Increased Performance of a Hybrid Optimizer for Simulation Based Controller Parameterization

• Autorzy: Neugebauer R. , Hipp K. , Hellmich A. , Schlegel H.
• Języki publikacji: EN

Abstrakty

EN

The controller parameterization is often carried out by applying basic empirical formulas within an integrated automatic design. Hence, the determined settings are often insufficiently verified by the resulting system behavior. In this paper an approach for the controller parameterization by using methods of simulation based optimization is presented. This enables the user to define specific restrictions e.g. the complementary sensitivity function (CSF) to influence the dynamic behavior of the control loop. Furthermore it is possible to choose alternative optimization criteria. A main influence factor for practical offline as well as controller internal optimization methods is the execution time, which can be reduced by applying a hybrid optimization strategy. Thus, the paper presents a performance comparison between the straight global Particle-Swarm-Optimization (PSO) algorithm and the combination of the global PSO with the local optimization algorithm of Nelder-Mead (NM) to a hybrid optimizer (HO) based on examples.

Słowa kluczowe

EN

controller parameterization; simulation based optimization; particle swarm optimization (PSO); Nelder-Mead

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2012
• Tom: Vol. 6, No. 1
• Strony: 42--45
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Neugebauer R.

autor

Hipp K.

autor

Hellmich A.

autor

Schlegel H.

• Chemnitz University of Technology, Faculty of Mechanical Engineering, Institute for Machine Tools and Production Processes, Reichenhainer Str. 70, 09126 Chemnitz, Germany,

Bibliografia

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