This paper investigates the disturbance observer based actor-critic learning control for a class of uncertain nonlinear systems in the presence of unmodeled dynamics and time-varying disturbances. The proposed control algorithm integrates a filter-based design method with actor-critic learning architecture and disturbance observer to circumvent the unmodeled dynamic and the time-varying disturbance. To be specific, the actor network is employed to estimate the unknown system dynamic, the critic network is developed to evaluate the control performance, and the disturbance observer is leveraged to provide efficient estimation of the compounded disturbance which includes the time-varying disturbance and the actor-critic network approximation error. Consequently, high-gain feedback is avoided and the improved tracking performance can be expected. Moreover, a composite weight adaptation law for actor network is constructed by utilizing two types of signals, the cost function and the modeling error. Eventually, theoretical analysis demonstrates that the developed controller can guarantee bounded stability. Extensive simulations and experiments on a robot manipulator are implemented to validate the performance of the resulted control strategy.

This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters, mismatched and matched disturbances. Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only, the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters. Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way. With skillful integration of the backstepping technique and the adaptive control, a synthesized controller framework is successfully developed for electro-hydraulic axis systems, in which the coupled interaction between parameter estimation and disturbance estimation is avoided. Accordingly, this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances. Also, a nonlinear filter is designed to eliminate the “explosion of complexity” issue existing in the classical back-stepping technique. The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured. Finally, contrastive experiment results validate the superiority of the developed method as well.

Unknown dynamics including mismatched mechanical dynamics (i.e., parametric uncertainties, unmodeled friction and external disturbances) and matched actuator dynamics (i.e., pressure and flow characteristic uncertainties) broadly exist in hydraulic actuation systems (HASs), which can hinder the achievement of high-precision motion axis control. To surmount the practical issue, an observer-based control framework with a simple structure and low computation is developed for HASs. First, a simple observer is utilized to estimate mismatched and matched unknown dynamics for feedforward compensation. Then combining the backstepping design and adaptive control, an appropriate observer-based composite controller is provided, in which nonlinear feedback terms with updated gains are adopted to further improve the tracking accuracy. Moreover, a smooth nonlinear filter is introduced to shun the “explosion of complexity” and attenuate the impact of sensor noise on control performance. As a result, this synthesized controller is more suitable for practical use. Stability analysis uncovers that the developed controller assures the asymptotic convergence of the tracking error. The merits of the proposed approach are validated via comparative experiment results applied in an HAS with an inertial load as well.

High dynamic tracking performance is a key technical index of hydraulic flight motion simulator (HFMS). However, the strong nonlinearities, various model uncertainties and measurement noise in hydraulic actuation systems limit the high dynamic performance improvement. In this paper, the outer axis frame of a HFMS is taken as a case study and its nonlinear dynamic model with consideration of strong nonlinearities, matched and mismatched uncertainties is established. A novel cascaded extended state observer (ESO) is proposed to estimate the unavailable system states to avoid the adverse effect of measurement noise on control performance. Meanwhile, the designed cascaded ESO also produces estimates of matched and mismatched uncertainties. Then, an output feedback robust controller (OFRC) is proposed by integrating the cascaded ESO with a robust integral of the sign of the error (RISE) feedback based on the backstepping framework. The proposed controller achieves compensation of both matched and mismatched model uncertainties in an output feedback form. Theoretical analysis indicates that the proposed OFRC ensures the boundedness of all closed-loop system signals in the presence of matched and mismatched time-varying model uncertainties. Excellent asymptotic tracking performance can also be obtained when the model uncertainties are time-invariant. Comparative experimental results show that the proposed OFRC achieves significant performance improvement compared with the extensively employed PI control with velocity feedforward (VFPI).