Dual-stage Actuator System Based On A Model Car

The dual-stage actuator (DSA) control system has drawn a great deal of interest from researchers, and it has led to a wide range of applications in many fields. Our objective is to design a control law such that the two actuators cooperate to enable the total position output to track a step command input of amplitude rapidly. The DSA system consists of the first and the second actuator in series, which can achieve a better performance by delicately control the two actuators.There are a lot of control algorithms for DSA systems, the secondary actuator saturation control, robust control etc. The outline of this thesis is as follows:Chapter1briefly introduces the background knowledge the state of DSA system.Chapter2summarizes the background knowledge of linear control system, reset state and observer.Chapter3presents a linear control algorithm. First, we design PTOS to yield a small overshoot for the primary actuator system, and linear algorithm is designed for the secondary actuator to reduce the overshoot, then, detailed parameter design is carried out to enhance the system performance, finally, a simulink platform is developed in this chapter.Chapter4considers Dual-stage Actuator linear system as the object of research. In networked control system, there exists the phenomenon of quantitative data jumping when the data is quantized in the segment which caused by low accuracy of controller or all kinds of noise. We provide a reset state observer for linear systems to suppress effects of quantitative data jumping. Using the Lyapunov approach, we can prove the closed loop control system is asymptotically stable. Finally, using the state estimate-value measured by the state observe, the controller made dual-stage actuator work coordinately.In chapter5, Based on Dual-stage Actuator linear system with uncertainty Feature, it is considered that estimation problem for linear systems using quantized measurements. The communication channel we consider encounters inunreliable case. we introduce the stochastic variable satisfying Bernoulli random binary distribution to model the lossy measurements. We design a estimator to cope with the losses and mitigate quantization effects simultaneously such that the estimation error system is stochastically stable, Finally, a simulation example is given to illustrate that the proposed approach is effective and feasible.