Longitudinal dynamics control is the basis for autonomous driving of intelligent vehicles, which have great significance to the development of intelligent transportation system (ITS). To solve the problems of traditional sliding mode control method when applied to intelligent vehicle longitudinal dynamics, such as large velocity tracking errors, strong chattering phenomenon and so on, a new sliding mode control strategy based on RBF (Radical Basis Function) neural network is presented in this paper. Firstly, a nonlinear mathematical model of the intelligent vehicle longitudinal motion is established by considering the dynamics of the engine, the torque converter, the automatic transmission and the brake system. On the basis of the system model, a variable structure control system with sliding mode is introduced to design a sliding mode variable controller with RBF neural network. This controller can adaptively adjust the switching gain and its stability is proved based on the Lyapunov theory. Finally, the effectiveness of the designed longitudinal velocity control strategy is verified by simulation under typical driving conditions. The simulation results show that the improved control algorithm can effectively suppress chattering, obtain the higher precision and stronger robustness than the traditional sliding mode control. Thus, the longitudinal motion control performance of intelligent vehicles is improved effectively. INDEX TERMS Intelligent vehicles, intelligent transportation system, longitudinal dynamics control, sliding mode control, RBF neural network.
A new kind of semi-active energy-regenerative suspension system is proposed to recover suspension vibration energy, as well as to reduce the suspension cost and demands for the motorrated capacity. The system consists of an energy-regenerative damper and a DC-DC converterbased energy-regenerative circuit. The energy-regenerative damper is composed of an electromagnetic linear motor and an adjustable shock absorber with three regulating levels. The linear motor just works as the generator to harvest the suspension vibration energy. The circuit can be used to improve the system's energy-regenerative performance and to continuously regulate the motor's electromagnetic damping force. Therefore, although the motor works as a generator and damps the isolation without an external power source, the motor damping force is controllable. The damping characteristics of the system are studied based on a two degrees of freedom vehicle vibration model. By further analyzing the circuit operation characteristics under different working modes, the double-loop controller is designed to track the desired damping force. The external-loop is a fuzzy controller that offers the desired equivalent damping. The inner-loop controller, on one hand, is used to generate the pulse number and the frequency to control the angle and the rotational speed of the step motor; on the other hand, the inner-loop is used to offer the duty cycle of the energy-regenerative circuit. Simulations and experiments are conducted to validate such a new suspension system. The results show that the semi-active energy-regenerative suspension can improve vehicle ride comfort with the controllable damping characteristics of the linear motor. Meanwhile, it also ensures energy regeneration.
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