Lyapunov based predictive control of vehicle drivetrains over CAN

Vehicle drivetrains are characterized by fast dynamics, subject to physical and control constraints, which make controller design for driveline oscillations damping a challenging problem. Furthermore, in current implementations, the connections between the controller and the physical plant are realized using a controller area network (CAN) as the communication medium, which introduces time-varying delays. 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 continuous-time model of a vehicle drivetrain is derived. Then, a method for determining a worst case upper bound on the delays that can be introduced by a CAN is presented, which enables the usage of a polytopic approximation technique to obtain a discrete-time model of the closed-loop CAN system. Thirdly, a non-conservative Lyapunov based predictive controller is designed for the resulting model with time-varying delays, polytopic uncertainty and hard constraints. Several tests performed using an industry validated drivetrain model and the Matlab toolbox TrueTime indicate that the proposed design methodology can handle both the performance/physical constraints and the strict limitations on the computational complexity, while effectively coping with time-varying delays. Preliminary real-time results further validate the proposed methodology.