Control of nonlinear processes operating at varioussteady states. analysis and synthesis of linear andadaptive model based control approaches
Başlık çevirisi mevcut değil.
- Tez No: 626159
- Danışmanlar: PROF. DR. DANIŞMAN YOK
- Tez Türü: Doktora
- Konular: Kimya Mühendisliği, Chemical Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2001
- Dil: İngilizce
- Üniversite: University of Houston
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 246
Özet
Control orrronlincar syslcms- ha afways becır1hc focus of proccss- industry, simply fol'“ the fact that many processes such as high purity distillation columns, highly exothermic chemical reactions, pH neutralizations, and batch systems can exhibit ”highly“ nonlinear response. If the process is only ”mildly“ nonlinear or remains in the 'vicinity' ofa nominal steady state, then the effects of nonlinearity may not be severe. However these processes may be required to operate ovcr a wide range of conditions due to ”large“ process upsets or setpoint changes. When conventional PID controllers are used to control '”highly“ nonlinear processes, the controllers must be tuned very conservatively in order to provide stable behavior over the entire range of operating conditions. However conservative controller tuning can result in serious degradation of control system performance. Thus, there are considerable incentives for developing more effective control strategies that incorporates knowledge of the nonlinear process. This incentive coınbined with continuous iınprovement in the capabilities of coınputer- control hardware and software, ınaking it feasible to ıncorporate complex nonıınear mocteıs ın pıant controı systems, encouragea a oıg ımeresı ın theory and applications of nonlinear control. However this interest lacks a smooth transition from linear control to nonlinear control applications. The questions when to use nonlinear control or when and which linear control action will be sufficient for the control ofa nonlinear process in case nonlinearities are ”mild", must be answered for the proper application of nonlinear control and linear control techniques. in this work, a methodology for the analysis and synthesis of model based linear controllers is developed, for suffıcient linear control ofa nonlinear process operating at different steady states. For the cases where linear control would not achieve desired performance, a nonlinear control technique, simultaneous model predictive control and identification (MPCI) of previous studies, is considered. MPCI, an adaptive MPC methodology, which uses convenient linear models of the process at various steady states, found by closed-loop identification by online optimization, can be an alternative to nonlinear MPC. However closed-loop theoretical properties of this technique, are missing. in this work, those theoretical properties of MPCI are established.
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