LQR Autonomous Longitudinal Cruise Control with a Minimum Order State Observer

M.J. Khan, S. Wang, U. Keerio, and N. Rao (PRC)


Vehicle longitudinal control, LQR optimal control, intelligent transportation systems, automatic cruise control.


Continuous growth of population all over the world creates a great challenge to the transport management systems. In future intelligent transportation systems, one important aspect of automation components is the design of intelligent control systems that enables the system to become autonomous, hence ensuring safety, comfort and best usage of available infrastructure. In this paper, an optimal control strategy is adopted for a longitudinal vehicle model. A feedback-linearized third-order system models the vehicle and power train dynamics. Based on the theory of optimal control by LQR 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 our strategy under the constraints of physical limitations yields valid results. Since the plant model involves differentiation of a state variable to generate another, resulting in a reduction of signal to noise ratio, a minimum order state observer is designed for the feedback system. The results are further enhanced by using a feed-forward controller to ensure maximum safety and improved performance. A comparative simulation study reveals the system’s performance under certain conditions.

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