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Parameter identification of induction motors using dynamic encoding algorithm for searches (DEAS)

IEEE TRANSACTIONS ON ENERGY CONVERSION 2005年第1期20卷 16-24页

作者： Kim, JW Kim, SW POSCO Tech Res Labs Elect Steel Sheet Res Grp Pohang 790785 South Korea POSTETH Div Elect & Comp Engn Pohang South Korea

In this paper, a newly developed optimization algorithm, called the dynamic encoding algorithm for searches (DEAS), is introduced and applied to the parameter identification of an induction motor for vector control and fault detection. Digital simulations are conducted on startup with no load and normal operation with load perturbations. DEAS is compared with the continuous-time prediction error method and the genetic algorithm via identification performance using the startup signals. The capability of onload identification using the proposed technique is also verified with transient signals. Consequently, DEAS is shown to locate more precise parameter values than both the compared methods especially with much faster execution time than the genetical algorithm.

关键词： dynamic encoding algorithm for searches genetic algorithm (GA) induction motor parameter identification prediction error method

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PID control design with exhaustive dynamic encoding algorithm for searches (eDEAS)

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2007年第6期5卷 691-700页

作者： Kim, Jong-Wook Kim, Sang Woo Dong A Univ Dept Elect Engn Pusan 604714 South Korea Pohang Univ Sci & Technol Div Elect & Comp Engn Pohang 790784 Gyoengbuk South Korea

This paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang's and Ho's methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.

关键词： dynamic encoding algorithm for searches gain tuning multiobjective optimization PID control

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New encoding Method of Parameter for dynamic encoding algorithm for searches (DEAS)

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2011年第9期E94A卷 1804-1816页

作者： Park, Youngsu Kim, Jong-Wook Kim, Johwan Kim, Sang Woo Pohang Univ Sci & Technol POSTETH Div Elect & Comp Engn Pohang 790784 Gyungbuk South Korea Dong A Univ Dept Elect Engn Pusan 604714 South Korea

The dynamic encoding algorithm for searches (DEAS) is a recently developed algorithm that comprises a series of global optimization methods based on variable-length binary strings that represent real variables. It has been successfully applied to various optimization problems, exhibiting outstanding search efficiency and accuracy. Because DEAS manages binary strings or matrices, the decoding rules applied to the binary strings and the algorithm's structure determine the aspects of local search. The decoding rules used thus far in DEAS have some drawbacks in terms of efficiency and mathematical analysis. This paper proposes a new decoding rule and applies it to univariate DEAS (uDEAS), validating its performance against several benchmark functions. The overall optimization results of the modified uDEAS indicate that it outperforms other meta-heuristic methods and obviously improves upon older versions of DEAS series.

关键词： coding rule global optimization dynamic encoding algorithm for searches function optimization

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