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This paper proposes a non-iterative, Lyapunov-based distributed model predictive control (MPC) design for invariant spatially-interconnected systems comprised of a network of subsystems with coupled dynamcis and subject to local state and/or input constraints. Considered here is the distributed MPC design for linear systems in input-output form with fixed-structure local state-feedback-like control...
This paper presents an algorithm for solving optimization problems with bilinear matrix inequality (BMI) constraints, which frequently appear in controller synthesis. The algorithm is based on a combination of gradient-based optimization and linear matrix inequalities (LMIs), which makes it fast and enables it to handle a large number of decision variables. Here it is used to synthesize fixed-structure...
This paper considers a hybrid evolutionaryalgebraic approach to the non-convex problem of designing low-order H∞ optimal controllers. It is shown that using the closed-loop H∞ norm as fitness measure in a population-based, evolutionary search does not require the computation of the H∞ norm for each controller of the population. Instead, the fact that evolutionary algorithms assign fitness measures...
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