Predictive control using multiple model networks

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Predictive control using multiple model networks

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The aim of this paper is to describe a nonlinear modelling architecture, called the local model network (LMN), which introduces transparency while offering distinct advantages for nonlinear model-based control. Simulation results for a pH neutralisation process are used to illustrate the performance benefits of LMNs for two novel nonlinear dynamic matrix control schemes. (7 pages)

Inspec keywords: predictive control; nonlinear control systems; pH control; neural nets; multivariable control systems; process control

Subjects: Control technology and theory (production); Multivariable control systems; Nonlinear control systems; Chemical variables control; Self-adjusting control systems; Industrial processes; Neural nets (theory); Chemical industry; Optimal control; Control applications in chemical and oil refining industries

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