Logic Proportional Integral Derivative Controller Research Articles

Optimal Fuzzy Logic Proportional Integral Derivative Controller Design by Bee Algorithm for Hydro-Thermal System

This paper proposes a robustness and an optimum of the fuzzy logic-proportional integral derivative (FLPID) controllers for automatic generation control (AGC) of a two area interconnected hydro-thermal system and an application of bee algorithm (BA) in order to design FLPID controllers. Traditionally, membership functions (MF) and control rules (CR) of the fuzzy logic controller (FLC) were achieved by trial and error methods of designers. To solve this problem, BA was proposed to concurrently tune PID gains, MF and CR of the FLPID controllers to minimize frequency deviations and tie-line power deviations of power system. Simulation results clearly showed that the performance and the robustness of the optimal FLPID controllers were superior to the conventional PID and the FLPID controllers in terms of settling time and overshoot.

Design of a fuzzy logic proportional integral derivative controller of direct current motor speed control

Direct current (DC) motor speed control is useful. Speed can be modified based on needs and operations. DC motors cannot control their speed. To control the DC motor’s speed, a dependable controller is needed. The DC motor speed will be controlled by a fuzzy logic proportional integral derivative controller (FLC-PID). The DC motor circuit’s electrical and mechanical components have been modeled mathematically. Ziegler-Nichols is used to tune the PID controller’s gain parameters. The FLC controller employs 3×3 membership function rules in conjunction with the MATLAB/Fuzzy Simulink toolbox. Real hardware was attached to the simulation to evaluate the DC motor speed control using the fuzzy logic PID controller. DC motors with FLC PID controllers, FLC controllers, and DC motors alone will be compared for the transient response. The DC motor with an FLC PID controller performed better in this study.

Sliding mode controller based on type-2 fuzzy logic PID for a variable speed wind turbine

In this paper, an optimal type-2 fuzzy logic proportional integral derivative controller based on sliding mode controller (IT2FL-PID-SMC) is designed for a wind turbine with variable speed. The major aim of this work is to overcome the deficiencies of the classical sliding mode controller. In this study, the sliding mode controller presented is modified; the sliding surface is replaced by the type-2 fuzzy proportional integral derivative controller. The type-2 fuzzy system is used to improve the classical sliding mode control efficiency and the robustness. The proposed (IT2FL-PID-SMC) can be used to reach strong stability as well as increase the variable speed wind turbine performance. The reliability and consistency of the proposed approach is assessed by completing simulations and analyzing comparisons with the classical SMC. The simulation results are clearly indicated the effectiveness and the validity of the proposed method, in terms of precision and time of convergence.

PID Controller Design for Cruise Control System using Particle Swarm Optimization

This paper presents a design of a Proportional-Integral-Derivative (PID) controller for automobile cruise controlsystem. The parameters of the PID controller, which are the proportional ( ), derivative ( ) , and integrator ( ), have beenselected using Particle Swarm Optimization (PSO) algorithm. In this study, the overall system performance has beencompared with other predesigned controllers (conventional PID, Fuzzy logic PID, state space, and Genetic algorithm basedPID controller). The simulation result illustrates that PSO based PID controller gives the best response in terms of settlingtime, rise time, peak time, and maximum overshot. The robustness analysis shows that the system is robust despite thedeviations in some of the system parameters.