Controller Tuning with Evolutionary Multiobjective by Gilberto Reynoso Meza, Xavier Blasco Ferragud, Javier

By Gilberto Reynoso Meza, Xavier Blasco Ferragud, Javier Sanchis Saez, Juan Manuel Herrero Durá

This publication is dedicated to Multiobjective Optimization layout (MOOD) systems for controller tuning functions, through Evolutionary Multiobjective Optimization (EMO). It provides advancements in instruments, methods and directions to facilitate this approach, protecting the 3 basic steps within the approach: challenge definition, optimization and decision-making. The booklet is split into 4 components. the 1st half, basics, makes a speciality of the mandatory theoretical history and gives particular instruments for practitioners. the second one half, fundamentals, examines various easy examples in regards to the temper process for controller tuning, whereas the 3rd half, Benchmarking, demonstrates how the temper technique might be hired in different keep watch over engineering difficulties. The fourth half, purposes, is devoted to enforcing the temper approach for controller tuning in genuine processes.

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Extra resources for Controller Tuning with Evolutionary Multiobjective Optimization: A Holistic Multiobjective Optimization Design Procedure (Intelligent Systems, Control and Automation: Science and Engineering)

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3. Multicriteria decision making (MCDM) step. When the MOO process is merged with the MCDM step for a given MOP statement, it is possible to define a multiobjective optimization design (MOOD) procedure [12]. This MOOD procedure can not substitute, in all instances, an AOF approach; nevertheless, it could be helpful in complex design problems, where a close embedment of the designer is necessary. For example, where a trade-off analysis would be valuable for the DM before implementing a desired solution.

Therefore, the s-Pareto Front is built joining the design alternatives of K design concepts. In Fig. 3 two different Pareto Front approximations for two different concepts ( and respectively) are shown (Fig. 3a). In Fig. 3b, an s-Pareto Front with both design concepts is built. As remarked in [84], a comparison between design concepts is useful for the designer, because he/she will be able to identify the concepts strengths, weaknesses, limitations and drawbacks. It is also important to visualize such comparisons, and to have a quantitative measure to evaluate these strengths and weaknesses.

2 a summary on these applications is provided. The difference in the quantity of the works dedicated to fuzzy controllers and PID controllers is noticeable. Fig. 2 Summary of MOOD procedures for Fuzzy design concept. MOP refers to the number of design objectives; EMO to the algorithm implemented (or used as basis for a new one) in the optimization process. MCDM to the visualization and selection process used Process(es) References MOP EMO MCDM Aeronautical [12] 9 GA DC motor (HiL) Geological [127] 4 GA [66] 4 NSGA-II Bio-medical [37] 2 SPEA based Mechanical [80] 3 PSO HVAC system [46] 2 SPEA based Wall following [56] robot 4 SPEA based PAc Constraint violation analysis; fine tuning None According performance SCp Design alternatives comparison 2D Design alternatives/concepts comparison with other controllers.

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