Marco Filippo

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The present paper concerns the design of approximate off-line model predictive control laws for nonlinear discrete-time systems subject to hard constraints on state and input variables. The possibility to obtain an approximate receding horizon control law by performing off-line optimization, leads to a dramatic reduction of the real-time computational(More)
Approximate model predictive control laws for constrained nonlinear discrete-time systems: analysis and offline design G. Pin, M. Filippo, F.A. Pellegrino, G. Fenu & T. Parisini a Electrolux Professional S.p.A., Vallenoncello, 33170, Italy b Department of Engineering and Architecture, University of Trieste, Italy c Department of Electrical and Electronic(More)
The present paper proposes a recursively feasible networked model predictive control scheme for discrete-time constrained interconnected linear systems. A centralized controller, which communicates with the subsystems through a packet-based communication network, is designed to guarantee the uniform boundedness of the trajectories of the overall closed-loop(More)
In this work, the off-line approximation of state-feedback nonlinear model predictive control laws by means of smooth functions of the state is addressed. The idea is to investigate how the approximation errors affect the stability of the closed-loop system, in order to derive suitable bounds which have to be fulfilled by the approximating function. This(More)
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