Quantised MPC for LPV systems by using new Lyapunov–Krasovskii functional - Lee, Sangmoon; Kwon, Ohmin (IET control theory & applications, 2017)
This study deals with the problem of sampled-data model predictive control (MPC) for linear parameter varying (LPV) systems with input quantisation. The LPV systems under consideration depend on a set of parameters that are bounded and available online. To deal with a piecewise constant sampled-data and quantisation of the control input, the closed-loop system is modelled as a continuous-time impulsive dynamic model with sector non-linearity. The control problem is formulated as a minimisation of the upper bound of infinite horizon cost function subject to a sufficient condition for stability. The stability of the proposed MPC is guaranteed by constructing new Lyapunov–Krasovskii functional. Finally, a numerical example is provided to illustrate the effectiveness and benefits of the proposed theoretical results.