Design Of Fuzzy PID Controller Research Articles

English

In this paper, a trajectory tracking control for a non-holonomic differential wheeled mobile robot (WMR) system is presented. A big number of investigations have been used the kinematic model of mobile robot which is a nonlinear model in nature, thus a hard task to control it. This work focuses on the design of fuzzy PID controller tuned with a firefly optimization algorithm for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller's parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with the least possible value of error. Matlab Simulation results show that a good performance and robustness of the controller. This is confirmed by the value of minimized tracking error and the smooth velocity especially concerning presence of external disturbance or change in initial position of mobile robot.

Design a Fuzzy PID Controller for Trajectory Tracking of Mobile Robot

In this paper, a trajectory tracking control for a non-holonomic differential wheeled mobile robot (WMR) system is presented. A big number of investigations have been used the kinematic model of mobile robot which is a nonlinear model in nature, thus a hard task to control it. This work focuses on the design of fuzzy PID controller tuned with a firefly optimization algorithm for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller's parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with the least possible value of error. Matlab Simulation results show that a good performance and robustness of the controller. This is confirmed by the value of minimized tracking error and the smooth velocity especially concerning presence of external disturbance or change in initial position of mobile robot.

Improved fuzzy PID controller design using predictive functional control structure

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control.

Design and Evaluation of an Optimal Fuzzy PID Controller for an Active Vehicle Suspension System

Design and Evaluation of an Optimal Fuzzy PID Controller for an Active Vehicle Suspension System

Cuckoo search algorithm based design of interval Type-2 Fuzzy PID Controller for Furuta pendulum system

The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fuzzy Membership Function (MF). Numerous experimental investigations have shown the superiority of IT2FLC over T1FLC, particularly in high level of uncertainties and nonlinearities. Nevertheless, the systematic design of IT2FLCs remains an attractive problem because of the difficulty in finding the parameters associated with IT2FLCs. In this study, a novel application of Cuckoo Search (CS) algorithm in the design of an optimized cascade Interval Type-2 Fuzzy Proportional Integral Derivative Controller (IT2FPIDC) is presented. The PID gains and the parameters of the antecedent MFs of IT2FPIDC are optimized using CS algorithm. Considering the higher number of parameters to be optimized in cascade IT2FPIDC, the CS method was employed due to its high convergence speed and less computational cost. The proposed CS based cascade optimized IT2FPIDC is compared with CS-based Type-1 Fuzzy Proportional Integral Derivative Controller (T1FPIDC). The present research presents a new application of proposed CS based cascade optimized IT2FPIDC for the balancing control and trajectory tracking control of the Furuta pendulum (FP) which is a nonlinear, non-minimum phase and unstable system. Furthermore, the disturbance rejection ability of the proposed controller is analyzed. The proposed control strategies are evaluated on FP produced by Quanser through numerous experimentations in the real world as well as simulation. The performance characteristic considered for these controllers are settling time (ts), steady state error (Ess), rise time (tr) and maximum overshoot (Mp). Both the simulation and real world experiments results demonstrated the robustness and effectiveness of the proposed CS based IT2FPIDC with respect to parameter variation, noise effects and load disturbances, with an improved performance of 27.1%, 5.7% and 20.8% for tr, ts and Mp respectively over its CS based T1FPIDC counterpart.

Design, Implementation and Evaluation of Fuzzy Logic and PID Controllers for Fuel Cell Systems

Design, Implementation and Evaluation of Fuzzy Logic and PID Controllers for Fuel Cell Systems

DESIGN OF A FUZZY-PID CONTROLLER FOR A NANOSCALE X-Y PLATFORM

A fuzzy-PID controller design was proposed in this paper for a nanoscale platform positioning system. The target nanoscale X-Y platform is mounted on a pantograph mechanism and restricts the rotation by two small sliders; the device is driven by a traditional X-Y platform with common precision. The goal of this study is to drive the target platform’s movement in the region of 5 mm × 5 mm for the positioning, with repeated positioning accuracy error less than 200 nm by the traditional X-Y platform. Due to the different PID parameters affecting platform positioning accuracy and system response for the two axes, the fuzzy-PID controller will train to fit the mechanism to promote the positioning precision and path control effect. The simulation and experimental results indicated that the proposed method is feasible for nano-scale micro-platform positioning.

Design and analysis of fuzzy PID controller with derivative filter for AGC in multi‐area interconnected power system

This study presents a comprehensive analytical study of a fuzzy proportional-integral-derivative (fuzzy-PID) controller with derivative filter (fuzzy-PIDF) for automatic generation control (AGC) in multi-area power system tuned by a novel hybrid local unimodal sampling-teaching learning based optimisation (LUS-TLBO) algorithm. The relevant advantage of this recommended controller is its high sensitivity to load perturbation. Initially a two area non-reheat type thermal system is considered and the gains of PIDF controller are tuned employing hybrid LUS-TLBO algorithm. The supremacy of PIDF controller is shown by comparing the results with some recently published articles. The study is further extended to design fuzzy logic based PID controller with derivative filter (fuzzy-PIDF) for AGC of the same power system employing hybrid LUS-TLBO algorithm. Supremacy of the proposed approach is shown by comparing the results with another recently published article. In addition, the work is also extended to deal with AGC issues in two area multi source hydro thermal power system using the proposed controller. Finally, it is seen that fuzzy-PIDF controller retains its supremacy over PID/PIDF/fuzzy-PID controllers. In addition to it, robustness analysis is carried out for the non-reheat two area thermal power systems by varying different parameters within the range of ±50%.

Type-2 fuzzy logic PID controller and different uncertainties design for boost DC–DC converters

The aim of this work is the synthesis of a type-2 fuzzy logic PID controller for DC–DC boost converters. Performances of the proposed controller are evaluated and compared with those of type-1 fuzzy logic PID controller using the same structure and under similar operating conditions. Simulation results showed that the type-2 fuzzy logic PID controller has better performances than those of type-1 fuzzy logic PID controller.

The Design of Fuzzy PID Controller for Networked Systems with Random Time Delay

In this paper, the nonlinear systems with time delay network control is discussed transmission delays and packet dropouts for networked control system with random time delay are analyzed. In this paper, online delay estimation method to obtain the delay value, the delay value is an input parameter of fuzzy adaptive PID controller, fuzzy PID temporal adjustment based on genetic algorithm and Particle swarm optimization algorithm to optimization objective function, three parameters of PID is adjusted Online in order to improve the system stability, through Matlab co-simulation tool True Time, the shows the fuzzy logic control system base on PSO algorithm promote reduce transmission delays and packet dropouts. The paper also shows the superiority of Fuzzy PID controllers over their traditional PID for NCS applications.

LabVIEW Based Design and Analysis of Fuzzy Logic, Sliding Mode and PID Controllers for Level Control in Split Range Plant

LabVIEW Based Design and Analysis of Fuzzy Logic, Sliding Mode and PID Controllers for Level Control in Split Range Plant

Modeling and control of autonomous underwater vehicle (AUV) in heading and depth attitude via self-adaptive fuzzy PID controller

This paper focuses on design of a new self-adaptive fuzzy PID controller based on nonlinear MIMO structure for an AUV. Complexity and highly coupled dynamics, time-variance, and difficulty in hydrodynamic modeling and simulation, complicates the AUV modeling process and the design of proper and acceptable controller. In this work, the comprehensive nonlinear model of AUV is derived through kinematics and dynamic equations and then its treatment in open-loop is verified. In proposed controller, the PID parameters are adjusted by Mamdani fuzzy rules. Combined adaptive methods and dual PID controllers can improve solving of the uncertainty challenge in the PID parameters and AUV modeling uncertainty. The simulation results indicate that developed control system is stable, competent, and efficient enough to control the AUV in tracking the two channels of heading and depth with stabilized speed. Obtained results show that the proposed controller is not only robust, but also gives excellent dynamic, stunning steady-state characteristics and robust stability compared with a classically tuned PID controller.

A Design of Fuzzy-PID Controller of Constant Temperature for Semiconductor Laser Diodes

The paper introduces two types of precise temperature controllers for high power semiconductor laser diodes. We apply a category of self-tuning parameter fuzzy-PID controller and a kind of neuronal network optimized rules fuzzy-PID controller to realize stable temperature controlling. Also we simulate this two methods using Matlab. The result proves that the new method has more superiority than traditional means, such as PID controlling, etc. And further improvement on constant temperature control will inevitably promote the reliability of LD.

The Application of Fuzzy PID Control Algorithm in Variable Frequency Speed Regulation System of Glass Edge Grinding Machine

Aiming at the deficiencies of traditional PID control algorithm, the application of Fuzzy PID control algorithm is proposed in variable frequency speed regulation system of glass edge grinding machine. The design of fuzzy PID controller is presented in the paper. The paper not only introduces the system principle and models for inverter and AC asynchronous motor but also tells the principle of Fuzzy PID Controller and its design method. A simulation model including traditional PID Controller and Fuzzy PID Controller is established in MATLAB/Simulink. Through the analysis of the difference between the two controlling outputs, the better performance of Fuzzy PID Controller in response speed, accuracy and stability is proved effectively. The result can be used as important criterion to the practical application of Fuzzy PID control algorithm.

Multiple Models Fuzzy PID Controller Design in Ship Power System

The ship power system is a complex system with time varying, nonlinear and strong coupling characters. The traditional PID controller is difficult to meet the requirements of the system.In this paper, a multiple models fuzzy PID controller is designed. Considering the different operating conditions of on-land ship power system, two excitation regulation model which respectively corresponds to a fuzzy PID controller are set up. Each time, based on the input operation condition tested, only one fuzzy PID Controller is chosen to improve the control precision. At the end, simulation results show that multiple model fuzzy PID controller is superior to the single fuzzy PID controller, which effectively improves the transient response of the system, the steady state accuracy and robustness, having good prospects for engineering applications.

Optimal fuzzy PID controller design for an active magnetic bearing system based on adaptive genetic algorithms

We propose an adaptive genetic algorithm (AGA) for the multi-objective optimisation design of a fuzzy PID controller and apply it to the control of an active magnetic bearing (AMB) system. Unlike PID controllers with fixed gains, a fuzzy PID controller is expressed in terms of fuzzy rules whose consequences employ analytical PID expressions. The PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than conventional ones. Moreover, it can be easily used to develop a precise and fast control algorithm in an optimal design. An adaptive genetic algorithm is proposed to design the fuzzy PID controller. The centres of the triangular membership functions and the PID gains for all fuzzy control rules are selected as parameters to be determined. We also present a dynamic model of an AMB system for axial motion. The simulation results of this AMB system show that a fuzzy PID controller designed using the proposed AGA has good performance.

Design and Implementation of Fuzzy PID Controller for Single Link Flexible Joint Robotic System using FPGA

Designing a Fuzzy Proportional Integral Derivative (FPID) controller that can control single link flexible joint robotic system which is nonlinear and have a complex mathematical model, led to the need of finding a way that could be efficient to hardware implementation, using Field – Programmable Gate Array FPGA (small device size, cost effective, short time to market, Reliability and Long – Term Maintenance) could solve that issue. Fuzzy Logic Controller (FLC) system is a most promising area for industrial application and by combining it with PID control algorithms features; they offer a high speed process using simple rules with the accuracy of PID tuning methods. In this paper, we have demonstrated the implementation of FPID controller using Very high speed integrated circuits Hardware Description Language (VHDL) code in FPGA, we have used Mamdani type as a FLC structure. The controller algorithm have been developed, synthesized, simulated and implemented on FPGA Spartan6, XC6SLX150T, FGG676 board.

Level control of single water tank systems using Fuzzy-PID technique

In this study, for the control of a single water tank system, a fuzzy-PID controller design technique based on a fuzzy model is investigated. For this purpose, a water tank system is linearized as a number of submodels depending on the operating point, and a fuzzy model is obtained by fuzzy combining. Each submodel is approximated as a first order time delay model, and a PID controller is designed using several existing tuning techniques. Then, through the fuzzy combination of this controller using the same method as that of the fuzzy model, a fuzzy-PID controller is designed. For the proposed technique, a simulation is performed using the fuzzy model of a water tank system, and the validity is examined by comparing its performance with that of a PID controller.

Multi-Objective Optimal Fuzzy Fractional-Order PID Controller Design

The design of the optimal fuzzy fractional-order PID controller is addressed in this work. A multi-objective genetic algorithm is proposed to design rule base and membership functions of the fuzzy logic systems. Three conflicting objective functions in both time and frequency domains have been used in Pareto design of the fuzzy fractional-order PID controller. The simulation results reveal the effectiveness of the proposed method in comparison with the results produced by the fractional-order PID controllers.

A Fuzzy PID Controller Design and Application

Control system of microcomputer controlled electro-hydraulic servo rock three triaxial test instrument adopts closed loop control and the control strategy is based on PID control. Because the conventional PID control cannot meet the control accuracy and stability of system, the intelligent fuzzy controller is introduced to realize the automatic processing in control process. The fuzzy PID controller's design procedure is given to determine the fuzzy domain, fuzzy rules, calculating the reference method and defuzzification process of membership function.