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The application of fractional calculus to signal processing and adaptive learning is an emerging area of research. A novel fractional adaptive learning approach that utilizes fractional calculus is presented in this paper. In particular, a fractional steepest descent approach is proposed. A fractional quadratic energy norm is studied, and the stability and convergence of our proposed method are analyzed...
In this paper, we propose a new method for digital RST controller design based on the Particle Swarm Optimization metaheuristic. It is a systematic RST synthesis and tuning procedure to deal with the complexity of the known classical poles placement methods. The case of an electric DC drive benchmark has been successfully obtained to illustrate the efficiency of the proposed PSO-based RST control...
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