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Content archived on 2024-06-11

Fuzzy switching strategies for multiple model-based adaptive control

Objective



Research objectives and content
An area of particular industrial interest is the control of complex systems, operating in mulaple environments. In these cases the need for multiple models arises naturally, since a different mathematical model may be needed to represent the behavior of the plant in each environment. I propose the implementation of a fuzzy logic controller for performing the switching and tuning between the available controllers associated to the models. The fuzzy logic controller evaluates the inputs using the fuzzy logic rules and decides which model reflects the current state of the system, and then selects the corresponding controller at each instant. If none of the models is able to provide a satisfactory representation of the current state of the system, the fuzzy switching system may combine, and tune, the output of more than one controller in order to generate the control signal. The approach is extremely useful for single input single output systems, but it is likely to show all its potential in the case of complex multivariable processes, allowing the decomposition of the control problem in manageable subproblems. Thus the proposed research will provide new, alternative methods for studying, analyzing and controlling multivariable systems, which will be integrated in the FAMIMO LTR European Project coordinated by IRIDIA. Expected results of this project include the the development of a novel approach for controller which will enable efficient exploitation of the principle of hybridization, and facilitate simpler, more robust, plant controllers. This will result in a reduction of the complexity of the system allowing the efficient control of a large class of dynamical systems operating in rapidly time-varying environments. Training content (objective, benefit and expected impact)
The development of this research project will present many training aspects. The main ones include the development of research skills in both theoretical and applied scientific issues; gaining a detailed knowledge of an interdisciplinary emerging field of research; developing competence in applying various control techniques in several areas where control is needed; improving teamwork abilities in a high level expertise environment;experience of researching as a member of an international scientific community; contributing to the success of FAMIMO project proposing alternatives approaches;improvement of programming experience and skills; experience of living in another country of EU and improvement of the candidate command of French.The objective of the training is to provide a solid follow up point for further research activity in an academic or industrial context situated in any of the member state of the EU.
Links with industry / industrial relevance (22)
The proposed research project has both scientific importance in the field of fuzzy logic and a very strong application content which may lead to the development of a new generation of controllers, implementing multiple models, which could be applied in many areas. It is probable that the main examples will be found in process, aircraft, and car control, but the model may find useful implementations in pattern recognition applications(such as speech and character recognition), electrical drives, and financial market forecasting. In particular Siemens Automotive, one of the partners of the FAMIMO project, will be immediately able to take advantage of the results.

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Topic(s)

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Funding Scheme

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RGI - Research grants (individual fellowships)

Coordinator

Université Libre de Bruxelles
EU contribution
No data
Address
87,Avenue A. Buyl
1050 Bruxelles
Belgium

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Total cost

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Participants (1)

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