Kalman filter-based adaptive impedance control strategy for electro-hydrostatic actuator

In the process of EHA used in force control, due to the nonlinearity of EHA, the uncertainty of the model and the unknown load environmental parameters, the force tracking error, the impact oscillation in the transition process and the poor dynamic characteristics of EHA, this paper proposes a Kalman filter-based adaptive impedance control strategy. Aiming at the problem of unknown load environment parameters, a nonlinear mathematical model of the system is established. The causes of steady-state errors are analyzed and the adaptive control law is derived to estimate the environmental stiffness and environmental position. Aiming at the system nonlinearity and model uncertainty, the force feedback value after the interaction between the inner loop output and environment is regarded as a signal incorporating process and measurement noise. The Kalman filter principle is used to optimally estimate and correct the system state of the impedance controller. Simulation results show that the Kalman filter-based adaptive impedance control is superior to traditional impedance control in convergence speed and force tracking accuracy. The effectiveness and stability of this control strategy for EHA system under different environmental conditions are confirmed, which lays a solid foundation for precise force control of EHA in engineering applications.