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Go to Editorial ManagerIn this paper, the H-infinity Sliding Mode Control (HSMC) is designed to produce a new dynamic output feedback controller for trajectory tracking of the nonlinear human swing leg system. The human swing leg system represents the support of human leg or the humanoid robot leg which is usually modeled as a double pendulum. The thigh and shank of a human leg is represented by two pendulum links and the hip joint will connect the upper body to the thigh and the knee joint will connect the thigh to the shank. The external torques (servo motors) are applied at the hip and knee joints to move the muscles of thigh and shank. The results show that the HSMC can robustly stabilize the system and achieve a desirable time response specification better than if only H-infinity or SMC is used. This controller achieves the following specifications: sec, for hip joint and sec, for knee joint.
In this work, the design procedure of a hybrid robust controller for crane system is presented. The proposed hybrid controller combines the linear quadratic regulator (LQR) properties with the sliding mode control (SMC) to obtain an optimal and robust LQR/SMC controller. The crane system which is represented by pendulum and cart is used to verify the effectiveness of the proposed controller. The crane system is considered one of the highly nonlinear and uncertain systems in addition to the under-actuating properties. The parameters of the proposed LQR/SMC are selected using Particle Swarm Optimization (PSO) method. The results show that the proposed LQR/SMC controller can achieve a better performance if only SMC controller is used. The robustness of the proposed controller is examined by considering a variation in system parameters with applying an external disturbance input. Finally, the superiority of the proposed LQR/SMC controller over the SMC controller is shown in this work.
A new robust control algorithm is proposed for a class of nonlinear systems represented by a Single Link Manipulator (SLM) system. This algorithm is based on new techniques and methods in order to obtain a controller for the SLM system. First of all, the system is simplified using Variable Transformation Technique (VTT) in order to fit the analysis procedure. Then, a new idea of designing a model reference for the multiple states (n=4) system is presented to correspond the control design. Next, the Lyapunov Stability Analysis (LSA) is used to figure out a proper controller that can compensate the stability and the performance of the SLM system. After that, the Most Valuable Player Algorithm (MVPA) is applied to find the optimal parameters of the proposed controller to accomplish the optimum performance improvement. Finally, it can be concluded that the proposed control algorithm has improved the stability and the performance of the SLM system. In addition, the simulation results show the remarkable effects of the proposed nonlinear controller on the SLM system.