Linear Quadratic Regulator and Model Predictive Control Applied to a Four-Tank System: A Performance Comparison

Authors

  • William Oswaldo Chamorro Hernández Universidad Tecnológica Equinoccial
  • Pablo Velarde Rueda Universidad Tecnológica Equinoccial

DOI:

https://doi.org/10.29019/enfoqueute.v9n1.257

Keywords:

MPC, LQR, Optimal control, Least Square Method, Process Control, 4-Tank System

Abstract

This paper shows a comparison between two linear controllers, a PI-LQR and a Soft-Constrained MPC applied to a Four-Tank process, which main characteristics are the nonlinearities, multiple inputs and outputs coupled together and slow behavior. The model was linearized around an operating point by using an optimization method, named least square. Also, a general mathematic formulation for both controllers is presented that can be extended to any process control. All the procedure was described in detail as well as the simulation results for both controllers. To achieve a real performance comparison the experimental data were obtained under the same conditions and all the response parameters were analyzed.

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References

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Published

2018-03-30

How to Cite

Chamorro Hernández, W. O., & Velarde Rueda, P. (2018). Linear Quadratic Regulator and Model Predictive Control Applied to a Four-Tank System: A Performance Comparison. Enfoque UTE, 9(1), pp. 204 – 216. https://doi.org/10.29019/enfoqueute.v9n1.257

Issue

Section

Automation and Control, Mechatronics, Electromechanics, Automotive