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Particle Swarm Optimization (PSO) is an effective optimization technique that can efficiently solve nonlinear and non-convex optimization problems, however, system constraints like output and states constraints cannot be considered. On the other hand, Model Predictive Control (MPC) is an efficient optimization technique that can offer the optimal solution while respecting the given constraints; however,...
This paper deals with parameter and state estimation in a bounded-error context for uncertain dynamical aerospace models when the input is considered optimized or not. In a bounded-error context, perturbations are assumed bounded but otherwise unknown. The parameters to be estimated are also considered bounded. The tools of the presented work are based on a guaranteed numerical set integration solver...
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