Fuzzy PID Control for DC Motor
Implementation of Fuzzy PID Control for DC Motors - A Detailed Graduation Project Study on Fuzzy Control Algorithms with Comprehensive Code Documentation for Future Reference
Spacecraft Attitude Free Motion and PID Control Simulink Simulation
Simulation of spacecraft attitude free motion and PID control implementation using Simulink
Simulation Process of DC Wind Turbine Power Generation (Using PID-Controlled Three-Phase Rectifier)
Simulation Process of DC Wind Turbine Power Generation (Using PID-Controlled Three-Phase Rectifier)
Genetic Algorithm PID Control: Implementation and Applications
Self-developed genetic algorithm PID controller with excellent simulation performance, now integrated into our company's advanced PID control systems. The implementation features population-based optimization with fitness evaluation, crossover, and mutation operations for parameter tuning.
Single Neuron PID Control Example
Example of Single Neuron PID Control for Servo Motor Speed Regulation
SIMULINK Simulation of Multivariable Single Neuron PID Control Implemented Using S-Functions
SIMULINK Simulation of Multivariable Single Neuron PID Control Implemented Using S-Functions with Code Implementation Details
MATLAB Code Implementation of PID Control with Single Neuron Adaptive Algorithm
MATLAB-based PID control program featuring single neuron adaptive PID control algorithm for intelligent system regulation
Adaptive Control Using RBF Neural Networks Integrated with PID Control
This article introduces an adaptive control methodology that combines RBF neural networks with PID control algorithms, including implementation insights and practical applications.
RBF Neural Network Tuned PID Control with Radial Basis Functions
The PID control system tuned using RBF neural networks employs a three-layer feedforward network with a single hidden layer. This network structure demonstrates local approximation capabilities and has been proven to approximate arbitrary continuous functions with any desired precision.
Compact Form Linearization and Partial Form Linearization Methods
Based on compact form linearization and partial form linearization methods, nonlinear systems can be linearized for subsequent PID controller design, with implementation considerations for control algorithm structure and parameter tuning.