English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The dc motor is one of the most fundamental electromechanical devices of mechatronic systems, which plays an important role in maintaining the accuracy in the execution of tasks. One of the main issues in the accuracy and robustness of dc motor control system is how to optimally tune its parameters. In this paper, a multi-objective online tuning optimization approach is proposed to adaptively tune up the velocity control parameters of the permanent magnet dc motor. This approach simultaneously considers the modeled error and the corresponding sensitivity to choose the best compromise solution in the Pareto dominance-based selection process of solutions to deal the changing optimum solutions in the dynamic environment of the tuning approach based on online optimization method and moreover, the modified differential evolution with induced initial population based on non-dominated solution through a memory is proposed to guide the search into the feasible region, and to promote the exploitation of solutions found in the previous time interval. Simulation results verify that proposed modifications provide higher robustness and better quality in the velocity regulation control of the dc motor under parametric uncertainties, and also under discontinuous dynamic load, than multi-objective differential evolution, particle swarm optimization, and non-dominated sorting genetic algorithm-II.

Multi-Objective On-Line Optimization Approach for the DC Motor Controller Tuning Using Differential Evolution