Data-driven model-free adaptive sliding mode control for electromagnetic linear actuator

Abstract

A data-driven model-free adaptive sliding mode control (MFASMC) method is proposed to tackle the problems of inaccurate model and time-varying parameters of a micro electro-magnetic linear actuator system, considering the dependence of existing model-based control methods on the system dynamics model and the impact of unmodeled dynamics on the control performance. Firstly, the pseudo-gradient (PG) concept in the model-free adaptive control (MFAC) framework is used to transform the electromagnetic linear actuator dynamics model, which is difficult to obtain parameters accurately, into a full-format dynamic linearized data model, the dependence of the controller on the electromagnetic linear actuator model is reduced. To compensate for the effects of unknown perturbations, an improved discrete sliding mode exponential convergence law is introduced to derive a new composite control algorithm based on the pseudo partial derivative estimator, which improves the robustness of the control system. Then, the convergence of the control error and the stability of the system are demonstrated by theoretical analysis. The results show that the proposed MFASMC reduces the 10mm step response time of the electromagnetic linear actuator by 46.3% and 25.3% compared with PID and MFAC. The phase lag time and root-mean-square error of MFASMC under sinusoidal conditions are 0.8ms, 0.178mm respectively, and the steady-state error does not exceed 0.05mm. The experimental and simulation results keep the error within 5%, the proposed control algorithm has good trajectory tracking response speed and control accuracy, and has good robustness to system uncertainty and external force disturbance.

Dual Model Predictive Control Strategy of Direct‐Drive PMSM Based on Sliding Mode Disturbance Observer

“…The change of q-axis increment i * q (k t ) must be controlled to be small. And to prevent the slight change of q-axis increment i * q (k t ), quadratic performance index is designed as optimization criterion according to (21) and (22):…”

“…Speed loop design requires fast tracking and resistance to external interference [21,22]. At present, a variety of control strategies have been applied to the speed loop, such as SMC [23,24], fuzzy control [25,26], robust control [27,28], MPC [29], etc.…”

Nonlinear electromagnetic force analysis and compensation control of electromagnetic linear actuator

“…Electromagnetic force of the EMLA is the Lorentz force exerted by current-carrying coils in the air-gap magnetic field. Therefore, the nonlinearity of air-gap magnetic field will lead to the nonlinearity of electromagnetic force [32]. In the open circuit state, the magnetic flux density in the air gap regions is…”