An embedded Hildreth-based model predictive control of an Elbow Joint Orthosis Robot

Abstract

In this paper, we consider a constrained model predictive control design for an Elbow Joint Orthosis Robot. The challenge of the robotic device control is to achieve passive and resistive rehabilitation movements with hard and soft constraints. A fast quadratic programming solver based on the Hildreth method is developed to meet the short real-time implementation sampling time. The online optimization solver based on the Hildreth method is compared with two other solvers proving its superiority in terms of computation time in the simulation environment. Simulation results show successful set point tracking and constraints satisfaction. An embedded version of constrained model predictive control using the Hildreth quadratic programming solver is implemented on an Arduino Due microcontroller. The results are satisfactory, and motion tracking errors and inputs variance are minimized. Less effort, optimal performances, and absence of overshoot and control signal oscillations are considered to evaluate the different studied motions. A lower computational cost is obtained taking into account the trade-off between the control effort and the closed-loop performances.