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QFT Based Gain-Scheduling Control Design for Linear Time-Varying Systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Choil, Jae Weon Im, Ki Hong Zhu, Jim |
| Copyright Year | 2004 |
| Abstract | Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control and gain-scheduling have been applied to control design for the LTV systems. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification in frozen time sense. However, if these methods are a p plied to the approximated linear time-invariant (LTI) plants with large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed gain-scheduling control design based on QFT for LTV systems with bounded time-varying parameters. To generate a continuous and smooth gain-scheduling function, multi-layer neural network is used. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.computer.org/csdl/proceedings/cdc/2000/6638/05/00914678.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Approximation algorithm Artificial neural network Biological Neural Networks Control engineering Gain Layer (electronics) Linear time-invariant theory Numerous Robust control Scheduling (computing) Scheduling - HL7 Publishing Domain Specification Time complexity Time-invariant system Time-scale calculus |
| Content Type | Text |
| Resource Type | Article |
