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Many methods have been developed for controlling non-linear systems, which include controller design based on linearised models, adaptive control, and non-linear model predictive control. The objective of this project is to investigate the performance of a new method developed by Skogestad and co-workers (Zotică et al., 2020) that uses transform…

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Transformed Manipulated Variables for Linearisation, Decoupling, and Disturbance Rejection

Project by: Jacobus George van Dyk ([email protected], SU number: 20790147)

Project supervised by: Prof Steven M. Bradshaw ([email protected])

Department of Process Engineering, Stellenbosch University, 2022.

Project Description and Objectives:

Many methods have been developed for controlling non-linear systems, which include controller design based on linearised models, adaptive control, and non-linear model predictive control. The objective of this project is to investigate the performance of a new method developed by Skogestad and co-workers (Zotică et al., 2020) that uses transformed manipulated variables for linearisation, decoupling, and perfect steady state disturbance rejection.

Project Outcome and Deliverables

The following requirements must be met for the project to be considered successful:

• Successful dynamic modelling of two non-linear processes.

• Successful implementation of transformed manipulated variable control on the processes.

• Successful investigation of the performance of the novel control strategy and appropriate comparison with other methods.

Project Characteristics and Requirements

  1. Applicability to Chemical Engineering:

Dynamic modelling and control of nonlinear processes are significant chemical engineering activities.

  1. References:

• Cristina Zotică et al., Transformed manipulated variables for linearization, decoupling and disturbance rejection, IFAC PapersOnLine 53-2 (2020) 4052–4057.

• Henson, M.A. and Seborg, D.E. (1991). Critique of exact linearization strategies for process control. Journal of Process Control, 1(3), 122–139.

• Balchen, J.G., Lie, B., and Solberg, I. (1988). Internal Decoupling in Non-Linear Process Control. Modeling, Identification and Control, 9(9), 137–148.

  1. Infrastructure, Resources, and Funding:

None required. MATLAB is available to all students.

Queries:

George van Dyk - [email protected]

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Many methods have been developed for controlling non-linear systems, which include controller design based on linearised models, adaptive control, and non-linear model predictive control. The objective of this project is to investigate the performance of a new method developed by Skogestad and co-workers (Zotică et al., 2020) that uses transform…

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