LMI-Based Design of a Robust Affine Control Law for the Position Control of a Knee Exoskeleton Robot: Comparative Analysis of Stability Conditions

Rehabilitation exoskeleton robots have emerged as valuable tools for restoring functional lower limb movements in individuals afflicted with locomotor impairments. Our innovative approach is centered on the use of a linear state-feedback control strategy, meticulously designed to achieve precise control over the knee exoskeleton’s position, even in the face of complex dynamics and challenges posed by the presence of frictions, uncertain parameters, and external disturbances. To achieve this goal, we will rely on the Lyapunov methodology, allowing us to develop three distinct methods for establishing stability conditions. These conditions are presented in the form of Linear Matrix Inequalities (LMIs). We have also conducted a thorough comparative analysis to assess the efficiency of these methods. As we conclude this research, we have fortified our findings with comprehensive simulations, which offer solid evidence of the effectiveness of our control law in achieving an efficient and robust stabilization of the knee exoskeleton robot.