A decentralized observer-based optimal control for interconnected systems using the block pulse functions

International audienceThe paper proposes a method to integrate numerically an interconnected system, based on an idea of orthogonal approximation of functions. Here, block pulse functions (BPFs) are chosen as the orthogonal set. The main advantage of using this technique is its ability to transform the original optimal control problem to a mathematical programming problem relatively easier to solve. The primary focus of this paper is to exploit and rigorously develop the BPFs parametrization technique for the synthesis of a decentralized observer-based optimal control for large-scale interconnected systems. In addition, we develop a mathematical model of a double-parallel inverted pendulum coupled by a spring, taking into account all possible changes of the connecting position of the elastic spring. In so doing, we conducted advanced simulations applying the new optimal control method to the studied interconnected system. Our results demonstrate the validity and the effectiveness of the developed decentralized observer-based optimal control approach

A Novel LQR-Based Cascaded Control Scheme of a Powered Knee Joint Orthosis for Rehabilitation

International audienceIn order to improve the healthcare services quality, various initiatives have been carried out to develop new assistive technologies such as wearable robots. This paper deals with the control of an actuated knee joint orthosis dedicated to assistive and rehabilitation purposes. The proposed control scheme is based on a nonlinear state feedback complied with a linear quadratic regulator (LQR) in a cascaded control architecture. The proposed control scheme has been validated in simulation for the control of an active orthosis in various operating conditions and compared with a PID controller. The obtained simulation results show clearly the efficiency of the proposed control scheme and its superiority with respect to the PID in terms of the tracking performance and the comfort of the user

An Assistive Explicit Model Predictive Control Framework for a Knee Rehabilitation Exoskeleton

International audienceThis article focuses on the control of an actuated knee joint orthosis. The proposed solution is a novel model predictive control framework dedicated to assistive and rehabilitation purposes. This framework includes 1) an exact input-to-state feedback linearization, 2) a model predictive controller (MPC or EMPC), considering input/output constraints, 3) a least-squares dynamic parameters identification, 4) a nonlinear disturbance observer for the estimation of the wearer's torque, 5) a Lyapunov-based stability analysis of the resulting closed-loop system, and 6) a reference trajectory generator. The proposed framework has been validated via real-time experiments performed on three healthy subjects wearing the knee joint orthosis. Various experimental scenarios have been considered, including assistive and resistive rehabilitation tasks in a sitting position and walking with normal/abnormal gait patterns. The obtained results indicate the efficiency of the proposed predictive controllers with respect to a conventional proportional-integral-derivative (PID) controller in terms of tracking performance, required torque, and wearer comfort