A Comparative Study of Different Optimization Techniques in Modelling and Predictive Controls

This study summarizes different optimization techniques in modeling and predictive controls. Optimization plays an important role in Model Predictive Control (MPC). The optimization techniques help to evaluate the best solution to a mathematical model by comparing it with visual data. The different optimization techniques include the Polak method, Cauchy method, Newton method, Modified Newton method, Steep Decent method, David-Fletcher-Powell (DFP) method, and Momentum method. These optimization techniques can fit linear and non-linear models with n-number input variables. This can help to improve the performance of the MPC controller by addressing the challenges of the data being controlled. The solution to this problem is addressed in this study, including the mathematical modeling of optimization techniques. Simulation is conducted to verify the comparison test and model a nonlinear dynamic process. The output of the MPC controller shows a linear agreement with the open-loop test, for all the optimization techniques, with some deviation in the overshoot, rise times and settling times.

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Work Title A Comparative Study of Different Optimization Techniques in Modelling and Predictive Controls
Access
Open Access
Creators
  1. Ma'moun Abu-Ayyad
  2. Yash Lad
  3. Anilchandra Attaluri
Keyword
  1. Optimal control
  2. Nonlinear systems
License In Copyright (Rights Reserved)
Work Type Conference Proceeding
Publisher
  1. Proceedings of the ASME 2023 International Mechanical Engineering Congress and Exposition
Publication Date February 5, 2024
Publisher Identifier (DOI)
  1. https://doi.org/10.1115/imece2023-112145
Source
  1. ASME International Mechanical Engineering Congress and Exposition October 29–November 2, 2023 New Orleans, Louisiana, USA
Deposited February 25, 2024

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Version 1
published

  • Created
  • Added v006t07a084-imece2023-112145.pdf
  • Added Creator Ma'moun Abu-Ayyad
  • Added Creator Yash Lad
  • Added Creator A Attaluri
  • Published
  • Updated Source, Keyword, Publisher, and 1 more Show Changes
    Source
    • ASME International Mechanical Engineering Congress and Exposition October 29–November 2, 2023 New Orleans, Louisiana, USA
    Keyword
    • Optimal control, Nonlinear systems
    Publisher
    • ASME International Mechanical Engineering Congress and Exposition
    • Proceedings of the ASME 2023 International Mechanical Engineering Congress and Exposition
    Publication Date
    • 2023-10-30
    • 2024-02-05
  • Renamed Creator Anilchandra Attaluri Show Changes
    • A Attaluri
    • Anilchandra Attaluri
  • Updated