In most field robots, go or no-go decision depends on the maximum height of a bump. For combat vehicles, however, much advanced capability of the vehicle is required to pass over a higher bump compared to its wheel radius. For this purpose, many combat vehicles are using variable geometry suspension (VGS). In this paper, a 6x6 vehicle with a rotating VGS was designed. Computer simulations of the designed vehicle were carried out with the ADAMS program to estimate motor capacity and the required torque. The suspension was designed to rotate 360 degrees about the swing axis, thus, the vehicle could climb a higher bump by rotating its suspension.
Due to the inherent nonlinear nature of Electro-rheological(ER) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the nonlinear damping force model is made to identify the properties of the ER damper using higher order spectrum. The higher order spectral analysis is used to investigate the nonlinear frequency coupling phenomena with the damping force signal according to the sinusoidal excitation of the damper. Also, this paper presents an inverse model of the ER damper, i.e., the model can predict the required voltage so that the
ER damper can produce the desired force for the requirement of vibration control of vehicle suspension systems. The inverse model has been constructed by using a multi-layer perceptron. A quarter-car suspension model is considered in this paper for analysis and simulation. Simulation results show that the proposed inverse model of ER damper can obtain control voltage of ER damper for required damping force.
Recently, there exists an abundance of research on the semi-active suspension system. The skyhook control is commonly known to control semi-active suspension system because it has practicality. In this paper, the fuzzy logic control based on heuristic knowledge is combined with the skyhook control. And it simulated in a quarter car model. The acceleration value of the sprung mass was reflected in fuzzy inference to reduce the vertical acceleration RMS value of the sprung mass. Then scale factors and membership functions that determine performance efficiency of fuzzy skyhook controller are tuned by a genetic algorithm known as a kind of optimization method.