ABSTRACT
This chapter investigates the effect of input saturation on strong string stability. Combining Chebyshev neural networks with sliding mode technique, a new neural network-based adaptive control scheme is provided. Intelligent vehicle highway systems and intelligent transportation systems have attracted considerable attention among researchers for addressing awfully crowded urban traffic. The aim of the platoon control is to track the speed of the leader while maintaining a desired safety spacing between consecutive vehicles. One of major spacing policies for vehicle-following platoons is constant time headway policy. The proposed controller can force the followers to track the leader’s trajectory while maintaining a desired safe spacing simultaneously, even in the presence of input saturation, unknown unmodeled dynamics and external disturbances. A simple and straightforward strategy by adjusting only a single parameter is proposed to attenuate the effect of input saturation.
