| Project/Area Number |
05650411
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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 | Kyushu Institute of Technology |
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Principal Investigator |
FUJII Takao Kyushu Inst.of Tech., Dept.Control Engg.&Sci., Professor, 情報工学部, 教授 (70029510)
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| Co-Investigator(Kenkyū-buntansha) |
TSUJINO Taro Kyushu Inst.of Tech., Dept.Control Engg.&Sci., Research Associate, 情報工学部, 助手 (00227406)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1994: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1993: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Control of a magnetic levitation system / Robust control / Multivariable control / Decoupling control / Servo system / Optimal control / Inverse problem of optimal control / ILQ design method |
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| Research Abstract |
The purpose of this research is that we develop a design method of robust servo systems from the viewpoint of the inverse problem and apply it to a control problem of a magnetic levitation system in order to clarify its effectiveness and its problem and furthermore improve the method if necessary. In order to achieve this purpose, we applied the Robust ILQ design method developed by us to the control problem of the magnetic levitation system with a Y shape iron plate as a levitation vehicle last year. As a result we succeeded in a control experiment of its very stable levitation and attitude with an application of step change in a set point. We, however, found it that an unstable motion happened due to the modelling errors which was arisen from nonlinearity and modes of vibration neglected in modelling when an impulse disturbance was applied. We first try to solve this problem this year and take measures against two kinds of modelling errors. Against the former modelling error we made
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a model of the magnetic levitation system by using exact linearization technique, which is useful as was pointed out recently, instead of approximate linearization technique and then design a control system and did a control experiment. As a result its performance was a little improved. The unstable motion caused by an impulse disturbance, however, was not suppressed. On the other hand against the former modelling error we use H_* control theory, which can take it into account in the control system design, and design the control system. Then a controller was designed in order to suppress the unstable motion caused by an impulse desturbance with an application of small step change in a set point. It, however, could not be designed with an application of large step change in a set point. In order to grasp the effectiveness of exact linearization technique correctly, we did a similar levitation control experiment with a very rigid barbel shape levitation vehicle and verified that a simulation result and an experimental result based on the exactly linearized model was more consistent than that based on the linear approximation model. Based on the above-mentioned information we extended the ILQ optimal servo system design method this year. So far this design method have taken only a step reference input into consideration and a controller obtained by using the method therefore had low order and it prevented the performance of the control system from being improved. Hence, we generalized ILQ optimal servo design method with respect to the reference input and developed its CAD this year. Less
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