behavior and successfully apply it to design the controller of NCSs based on hyper-sampling mode.While there are no guarantees that the method is the best,but it is feasible.