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Multi-loop decentralized PID control based on covariance control criteria: an LMI approach
1Department of Chemical & Materials Engineering, University of Alberta, Edmonton, Alberta, Canada T6G2G6.
ISA Transactions
|March 6, 2004
Summary
This study presents a new computational algorithm for designing multi-loop PID controllers. The algorithm ensures process variables meet generalized covariance constraints, even with stable or random-walk disturbances.
Area of Science:
- Control Engineering
- Industrial Automation
- Process Control
Background:
- Proportional-Integral-Derivative (PID) control is a cornerstone of industrial automation.
- Designing decentralized or multi-loop PID controllers for multivariable systems remains a significant challenge.
- Simultaneously meeting multiple performance objectives, like covariance constraints, is complex.
Purpose of the Study:
- To develop a systematic method for designing multi-loop PID controllers.
- To ensure process variables satisfy generalized covariance constraints.
- To address control challenges in processes with both stable and random-walk disturbances.
Main Methods:
- A convergent computational algorithm is proposed for multi-loop PID controller design.
- The algorithm is specifically developed for processes with stable disturbances.
- The method is extended to accommodate processes exhibiting random-walk disturbances.
Main Results:
- The proposed algorithm successfully calculates multi-loop PID controllers.
- The controllers enable process variables to meet generalized covariance constraints.
- The algorithm's effectiveness is demonstrated through various simulation examples.
Conclusions:
- A feasible and convergent computational algorithm for designing multi-loop PID controllers has been developed.
- The method provides a systematic approach to satisfy generalized covariance constraints in multivariable processes.
- The algorithm offers a practical solution for complex industrial control applications with different disturbance types.