Computer-controlled systems: theory and design (2nd ed.)
Computer-controlled systems: theory and design (2nd ed.)
Discrete-time control systems (2nd ed.)
Discrete-time control systems (2nd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Digital Control Systems
Robust Control: The Parametric Approach
Robust Control: The Parametric Approach
Digital Control of Dynamic Systems
Digital Control of Dynamic Systems
Robust Control: Systems with Uncertain Physical Parameters
Robust Control: Systems with Uncertain Physical Parameters
Identification of Continuous-Time Systems: Methodology and Computer Implementation
Identification of Continuous-Time Systems: Methodology and Computer Implementation
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
IEICE - Transactions on Information and Systems
Design of optimal disturbance rejection PID controllers usinggenetic algorithms
IEEE Transactions on Evolutionary Computation
Hybrid methods using genetic algorithms for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete interval model is first formulated as multiple mono-objective optimization problems for matrix-value functions associated with the discrete system matrices, and subsequently optimized via a proposed genetic algorithm (GA) to obtain the lower and upper bounds of the entries in the system matrices. To show the effectiveness of the proposed approach, roots clustering of the characteristic equation of the obtained discrete interval model is illustrated for comparison with those obtained via existing methods.