Intelligent longitudinal cruise control by quadratic minimization and robust synthesis

In the last four decades, many efforts have been made to improve the factors of safety and comfort in the area of vehicular traffic. In future intelligent transportation systems, one important aspect of automation components is the design of intelligent control systems that enables the system to behave autonomously, thus ensuring safety, comfort and best usage of available infrastructure. In this paper, two separate control strategies are adopted for a longitudinal vehicle model. A third-order linear system models the vehicle and power train dynamics. Based on the theory of optimal control by QR methods, firstly, one strategy for automated vehicle tracking is described comprehensively. A priori choice of the weights in the local quadratic criteria allows obtaining diverse desired overall system characteristics. Simulation results reveal that the strategy under the constraints of physical limitations yields valid results. Uncertainties in the plant parameters, being unavoidable, are then introduced to the extent of worst case deviation, and then the second control strategy based on robust H-infinity control is adopted which though tends the control to lose little on performance but handles uncertainties in the plant variation to the desired extent.