Online constraint removal: Accelerating MPC with a Lyapunov function

Simulation studies on online constraint removal with a Lyapunov function

MPC for LPV Systems Based on Parameter-Dependent Lyapunov Function with Perturbation on Control Input Strategy

In this paper, the model predictive control (MPC) algorithm for linear parameter varying (LPV) systems is proposed. The proposed algorithm consists of two steps. The first step is derived by using parameter-dependent Lyapunov function and the second step is derived by using the perturbation on control input strategy. In order to achieve good control performance, the bounds on the rate of variat...

Robust Mpc Controller Design for Switched Systems Using Multi-parameter Dependent Lyapunov Function

The paper addresses the problem of designing a robust output/state model predictive control for linear polytopic switched systems. We propose a new method for calculation of control algorithm parameters for predictive robust control of a linear switched polytopic system. Lyapunov function approach guarantees the multi-parameter-dependent quadratic stability (MPDQS) and guaranteed cost for a clo...

Stable Constrained MPC without Terminal Constraint

Sufficient conditions to guarantee stability of MPC strategies require the use of a terminal cost function and a terminal constraint region [9]. This paper gives a procedure for removing the terminal constraint while maintaining asymptotic stability. This is specially interesting when the system is unconstrained on the state. In this case, the computational burden of the optimization problem do...

Interpolation based MPC with exact constraint handling: the nominal case

Interpolation techniques are known to reduce computational complexity of MPC algorithms (Rossiter et al., 2004, Bacic et al., 2003). However, despite giving good feasible regions, there is nevertheless often some conservatism. This paper presents a new insight on general interpolation which reduces this conservatism and hence allows a substantial increase in feasible regions and therefore the p...