Process Modelling, Identification, and Control

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Process Modelling, Identification, and Control

theory and applications, which makes the book especially useful for students, practicing engineers and researchers interested in modeling and control of processes. Well written and easily understandable

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Process Identification and PID Control

Process Identification and PID Control enables students and researchers to understand the basic concepts of feedback control, process identification, autotuning as well as design and implement

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Advanced Process Identification & Control

A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover

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Modelling, Simulation and Identification

planning. New techniques in signal processing, adaptive control, non-linear system identification, multi-agent simulation, eigenvalue analysis, risk assessment, modeling of dynamic systems, finite difference

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Identification of Dynamic Systems: An Introduction with Applications

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using

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Industrial Process Identification and Control Design: Step-test and Relay-experiment-based Methods (Advances in Industrial Control)

Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay

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Modelling and Identification with Rational Orthogonal Basis Functions

Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. A model is always only

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Block-oriented Nonlinear System Identification

in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves

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Process Modelling for Control: A Unified Framework Using Standard Black-box Techniques (Advances in Industrial Control)

Many process control books focus on control design techniques, taking the construction of a process model for granted. Process Modelling for Control concentrates on the modelling steps underlying

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Subspace Methods for System Identification (Communications and Control Engineering)

for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods

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