Control of robotic systems is an interesting subject due to their wide spectrum applications in medicine, aerospace and other industries. This paper proposes a novel continuous control mechanism for tracking problem of a 5-DOF upper-limb exoskeleton robot. The proposed method is a combination of a recently developed robust integral of the sign of the error (RISE) feedback and neural network (NN) feed-forward terms. The feed-forward NN learns nonlinear dynamics of the system and compensates for uncertainties while the NN approximation error and nonlinear bounded disturbances are overcome by the RISE term. Typical NN-based controllers generally result in uniformly ultimately bounded (UUB) stability due to the NN reconstruction error. In this paper to eliminate this error and achieve asymptotic tracking, the RISE feedback term is integrated into the NN compensator. Finally, a comparative study on the system performance is conducted between the proposed control strategy and two other conventional control methods. Simulation results illustrate the effectiveness of the proposed method. تفاصيل المقالة

In this paper, an integration of Improve Particle Swarm Optimization (IPSO) in combination with Successive Quadratic programming (SQP) so called IPSO-SQP algorithm is proposed to solve time optimal bang-bang control problems. The procedure is found not sensitive to the initial guess of the solution. Due to random selection in the first stage of the search process, the chance of converging to the global optimum is significantly increased, without sticking in a local optimum. The combined technique gains both advantages of its original algorithms. The IPSO directly minimizes the cost function without the need for gradient-based techniques. The performance of the outcome will be increased when the SQP immediately undertakes the optimization task. This is shown via applying those on some other nonlinear systems. Consequently, the proposed algorithm is successfully applied on a time optimal bang-bang control of an autonomous underwater vehicle. A pitchprogramming task is also investigated for the autonomous underwater vehicle by designing an optimal PID controller . تفاصيل المقالة