Robust and compliance control for robotic knee prosthesis using admittance model and sliding-mode controller

Abstract

Achieving compliance and flexibility under the premise of ensuring trajectory tracking performance and also reflecting the wearer’s movement intention, has not yet been well solved in the field of prosthesis. The aim of this paper is to provide a compliant, robust, and continuous control scheme for robotic knee prosthesis to solve the contradictory problems of trajectory tracking performance and compliance. The proposed scheme are based on the admittance model and radial basis function (RBF) neural network–enhanced nonsingular fast terminal sliding-mode controller (NFTSMC). The desired trajectory of the prosthetic knee joint is driven by humans and reshaped to reference trajectory by an admittance model, so that the prosthetic leg can reflect the human’s movement intention and being compliant. RBF neural network is introduced to achieve adaptive approximation of unknown models and ensure that the controller does not depend on the mathematical model of the “human-in-the-loop” prosthesis system. A novel NFTSMC was proposed to deal with the influence of ground reaction forces (GRFs) and fitting errors of the RBF neural network, which make the tracking error converge to zero in a finite time. The adaptive law of the RBF neural network is obtained by the Lyapunov method, and the stability and finite-time convergence of the closed-loop system are rigorously proved and analyzed mathematically. The simulation results prove the feasibility and effectiveness of the propose control scheme.

Extended state observer–based improved non-singular fast terminal sliding mode for mobile manipulators

“…As compared to the developed SM surfaces, the NFTSM avoids singularities and has a fast finite-time reaching even when the state is far from the equilibrium point (Boukattaya et al, 2018). In view of these promising features, the NFTSM controller has gained popularity for high-accurate tracking control problems in robotic systems such as in RM (Boukattaya et al, 2018; Geng et al, 2014; Lu et al, 2022), robotic knee prosthesis (Huang et al, 2022), underactuated quadrotor UAV (Labbadi and Cherkaoui, 2020), and mobile lower limb exoskeleton (Hernandez et al, 2020). Furthermore, non-singular fast terminal sliding mode control (NFTSMC) techniques have been a few works published recently to solve the problem of tracking trajectory of MM.…”