Adaptive Controller Tuning Method Based on Online Multiobjective Optimization: A Case Study of the Four-Bar Mechanism

Rodríguez-Molina, Alejandro; Villarreal-Cervantes, Miguel Gabriel; Mezura-Montes, Efrén; Aldape-Pérez, Mario

doi:10.1109/tcyb.2019.2903491

Cited by 19 publications

(8 citation statements)

References 33 publications

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“…Among multi-objective evolutionary algorithms, different search approaches for approximating the Pareto front (PF) can be found. In [31] and [32], different search approaches are compared in a defense-related application and the four-bar mechanism speed regulation problem, respectively. They provide some insights about the importance of the search approach to improve the Pareto front.…”

Section: Taking Into Consideration the Investigation Reported Inmentioning

confidence: 99%

“…In MOEA/ D-DE, the population is evolved through a Differential Evolution (DE) [49] operator and mutation is done using PM (with p m and η m ). The crossover between individuals in the weights' neighborhood of each individual is worked out through the DE/rand/1/bin variant with a crossover probability C r [32].…”

Section: E Moea/dmentioning

confidence: 99%

“…Next, solutions that belong to the last removed PF are chosen considering their closeness to the less crowded reference point regions and added to the combined population to complete the N individuals [32]. Finally, the population of N individuals is used as the new parent population.…”

Section: F Nsga-iiimentioning

confidence: 99%

“…The above promotes the convergence of the obtained solutions to the true PF and also the diversity of solutions. On the other hand, unlike the HV-MODE in [32], which is convenient for online optimization problems (where the convergence time is a crucial factor, and a reduced number of generations is required for the dynamic environment), the MODE-HVR is focused on offline optimization. In the case of the proposed MODE-HVR, the reinforcement of the diversity and convergence depends on the cumulative nondominated solutions created through generations, while in HV-MODE, they rely on the fulfillment of a percentage of nondominated solutions in the external archive (it does not rely on the generation accumulation).…”

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confidence: 99%

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Optimum Nozzle Design for a Viscous Liquid by Using Multi-Objective Search Approaches

et al. 2020

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This work deals with the problem of a nozzle design addressed through a multi-objective optimization strategy where governing equations of fluid dynamics model the phenomena. The liquid flow rate and the nozzle length are considered as the design criteria. Two Differential Evolution variants are proposed to obtain a set of design configurations that presents numerous and different synergies between the design criteria. The first variant is based on the Hypervolume performance metric (MODE-HVR) and the second one includes the-dominance concept (MODE-HV R). A comparative study is performed with other optimizers from well-established search approaches for multi-objective optimization such as algorithms based on Pareto dominance (NSGA-II and SPEA2), decomposition (MOEA/D), metric (SMS-EMOA) and hybrid (NSGA-III). Based on the Spacing and Hypervolume indicators of the obtained Pareto fronts, the proposed optimization algorithms can provide more design solutions, promoting the reconfigurability (synergy) in the nozzle design. Hence, the multi-objective design strategy allows the designer to have a wide range of solutions and to choose the most suitable one for a particular application, compared with a traditional design where both design criteria are considered as a single aggregate function. INDEX TERMS Optimum nozzle design, multi-objective optimization, multi-objective search approaches, optimization.

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Section: Taking Into Consideration the Investigation Reported Inmentioning

confidence: 99%

Section: E Moea/dmentioning

confidence: 99%

Section: F Nsga-iiimentioning

confidence: 99%

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confidence: 99%

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Optimum Nozzle Design for a Viscous Liquid by Using Multi-Objective Search Approaches

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“…In [37], the (1+1)-Dynamic Evolution Strategy has been used to find the PI controller gains for a one-degree-of-freedom robotic mechanism. The use of different multi-objective evolutionary algorithms has been analyzed in the controller tuning of the four-bar mechanism [38].…”

Section: Introductionmentioning

confidence: 99%

Novel Asynchronous Activation of the Bio-Inspired Adaptive Tuning in the Speed Controller: Study Case in DC Motors

2021

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The fusion of bio-inspired algorithms into online controller tuning (adaptive controller tuning) is one of the main topics in Intelligent Control. One crucial issue is to reduce the times that the tuning process performs over time. In this work, a novel Asynchronous Adaptive Controller Tuning (AACT) approach is proposed to reduce the number of tuning process activations, and hence, this promotes resource savings in the overall computational cost for the tuning process. In this approach, an event function is designed to determine the control parameter update where the use of identification and predictive stages set the current control parameters. Furthermore, an elitist initialization in the differential evolution algorithm is also incorporated for solving the optimization problems at each stage. The speed regulation of the DC motor under disturbances is the study case in the ACCT approach. Comparative results with state-of-theart bio-inspired algorithms in control tuning reveal in the AACT approach that the elitist initialization in differential evolution notably benefits the controller performance. Moreover, the comparative results with the Synchronous Adaptive Controller Tuning (SACT) approach show that the proposal reduces 61% the tuning process computation frequency with a similar speed regulation performance when disturbances appear.INDEX TERMS Optimal controller tuning, DC motor, Event based tuning, Bio-inspired algorithm.

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Privacy Preserving Algorithms for Distributed Online Learning

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Wireless Networks

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Adaptive Controller Tuning Method Based on Online Multiobjective Optimization: A Case Study of the Four-Bar Mechanism

Cited by 19 publications

References 33 publications

Optimum Nozzle Design for a Viscous Liquid by Using Multi-Objective Search Approaches

Optimum Nozzle Design for a Viscous Liquid by Using Multi-Objective Search Approaches

Novel Asynchronous Activation of the Bio-Inspired Adaptive Tuning in the Speed Controller: Study Case in DC Motors

Privacy Preserving Algorithms for Distributed Online Learning

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