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Development of mixed constrained RTDA controller for industrial applications.

B A Haseena1, K Srinivasan1

  • 1Instrumentation and Control Engineering Department, National Institute of Technology, Tiruchirappalli 620015, India.

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This study introduces a new constrained controller for complex industrial processes. The advanced Real-Time Dynamic Average (RTDA) controller effectively manages multiple variables and constraints, outperforming existing methods in simulations.

Keywords:
ConstraintsDistillation columnMIMONext generation controller

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Area of Science:

  • Control Engineering
  • Process Systems Engineering
  • Optimization Theory

Background:

  • Industrial processes frequently involve multiple-input, multiple-output (MIMO) systems with operational constraints.
  • Developing effective controllers for these constrained MIMO systems presents significant challenges in control engineering.
  • Existing control strategies may not adequately address the complexities of real-time constraint handling in dynamic industrial environments.

Purpose of the Study:

  • To develop and present a novel constrained next-generation Real-Time Dynamic Average (RTDA) controller.
  • To enable the handling of various linear inequality constraints within a multi-variable control framework.
  • To demonstrate the controller's efficacy on complex industrial process simulations.

Main Methods:

  • Formulation of a Lagrangian function for constrained optimization.
  • Solving the dual problem using Hildreth's algorithm.
  • Application of Karush-Kuhn-Tucker (KKT) conditions to solve the combined hard-soft constrained RTDA optimization problem with exact penalty functions.

Main Results:

  • Successful development of a constrained RTDA controller capable of managing linear inequality constraints in MIMO systems.
  • Demonstrated performance through simulation studies on a nonlinear Continuous Stirred-Tank Reactor (CSTR) process.
  • Validated effectiveness on the Wood and Berry distillation column benchmark process.
  • Comparative analysis showing competitive or superior performance against constrained Dynamic Matrix Control (DMC) and Generalized Predictive Control (GPC).

Conclusions:

  • The developed constrained RTDA controller offers a robust solution for managing constraints in MIMO industrial processes.
  • The controller's performance is validated through simulations on challenging industrial unit operations.
  • This approach provides a valuable advancement for optimizing and controlling complex industrial systems with stringent operational requirements.