| Budget Amount *help |
¥7,800,000 (Direct Cost: ¥7,800,000)
Fiscal Year 2006: ¥3,000,000 (Direct Cost: ¥3,000,000)
Fiscal Year 2005: ¥4,800,000 (Direct Cost: ¥4,800,000)
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| Research Abstract |
Recently, the improvement of production quality and the reduction of the production cost have been further advanced in process industries, and the control systems play an important role in such a situation. In particular, the properties of process systems have been frequently changed due to the change of operating condition and/or nonlinearity of the systems. Therefore, it is necessary to readjust the control parameters corresponding to the change of system properties in order to maintain the desired control performance. As one of such strategies, the self-tuning control has been proposed. However, it is said that the recursive least squares method is not effective in nonlinear systems. By the way, for the purpose of maintaining the safety or the productivity of industrial process, the researches on control performance assessment(CPA) have been paid to attention in last decade. In process systems, it is most important problem to unify the CPA and the controller design in industries. In this research project, a design scheme of performance-adaptive PID controllers has been newly proposed. According to the proposed control scheme, the modeling performance is firstly evaluated, and system parameters are identified using the data-driven system identification which is effective in nonlinear systems, if the modeling performance is not good. In addition, PID parameters are adjusted based on the estimates so that the control performance satisfies the desired performance determined in advance. Concretely, the self-tuning PID control based on generalized predictive control scheme is adopted in order to tune PID parameters, and the user-specified parameter, that is, the control weighting factor which indicates the desired control performance, is chosen. The behavior of the proposed scheme has been examined by some numerical simulation examples and application for a real system.
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