Horizon-1 predictive control of networked controlled vehicle drivetrains

Design of a controller that damps driveline oscillations, while compensating network-induced time-varying delays, can be a challenging problem considering that vehicle drivetrains are characterized by fast dynamics that are subject to physical and control constraints. As such, the goal of this paper is to provide a control design methodology that can cope with all these challenges and limitations and still yield an effective solution. To this end, firstly, a method for determining a worst case upper bound on the delays that can be introduced by a Controller Area Network (CAN) is presented. Then, a polytopic approximation technique is applied to obtain a discrete-time model of the closed-loop CAN system. Thirdly, a horizon-1 predictive controller based on flexible control Lyapunov functions is designed for the resulting model with polytopic uncertainty and hard constraints. Several tests performed on a benchmark model indicate that the proposed design methodology can handle both the performance/physical constraints and the strict limitations on the computational complexity.