Rearch Of Hysteresis Compenation Model And Switch Control In Macro-micro Positioning Platform

With the upgrade of manufacturing, the innovation of IC integration and aerospace technology, as well as the breakthrough of genetic technology unceasingly, more and more high challenges and requirements are put forward for the high precision positioning technology. By macro-micro(dual-actuator) drive mode that micro positioning of the large stroke driven realized by linear motor driven and nanometer positioning of error compensation achieved by piezoelectric ceramics actuator, is a good form to meet the accuracy requirement of the stoke and engineering practice. As a brake component with nanometer resolution, piezoelectric ceramics actuator has the overwhelming advantages of fast respons e speed, low power consumption and small volume which is been widely used in the realm of precision position. However, it exhibits the inherent hysteresis nonlinearity which not only affects the final positioning accuracy, is also likely to destabilize the positioning system, and even causes oscillations. Therefore, the research of piezoelectric ceramics actuator on hysteresis nonlinear modeling, identification and control method, as well as to the control strategies and methods when micro actuator implements error compensation in the process of switch control of dual-actuator have the important significance.Taking macro/micro positioning platform as the research object, the nonlinearity is first analyzed in nanometer positioning stage driven by piezoelectric actuator through experiments. Meanwhile, several common phenomenological hysteresis modeling methods are discussed and analyzed.Mutation-Particle Swarm Optimization of chaotic map is used for identification of Prandtl-Ishlinskii(P-I) hysteresis model. P-I hysteresis model is nonlinear and its parameters are identified and adjusted difficultly. These characteristics are put forward higher demands and challenges for the conventional optimal control algorithms. In view of this, the group of intelligent evo lutionary algorithm: particle swarm optimization(PSO) is studied and improved. Firstly, three typical benchmark functions are tested and analyzed for three PSO algorithms having been improved. Secondly, in order to improve the searching ergodicity and the diversity of population, an initial method of adaptive inertia weight in chaotic map is proposed and the swarm’s convergence proved is prior to stochastic initialization by embedding in three common improved PSOs with test of three b enchmark functions. Finally, the convergence precision of MPSO algorithm with Logistic map is the best by comparing the simulation results. Based on the analysis of P-I model, the chaotic MPSO is implemented to solute the weight parameters of P-I model. The experimental results show that the parameters of model identified can make the P-I model trajectory fitting well with the experiment finally. So a conclusion is obtained that P-I model can accurately describe the hysteresis nonlinearity of piezoelectric ceramics.Hysteresis compensation control of micro positioning platform is studied. Firstly, the feedforward inverse compensation controller is designed with P-I model of identification. Secondly, two methods of the closed loop control of the PID control(displacement) and the P-I control are implemented respectively to improve the positioning precision based on the different input signal. And the inverse model of the nanometer positioning platform is obtained by P-I control of closed loop.Switch control based on macro/micro positioning platform is studied. According to the platform’s characteristic of feedbacks with double grating rulers, an adaptive inverse compensation control method is proposed. In the condition of macro platform with the control strategy of PID and feed-forward control, the static and dynamic switch control method of nanometer positioning platform are discussed and studied. Based on the characteristic of double grating feedback of dual platform and with the inverse model calculated of micro stage, a switch control method with adaptive inverse compensation is proposed. Finally the experimental results show that the method for final error has a good compensation effect.