No abstract

Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.

A real-value classifier system (CSR) is improved by the introduction of a continuous domain of actions to be employed for control of mechanical systems where there is no information concerning the system's mathematical model. To enable the classifier system to handle real-world control problems where continuous (non-discrete) actions are required, the exploitation of fuzzy membership functions is proposed. To cope with the dynamic system's delayed response due to its mass inertia, a dynamic reward assignment mechanism is incorporated into the proposed CSR. This allows the rapid calculation of the reward and hence enables the controller to be used in such real time applications. To demonstrate the efficiency of the developed enhanced CSR, it is employed as the controller to balance an unmanned bicycle, without using bicycle properties for the design process of the enhanced CSR. Simulation results show that in terms of overshoot and settling time, the proposed classifier system outperforms traditional XCSR as well as some of the more common balance-control strategies reported in the literature, as verified using ADAMS software.

This paper addresses the effect of different optimization criteria for the control purpose of vehicle suspension. In the present study, active vibration control system for a 5 degree-of-freedom (DoF) pitch-plane suspension model with bounce and pitch motions is investigated. In the proposed vehicle model, the impact of the wheel-axle-brake assemblies’ masses is also considered. The developed model is controlled using a fuzzy logic controller (FLC) to minimize the vibration of the driver’s seat. The controller is designed to control the applied force to the seat. Furthermore, in order to determine the optimal value of fuzzy system parameters, genetic algorithm (GA) optimization search is used based on minimizing both vibrations and accelerations of the driver’s seat. In other words, two different criteria are chosen for optimization of the controller: minimizing either absolute displacement or absolute acceleration which is related to ride comfort. In each case, the simulation is implemented and the results are presented. It is shown that optimization according to only one criterion may lead to undesirable results in other system parameters. In addition, it is demonstrated that considering absolute displacement as the only factor to be minimized is ineffective. Finally, another criterion which is a combination of the two previous criteria has been suggested and tested and the obtained results are presented. The combinational criterion can suppress the vibration as well as decreasing the vehicle acceleration.

No abstract