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— Piecewise affine (PWA) systems are useful models for describing non-linear and hybrid systems. One of the key problems in designing controllers for these systems is the inherent computational complexity of controller synthesis and analysis. These problems are amplified in the presence of state and input constraints and additive but bounded disturbances.(More)
The optimiser of a (multi) parametric linear program (pLP) is a piecewise affine function defined over a polyhedral subdivision of the set of feasible states. Once this affine function has been pre-calculated, the optimal solution can be computed for a particular parameter by determining the region that contains it. This is the so-called point location(More)
Closed-form Model Predictive Control (MPC) results in a polytopic subdivision of the set of feasible states, where each region is associated with an affine control law. Solving the MPC problem on–line then requires determining which region contains the current state measurement. This is the so-called point location problem. For MPC based on linear control(More)
We present a novel algorithm for the computation of explicit optimal control laws for piecewise affine (PWA) systems with linear performance indices. The algorithm is based on dynamic programming (DP) and represents an extension of ideas initially proposed in (Kerrigan and Mayne, 2002; Baoti´c et al., 2003). Specifically, we show how to exploit the(More)
This paper addresses invariant set computation for discrete-time switched systems subject to bounded disturbances. Specifically, we show how to compute the maximal robust switched invariant set˜C S ∞ , which we define to be the set of states which can be made robust invariant by an appropriate switching law. Furthermore it is demonstrated how the maximal(More)
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