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Model Predictive Control : Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model / by Ridong Zhang, Anke Xue, Furong Gao

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink BücherPublisher: Singapore : Springer Singapore, 2019Description: Online-Ressource (XV, 137 p. 28 illus., 25 illus. in color, online resource)ISBN:
  • 9789811300837
Subject(s): Additional physical formats: 9789811300820 | 9789811300844 | Printed edition: 9789811300820 | Printed edition: 9789811300844 DDC classification:
  • 629.8
MSC: MSC: *93-02 | 93A30 | 93C95LOC classification:
  • TJ212-225
DOI: DOI: 10.1007/978-981-13-0083-7Online resources: Summary: This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineeringSummary: Introduction -- Model Predictive Control Based on Extended State Space Model -- Predictive Functional Control Based on Extended State Space Model -- Model Predictive Control Based on Extended Non-Minimal State Space Model -- Predictive Functional Control Based on Extended Non-minimal State Space Model -- Model Predictive Control Under Constraints -- PID Control Using Extended Non-minimal State Space Model Optimization -- Closed-loop System Performance Analysis -- Model Predictive Control Performance Optimized by Genetic Algorithm -- Industrial Application -- Further Ideas on MPC and PFC Using Relaxed Constrained OptimizationPPN: PPN: 1030106193Package identifier: Produktsigel: ZDB-2-ENG | ZDB-2-INR | ZDB-2-SEB | ZDB-2-SXIT
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