Algorithms for PID Controller 2019
This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Special Issue Information
Dear Colleagues,
The conventional PID (Proportional–Integral–Derivative) controllers are most widely used in industrial applications because of their simple, robust, cheap, and good performances. To date, the PID control performance remains limited. The requirements for control precision have become higher, and the real systems have become more complex, including higher order, time-delayed linear, nonlinear systems, and systems without a mathematical model and uncertainties. The goal of control algorithms is to determine the optimal PID controller parameters. Practically, all PID controllers made today are based on microprocessors. This has created opportunities to provide additional features, such as automatic tuning, gain scheduling, and continuous adaptation. In addition to the conventional approaches such as the Lyapunov approach and PID control system analysis, there are more advanced and intelligent algorithms for PID tuning methods and metaheuristic algorithms, such as the Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Big Bang–Big Crunch, etc. In addition, sophisticated control strategies, such as predictive control, self-tuning methods, fuzzy and neural algorithms, are designed to overcome the problems associated with the regulation of PID controller gains.
Prof. Dr. Anastasios Dounis
Guest Editor
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Keywords
- Evolutionary PID control
- Adaptive fuzzy PID control
- Robust PID algorithms
- Uncertainty of PID algorithm
- Predictive control
- Interval type-2 fuzzy PID controller
- Reinforcement learning algorithm
- Sliding mode
- Lyapunov approach
- Kalman filtering
- Implementations
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Published Papers
Algorithms - ISSN 1999-4893