This chapter presents a control strategy aimed at robustly stabilizing a one-degree-of-freedom (1-DoF) knee rehabilitation exoskeleton robot. The proposed approach combines a linear state-feedback controller with a nonlinear control law to effectively manage the nonlinear dynamics characteristic of knee-joint exoskeleton systems, particularly in the presence of parameter uncertainties and disturbances. To simplify the model, we approximate the nonlinear function in the robot dynamics. Primarily, we assume that such a nonlinear function is bounded by a constant value, thus leading to the first design approach for the development of the Linear Matrix Inequality (LMI) condition. Following this, we assume that the nonlinear function remains bounded within the constraint of a linear equation. Under this assumption, we develop two distinct methods for the design of the LMI condition. To ensure stability and robustness, a quadratic Lyapunov function is used to derive LMI conditions for the computation of the feedback gain of the control law. In these three design approaches, the development of the LMI conditions is achieved through various technical lemmas such as Young’s inequality, the S-procedure, the Schur complement, and the matrix inversion lemma. The robustness of the controller is validated through simulations that introduce external disturbances. Additionally, a comparative analysis of the proposed control strategies is conducted. Numerical simulations confirm the effectiveness of our control approach in stabilizing the knee-joint exoskeleton robot, even in the presence of external disturbances and parametric uncertainties.