In this article, a new neural-network-based sliding-mode control (SMC) of an uncertain robot is presented. The distinguishing characteristic of the proposed control scheme is that the switching gain is designed as a dynamic model approximated value, which is handled by using the neural-network strategy to adapt the unknown dynamics and disturbances. In the presented control scheme, the modeling information of the robotic system is not required and only one parameter is required to be estimated in each joint of the robotic system. Subsequently, the Lyapunov method is utilized to prove that the trajectory tracking errors will eventually converge to a neighborhood of zero. Finally, the contrast simulation studies reveal that with the proposed control scheme, the problems of chattering and high-speed switching of control input, which takes place in a conventional SMC, can be addressed, and a satisfactory control precision is guaranteed.

During past four decades, applications of magnetorheological and electrorheological fluids in adaptive sandwich structures have been widely studied, primarily for the purpose of vibration control. The rapid response time of controllable magnetorheological/electrorheological fluids to an applied magnetic/electric field and reversible variations in their stiffness and damping properties have been the key motivations for adaptive structures applications. This article presents a comprehensive review of the reported studies on applications of magnetorheological/electrorheological fluids for realizing active and semi-active vibration suppression in sandwich structures. The review focuses on methods of characterizing the magnetorheological/electrorheological fluids in the pre-yield region, magnetic/electric field-dependent phenomenological models describing the storage and loss moduli of fluids, experimental and analytical methods developed for vibration analysis of sandwich structures with magnetorheological/electrorheological fluid treatments, analysis of structures with partial magnetorheological/electrorheological fluid treatments and optimal treatment locations, and developments in control strategies for vibration suppression of magnetorheological/electrorheological sandwich structures. The studies on dynamic responses of fully and partially treated magnetorheological/electrorheological-based sandwich beams, plates, shells, and panels are also discussed, including the mathematical modeling methods and associated assumptions, methods of solutions, and experimental methods.

The magnetorheological brake (MRB) is an electromechanical device that generates a retarding torque through employing magnetorheological (MR) fluids. The objective of this paper is to design, optimize and control an MRB for automotive applications considering. The dynamic range of a disk-type MRB expressing the ratio of generated toque at on and off states has been formulated as a function of the rotational speed, geometrical and material properties, and applied electrical current. Analytical magnetic circuit analysis has been conducted to derive the relation between magnetic field intensity and the applied electrical current as a function of the MRB geometrical and material properties. A multidisciplinary design optimization problem has then been formulated to identify the optimal brake geometrical parameters to maximize the dynamic range and minimize the response time and weight of the MRB under weight, size and magnetic flux density constraints. The optimization problem has been solved using combined genetic and sequential quadratic programming algorithms. Finally, the performance of the optimally designed MRB has been investigated in a quarter vehicle model. A PID controller has been designed to regulate the applied current required by the MRB in order to improve vehicle’s slipping on different road conditions.