Estimation of parameter bounds from bounded-error data: a survey
Mathematics and Computers in Simulation - Parameter identifications with error bound
Membership-set estimation using random scanning and principal componet analysis
Mathematics and Computers in Simulation - Parameter identifications with error bound
Optimal estimation theory for dynamic systems with set membership uncertainty: an overview
Automatica (Journal of IFAC)
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Comparing different approaches to model error modeling in robust identification
Automatica (Journal of IFAC)
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In nonlinear robust identification context, a process model is represented by a nominal model and possible deviations. With parametric models this process model can be expressed as the so-called Feasible Parameter Set (FPS), which derives from the minimization of identification error specific norms. In this work, several norms are used simultaneously to obtain the FPS. This fact improves the model quality but, as counterpart, it increases the optimization problem complexity resulting in a multimodal problem with an infinite number of minima with the same value which constitutes FPS contour. A special Evolutionary Algorithm (ε– GA) has been developed to find this contour. Finally, an application to a thermal process identification is presented.