Design Control Systems Using Modern Technologies and Techniques
Process control has increased in importance in the process industries, driven by global competition, rapidly changing economic conditions, more stringent environmental and safety regulations, and the need for more flexible yet more complex processes to manufacture high value-added products.
This long-awaited second edition of Dale Seborg, Thomas Edgar, and Duncan Mellichamp's PROCESS DYNAMIC AND CONTROL reflects recent changes and advances in process control theory and technology. The authors have added new topics, and enhanced the presentation with a large number of new exercises and examples, many of which utilize MATLAB and Simulink.
New and expanded topics includes:
* Mathematical modeling of chemical processes
* Developing dynamic models from process data
* Control system design
* Process safety and process control
* Enhanced single-loop control
* Digital control
* Multiloop and multivariable control
* Real-time optimization
* Model predictive control
* Process monitoring
* Batch process control
* Plantwide control
* Applications to semiconductor manufacturing and bioprocessing
* Control hardware and software
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Design Control Systems Using Modern Technologies and Techniques
Process control has increased in importance in the process industries, driven by global competition, rapidly changing economic conditions, more stringent environmental and safety regulations, and the need for more flexible yet more complex processes to manufacture high value-added products.
This long-awaited second edition of Dale Seborg, Thomas Edgar, and Duncan Mellichamp's PROCESS DYNAMIC AND CONTROL reflects recent changes and advances in process control theory and technology. The authors have added new topics, and enhanced the presentation with a large number of new exercises and examples, many of which utilize MATLAB and Simulink.
New and expanded topics includes:
* Mathematical modeling of chemical processes
* Developing dynamic models from process data
* Control system design
* Process safety and process control
* Enhanced single-loop control
* Digital control
* Multiloop and multivariable control
* Real-time optimization
* Model predictive control
* Process monitoring
* Batch process control
* Plantwide control
* Applications to semiconductor manufacturing and bioprocessing
* Control hardware and software
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