Abstract
There exist hydraulic parametric uncertainty and unknown external load in electro-hydraulic system (EHS), which inevitably decline the tracking performance and the stability of the closed-loop system. In this study, an optimal robust controller (ORC) is presented to solve this problem. Different from the traditional backstepping control, the ORC constructs the Hamilton–Jacobi–Bellman (HJB) equation based on the tracking error model of EHS to optimize the performance cost function as well as derive the optimal control variable. Furthermore, a critical neural network is adopted to estimate the optimal control solution of HJB equation such that guarantee the system state error of EHS uniformly ultimate boundary. Since the model uncertainty is considered in the HJB solution, the ORC has satisfactory robustness by using the network weight updation rather than direct parametric estimation or disturbance observer. The effectiveness of the proposed controller is verified by comparative simulation and experimental results.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
