| Project/Area Number |
63550320
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Waseda University |
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Principal Investigator |
AKIZUKI Kageo Waseda Univ., School of Science & Engineering, professor,, 理工学部, 教授 (10063603)
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| Co-Investigator(Kenkyū-buntansha) |
HASHIMOTO Hiroshi Tokyo Engineering Univ., School of Engineering, Lecturer,, 工学部, 講師 (60208460)
吉江 修 東京理科大学, 理学部, 助手 (20200933)
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| Project Period (FY) |
1988 – 1990
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| Project Status |
Completed (Fiscal Year 1990)
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| Budget Amount *help |
¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 1990: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 1989: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1988: ¥700,000 (Direct Cost: ¥700,000)
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| Keywords | System Identification / Multivariable Control System / Adaptive Control / Artificial Intelligence / Logical Control / Fuzzy Control / Knowledge Acquisition / ロバスト制御 / ファジイ制御 |
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| Research Abstract |
The following five basic subsystems are constructed in this research.
1. 「Knowledge acquisition supporting system」 : This system is used as a tool for knowledge acquisition. It has functions to resister, add and revise the knowledge in easy format to use.
2. 「Identification supporting system」 : As the supporting system for identification of discrete systems, selection of estimation method, model order and sampling time are available. This system has a special point in including the evaluation of the identification results.
3. 「CAD system for control」 : This system is intended to support the design of MIMO control system. In this system many graphic functions are practically used. It has a special point in including robust design techniques.
4. 「Supervisor of adaptive control system」 : the global convergence of STC is discussed and a new STC algorithm is derived. The selection rules of design parameters are made clear by many simulations.
5. 「Control system design supporting system by knowledge base」 : For the controlled objects which are difficult to express in mathematical formulation, a knowledge base control system design supporting system is constructed. It is a learning system which acquires the knowledge for control in the process of operation. The construction of the controller, the representation of knowledge and learning are based in fuzzy theory.
These five systems are connected organically and applied to support the design of control systems according to the priori information of the object.
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