In this paper, the nonlinear dynamic of the leg extension model through Functional Electrical Stimulation (FES) is studied. FES method is used to restore functional movement in which muscles are stimulated by low-level electrical current. However, using FES can cause muscle fatigue and when it occurs, patients are unable to use the rehabilitation devices, so investigations have been done to reduce the muscle fatigue and increase the time of benefiting from FES-based devices. Moreover, a multi-loops adaptive sliding control algorithm is proposed for the nonlinear system with unknown parameters in order to track the desired muscle activation and knee joint angle trajectory. The designed strategy can manipulate the electrical stimulation properly to compel the human leg to show particular motions which is beneficial for restoring the previous motions without causing muscle fatigue or muscle weakness. The proposed control has two loops to achieve the control goal, so it can be said that it is for the first time that the multi-loops adaptive sliding control is implemented into the unknown leg extension neuroprosthesis system. The Lyapunov theory is proposed to prove the stability of the control law. Finally numerical results illustrate that the control algorithm can be an effective control for tracking and identifying the uncertain system via FES.