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This work deals with the continuous predictive control problem for continuous linear systems with inequality constraints on the state and input variables. The problem of the input vector constraints has been solved in the past especially for the discrete linear systems. In this paper, we will develop a continuous model predictive control and show how to use Taylor approximation to transform state...
Although linear Model Predictive Control has gained increasing popularity for controlling dynamical systems subject to constraints, the main barrier that prevents its widespread use in embedded applications is the need to solve a Quadratic Program (QP) in real-time. This paper proposes a dual gradient projection (DGP) algorithm specifically tailored for implementation on fixed-point hardware. A detailed...
This paper proposes a novel method for design and circuit implementation of approximate controllers for constrained hybrid or piecewise affine (PWA) systems, through switched model predictive control technique. The PWA solution (discontinuous, in general) provided by this method is approximated by another PWA function composed of continuous patches defined over regular simplices. Two circuit architectures...
This paper develops a technique for improving the region of attraction of a robust variable horizon model predictive controller. It considers a constrained discrete-time linear system acted upon by a bounded, but unknown time-varying state disturbance. Using constraint tightening for robustness, it is shown how the tightening policy, parameterised as direct feedback on the disturbance, can be optimised...
In this article a novel approach to the determination of polytopic invariant sets for constrained discrete-time linear uncertain systems is presented. First, the problem of stabilizing a prespecified initial condition set in the presence of input and state constraints is addressed. Second, the problem of computing an estimate of the maximal positively invariant or controlled invariant set for this...
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