PID Controller Tuning Using Chaotic Particle Swarm Optimization Algorithm
MATLAB implementation of chaotic particle swarm optimization for PID controller parameter tuning
Genetic Algorithm-Based PID Controller Parameter Tuning Using MATLAB
Implementation of genetic algorithm for PID controller parameter optimization using MATLAB programming, applied to first-order plus time delay system control with step response simulation analysis.
Bacterial Foraging Optimization Algorithm
This optimization algorithm is designed for control parameter tuning, specifically for PID controller optimization and gain value adjustment through biologically-inspired computational methods.
BP Neural Network PID Parameter Tuning
BP neural network PID parameter tuning enables automatic adjustment of PID parameters through machine learning algorithms
MATLAB Code Implementation of Particle Swarm Optimization Algorithm
Particle Swarm Optimization Algorithm with MATLAB Source Code for PID Controller Tuning
PID Control Tuned with BG-PSO Algorithm
Implementation of PID control using the BG-PSO (Binary Grid Particle Swarm Optimization) tuning algorithm, providing a reference for learners with detailed code examples and parameter optimization techniques.
Simplex Method for PID Parameter Tuning
PID parameter tuning using simplex method in Simulink environment, where the algorithm's effectiveness heavily depends on initial value selection. Initial parameters are configured in canshu.m file.
A PID Control Tuning Method Based on BP Neural Network
MATLAB source code for PID control tuning using BP neural networks with integrated algorithm implementation