Name
Title | ||
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Interval-model-based global optimization framework for robust stability and performance of PID controllers |
Abstract | ||
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Graphical abstractDisplay Omitted HighlightsConstrained particle swarm optimization algorithm is used to tune the parameters of a robust PID controller.The design is oriented towards robust control performance and robust stability.Various control-performance criteria can be easily implemented.Robust stability within the intervals of the uncertain parameters is ensured.Useful, computationally tractable and efficient framework based on interval models. PID controller structure is regarded as a standard in the control-engineering community and is supported by a vast range of automation hardware. Therefore, PID controllers are widely used in industrial practice. However, the problem of tuning the controller parameters has to be tackled by the control engineer and this is often not dealt with in an optimal way, resulting in poor control performance and even compromised safety. The paper proposes a framework, which involves using an interval model for describing the uncertain or variable dynamics of the process. The framework employs a particle swarm optimization algorithm for obtaining the best performing PID controller with regard to several possible criteria, but at the same time taking into account the complementary sensitivity function constraints, which ensure robustness within the bounds of the uncertain parameters' intervals. Hence, the presented approach enables a simple, computationally tractable and efficient constrained optimization solution for tuning the parameters of the controller, while considering the eventual gain, pole, zero and time-delay uncertainties defined using an interval model of the controlled process. The results provide good control performance while assuring stability within the prescribed uncertainty constraints. Furthermore, the controller performance is adequate only if the relative system perturbations are considered, as proposed in the paper. The proposed approach has been tested on various examples. The results suggest that it is a useful framework for obtaining adequate controller parameters, which ensure robust stability and favorable control performance of the closed-loop, even when considerable process uncertainties are expected. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.asoc.2015.11.046 | Applied Soft Computing |
Keywords | Field | DocType |
Robust PID controller,Parameter tuning,Interval model,Constrained particle swarm optimization,Robust stability and control performance | Particle swarm optimization,Mathematical optimization,Control theory,PID controller,Control theory,Robustness (computer science),Adaptive control,Robust control,Sensitivity (control systems),Mathematics,Constrained optimization | Journal |
Volume | Issue | ISSN |
40 | C | 1568-4946 |
Citations | PageRank | References |
4 | 0.44 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gorazd Karer | 1 | 48 | 4.17 |
| Igor Skrjanc | 2 | 354 | 52.47 |