Fuzzy Self-tuning PID Controller Research Articles

Self-Tuning PID Controller for Quadcopter using Fuzzy Logic

Tracking has become a necessary feature of a drone. This is due to the demand for drones, especially quadcopters, to be used for activities such as surveillance, monitoring, and filming. It is crucial to ensure the quadcopters perform the tracking with stable flight. Despite the advantages of having VTOL ability and great maneuverability, quadcopters require an effective controller to overcome their under-actuation and instability behavior. Even though a PID controller is commonly used and promising with its simple mechanism, it requires very proper tuning to ensure the stability of the system is not affected. In this paper, a simple Fuzzy algorithm is proposed to be incorporated into a PID controller to form a self-tuning Fuzzy PID controller. The Fuzzy logic controller works as the self-adjuster to the PID parameters. A mathematical model of the DJI Tello quadcopter is derived with position and attitude control loops that are designed to track a variety of trajectories with stable flight. The proposed method uses a simple architecture where the ranges of PID parameters are used as scaling factors for Fuzzy controller outputs. The results of the simulations show the tracking error performance metrics, which are IAE, ISE, and RMSE, are smaller compared to the values of the PID controller. Beyond its impact on quadcopter control, the proposed self-tuning approach holds promise for broader applications in nonlinear systems.

Improve the performance of automatic voltage regulator for power system using self-tuning fuzzy-PID controller

The optimal design of the automatic voltage regulators for a synchronous machine are positively reflected on the quality of voltage stability. This paper is concerned with the design of an AVR by adopting three control techniques. The first one was designed according to the traditional proportional integration-derived (PID) controller while the fuzzy logic was adopted in design the second powerful controller, finally the fuzzy PID controller for an automatic voltage regulator (AVR) based on fuzzy logic technology, selftuning fuzzy proportional integration-derived (STFPID) have been designed to tuning the gains of the PID controller (KP, KI and KD). To confirm the efficiency of the proposed control systems, a simulation was carried out, and the results showed that the designed STFPID controller achieves the best performance of the AVR system, and gives the preferable tracking low rise time, lower overshoot, least stetting time, minimal steady state error, and gives the ideal response against PID and fuzzy logic technology.

Intelligent VIV control of 2DOF sprung cylinder in laminar shear-thinning and shear-thickening cross-flow based on self-tuning fuzzy PID algorithm

A self-tuning fuzzy PID (ST-FPID) control scheme is implemented within a joint interactive (Matlab/Simulink/Fluent) co-simulation framework for effective two degrees of freedom (2DOF) vortex-induced vibration (VIV) control of an elastically-mounted circular cylinder in laminar cross-flow of incompressible non-Newtonian power-law fluids based on the control action of a single transverse force actuator. The model-free controller, which systematically tunes the control parameters online in real time based on given rules, is well-known to be highly advantageous over the previously employed conventional PID controllers. It is particularly capable of handling the intricate non-linear dynamic effects inherent in the complex fluid rheology of non-Newtonian flow past the cylinder in presence of unmodeled system dynamics, high parametric uncertainties, diverse operational conditions, and time-varying external disturbances and control signals. Extensive numerical simulations reveal that the complex shear-thinning and shear-thickening behaviors of fluid viscosity can substantially influence the cylinder dynamic response, applied hydrodynamic forces, and flow structure. In particular, effectiveness and high performance of the adopted ST-FPID control strategy in substantial suppression of the high amplitude coupled 2DOF VIV of the elastically-mounted cylinder at selected critical reduced velocities in the lock-in region are established for a wide range of power-law index parameters (e.g., up to 83% reduction in RMS value of cylinder cross-flow displacement and up to 35% reduction in RMS value of cylinder in-line displacement for n=1and U* = 5 at Re = 100). Also, the vigorous action of the error-driven ST-FPID controller in forcing the high strength vortex shedding patterns of the uncontrolled cylinder out of the lock-in condition into the classical von Kármán vortex street of 2S-type mode of moderately weaker strengths is verified.

2-DoF Self-tuning Fuzzy PID Controller for Under-actuated Inverted Pendulum System with Uncertainties in Model

2-DoF Self-tuning Fuzzy PID Controller for Under-actuated Inverted Pendulum System with Uncertainties in Model

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

—Fuzzy Logic controller is one of the popular techniques in control system. However, the accuracy depends on numbers and the design of membership functions. Further, the output does not always fulfill specific design requirements. In this study, Fuzzy PID controller with first-order reference model had been designed and evaluated. The proposed new structure is able to guide fuzzy mechanism to produce desired output response as specified by the first-order model such as the time constant, rise time and settling time. The study was implemented on a ball and beam system to control the position of the ball while rolling on a beam. The control of a ball and beam system is challenging because it is an open-loop unstable system as the ball will continuously moves on the beam without control. The study also compares the results acquired from Fuzzy PID and Fuzzy PI plus PD against the proposed Fuzzy PID with first-order reference model controller. The evaluation covers for a pole starting from 0 until 1.0 for the first-order model. As a results, the proposed controller is able to produce an output response as specified where the fastest response was acquired when pole is set to 0.9. Whereas the Fuzzy PID and Fuzzy PI plus PD always produce the same transient response during step input test.

Active Vibration Control for the Mitigation of Wheel Squeal Noise Based on a Fuzzy Self-Tuning PID Controller

The wheel squeal noise of a train is often made when it passes a tight curve. The noise annoys the passengers and the people living close to railway tracks. According to the research background, wheel vibration, as a result of unstable contact force, is the main source of wheel squeal noise. This study presents a novel method to reduce wheel squeal noise based on the active vibration control of wheels and the use of piezoelectric actuators attached to wheel treads. The proposed method is implemented in an experimentally validated time model involving the linear dynamics of wheel and track and nonlinear contact forces. Then, the model is modified to enhance the effect of the piezoelectric actuators. The relationship between the momentum and the voltage applied to the piezoelectric patch is also considered in modeling. To determine the amplitude and the direction of the applied voltage, a feedback controller is designed based on the fuzzy self-tuning PID controller scheme. This controller is similar to the conventional PID controller, but its coefficients are tuned by the fuzzy tuning mechanism according to the wheel response. The results show that the proposed method is capable of suppressing wheel squeal noise, especially in high frequencies. Furthermore, it is as applicable to worn wheels as to new ones.

Self-tuning Fuzzy PID Controller Design and Energy Management in DC Microgrid: Standalone and Grid Connected Mode

This paper presents a control system and energy management strategy with a standalone and grid-connected mode in the microgrid. The microgrid is energized by distributed generation system of a photovoltaic panel, wind turbine and lithium-ion batteries. In this paper, the controller structure for regulating the voltage regulation in this microgrid consisting of renewable energy sources and battery system is covered. Overshoot, rise time, settling performances of designed self-tuning fuzzy proportional-integral-derivative controller and conventional proportional-integral-derivative controller examined comparatively. In addition, an energy management system has been proposed for loads which fed in the microgrid. Here, the aim is to make maximum use of renewable energy sources as much as possible, to maintaining voltage regulation and to ensure continuity in the feeding of the critical load. The system switches between the standalone and grid-connected modes if necessary. A model of the microgrid's dynamic behavior was constructed and it is simulated in the MATLAB®/Simulink environment. The results show that despite the changes in the production and load side of the grid, voltage and frequency oscillations are stabilized within a short time and allowed tolerance limits.

Investigation into the Electrohydraulic Synchronous Motion Control of a Thrust System for a Tunnel Boring Machine

The thrust system of a tunnel boring machine plays a crucial role by driving the machine ahead and supporting the gripper shoes stably. A thrust hydraulic control system, assembled with a proportional flow control valve and a pressure relief valve, is established with system operating parameters. The mathematical model of a thrust electrohydraulic system is presented. To improve the control characteristics of the thrust system, a self-tuning fuzzy PID controller was introduced in synchronization motion control situations. To attain the best control parameters, three synchronization motion control systems were used to control the thrust propel cylinders. Tests on a Ø2.5 m scaled TBM test rig were carried out to verify the capabilities of the ISCS, SRSCS and CRSCS. Comparative tests were conducted, and the results showed that the thrust system adopting SRSCS achieved the least oscillation and the quickest response. The steady-state displacement error decreased by about 33.3% in contrast to the ISCS and CRSCS.

Performance Analysis of Electro-Hydraulic Thrust System of TBM Based on Fuzzy PID Controller

The tunnel boring machine (TBM) is widely used in tunnel construction projects. The thrust system plays a crucial role to drive the machine ahead and support gripper shoes stably while tunneling. More and more attention has been paid to the pressure and velocity regulation efficiency as the TBM advances in complex rock conditions to ensure the stabilization of the tunneling process. A thrust hydraulic control system, assembled with a proportional pressure reducing valve, is established with system operating parameters. The mathematical model of the thrust electro-hydraulic system is revealed. To improve the control characteristics of the thrust system, a self-tuning fuzzy PID controller is introduced in the pressure and velocity regulation procedures. After that, tests on a Φ2.5 m scaled TBM test rig are carried out. The test results show that the thrust system adopting the fuzzy PID controller results in less oscillation and a smoother regulation process. It takes less time to reach the target goal of pressure regulation with less vibration during the pressure regenerating periods, and both systems of conventional PID controller and fuzzy PID controller are qualified in velocity regulation movements. The proposed control methods show better benefits in reduction of vibrations and shorter time of regulation to stable conditions, which extends the machine’s life and affects the acceleration of the tunneling process.

Research on system simulation based on fuzzy self-tuning

This paper introduces the principle of fuzzy control. On this basis, a fuzzy self-tuning PID controller is designed to the requirements of SRD system. The fuzzy self-tuning PID controller is introduced into the switched reluctance motor speed regulation system, the switched reluctance motor speed regulation system based on fuzzy self-tuning PID is simulated and compared with the conventional PID switched reluctance motor speed regulation system. The comparison results show that the application of fuzzy self-tuning PID controller in the switched reluctance motor speed regulation system can make the speed regulation system obtain good dynamic Static performance.

Control System and Algorithm of Sewage Treatment Plant Based on Artificial Intelligence

With the improvement of people’s awareness of environmental protection in recent years, the related problems of water pollution treatment have gradually come into people’s view. As the source of life, water accounts for a huge proportion in our lives, but at the same time, water pollution is quietly spreading in places we don’t know. The continuous discharge of heavy industrial wastewater, agricultural wastewater and domestic sewage leads to increasingly serious water pollution. Sewage treatment(ST) is imperative, and its social benefits are huge, but the corresponding cost is high, and the return on investment is low. Traditional ST methods can not load large-scale ST. How to carry out ST based on artificial intelligence(AI), build ST plant control system, and make ST enter the era of automation is the problem to be solved. The purpose of this paper is to put forward the reform of control system for ST plant based on AI, apply AI into ST, and realize the automation and precision of ST plant. This paper mainly uses the fuzzy self-tuning PID control system algorithm, through the analysis of ST control object, analysis of fuzzy self-tuning PID controller design to complete the ST control system settings. In this paper, the literature review method and data analysis method are used. By collecting relevant data, the control system of ST plant is constructed to simulate ST, and the real-time data of ST is analyzed. The traditional PID control and fuzzy self-tuning PID control are compared. The experimental results show that the wastewater treatment plant system based on AI input, in the aspect of wastewater treatment, the concentration of COD and BOD in the treated wastewater are reduced by a certain proportion, the dissolved oxygen content in the wastewater reaches about 2.0mg/l, which meets the national discharge standard, and its rising time is reduced to 25 seconds, and the adjustment time is saved by 50 seconds.

An intelligent self-tuning fuzzy-PID controller to coupled tank liquid level system

An intelligent self-tuning fuzzy-PID controller to coupled tank liquid level system

Optimization of DC motor speed control based on fuzzy logic-PID controller

In this paper the PID controller and the Fuzzy Logic Controller (FLC) are used to control the speed of separately excited DC motors. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to Fuzzy Logic rules. The FLC cotroller is designed according to fuzzy rules so that the system is fundamentally robust. Twenty-five fuzzy rules for self-tuning of each parameter of the PID controller are considered. The FLC has two inputs; the first one is the motor speed error (the difference between the reference and actual speed) and the second one is a change in the speed error (speed error derivative). The output of the FLC, i.e. the parameters of the PID controller, are used to control the speed of the separately excited DC Motor. This study shows that the precisiom feature of the PID controllers and the flexibllity feature of the fuzzy controller are presented in the fuzzy self-tuning PID controller. The fuzzy self – tuning approach implemented on the conventional PID structure improved the dynamic and static response of the system. The salient features of both conventional and fuzzy self-tuning controller outputs are explored by simulation using MATLAB. The simulation results demonstrate that the proposed self-tuned PID controller i.plementd a good dynamic behavior of the DC motor i.e. perfect speed tracking with a settling time, minimum overshoot and minimum steady state errorws.

Comparative study on control effect of permanent magnet synchronous motor based on Fuzzy PID control and BP neural network PID control

Aiming at the problems of low control precision, poor anti-interference ability and poor stability of traditional PID controller, the improvement effect of fuzzy control and BP neural network in closed-loop control of PMSM is compared. In the case of variable speed and variable load, the stability, real-time, anti disturbance and robustness of PMSM system with traditional PID controller, fuzzy self-tuning PID controller and BP neural network PID controller as speed regulator are simulated and analyzed. The simulation results show that the fuzzy self-tuning PID controller has more advantages in the response speed of the system, and can make the system quickly recover to the initial state in case of sudden change. The BP neural network PID controller can ensure the relative stability of the system is better, and can restrain the sudden fluctuation.

Research on Efficient and Intelligent Regulation of Nutrients in Protected Soilless Culture

Green plants can effectively purify the air, release negative ions, and form a green field of vision to promote human physical and mental health. Nowadays, with the acceleration of the pace of life and the increase in the pressure of life, people do not have enough time and energy to take care of plants grown indoors in homes. Plants in large office places need to hire professionals to plant them. Raw intelligent control of flower pots can reduce energy consumption, save resources, and realize a smart life of health, environmental protection and low-carbon energy saving. At present, the effective combination of smart flowerpots and the Internet of Things makes smart flowerpots more distinctive and more obvious than traditional flowerpots. The purpose of this article is to study the efficient and intelligent regulation of nutrients in protected soil-less cultivation. In terms of methods, this paper first proposes fuzzy control and fuzzy self-tuning PID control. When the PID parameters of temperature and humidity are controlled by this control system, fuzzy rules, fuzzy reasoning and non-fuzzy processes are also used. In the soil-less cultivation control system, when the humidity in the greenhouse is too low for plant growth, you can choose to adjust the humidity in the greenhouse by starting the spray device or natural ventilation. As for the nutrient liquid level sensor, a light-weight, convenient, simple-to-use, and highly cost-effective water level recognition sensor is manufactured using the characteristics of liquid conductivity. In terms of experiments, between traditional soil-grown lettuce and container-less cabin-grown lettuce under the intelligent control system of soil-less cultivation yields comparative data and results. It is found that intelligent soilless cultivation is superior to traditional soil cultivation in terms planting effects, which reflects the effectiveness of the intelligent soil-less cultivation proposed in this paper.

Analysis of Thermal Characteristics of Airborne Integrated Environmental Control System

Taking the simplified airborne integrated thermal management system as the research object, the change characteristics of the system under different control modes are analyzed, which provides a theoretical basis for the study of system control schemes. Using a combination of mathematical models and computer models to establish an integrated airborne thermal management system model with fuel as the main heat sink, air/fuel heat exchanger, fuel/PAO heat exchanger and other main components, and A fuzzy self-tuning PID control method is proposed to analyze system characteristics such as fuel/PAO heat exchanger and electronic equipment thermal changes. The results show that compared to open-loop control under thermal extreme conditions, the fuzzy self-tuning PID control mode can not only effectively control a series of equipment such as fuel pumps to maintain proper speed, but also ensure the electronic cabin and fuel/PAO heat exchanger the outlet temperature is kept within a predetermined range to meet the design requirements of the onboard thermal management system.

Имитационное экспериментальное исследование на испытательном стенде с шестью степенями свободы на основе стратегии нечеткого ПИД управления

The quality of the control system depends on various factors such as the characteristics of the controlled object, the control scheme, the form and size of interference, etc. In a control system where the characteristics of the object and the hardware and software have been basically determined, the control quality of the system depends on the control algorithm. The control algorithm will make the motion process control have better speed, accuracy and stability. The study of control law is an important part of the control system design of the entire six-degree-of-freedom test bench. The characteristics of the controlled object and the existence of interference in this control system require the designed control law to have the characteristics of strong robustness, certain intelligence, and easy implementation, so as to achieve stable and precise control of the system and achieve the control indicators required by the system. The control strategy of this six-degree-of-freedom test bench adopts Fuzzy PID control, which combines fuzzy theory with the mature traditional PID control theory and uses fuzzy theory to tune the three control parameters of PID to form a parameter self-tuning Fuzzy PID control Device. The Fuzzy PID control strategy is simulated by MATLAB simulation software.

Self-tuning fuzzy logic PID controller with a practical view to PEM fuel cell air supply system

Self-tuning fuzzy logic PID controller with a practical view to PEM fuel cell air supply system

Self-tuning fuzzy logic PID controller with a practical view to PEM fuel cell air supply system

Self-tuning fuzzy logic PID controller with a practical view to PEM fuel cell air supply system

Control for Carbon Dioxide Exchange Process in a Membrane Oxygenator Using Online Self-Tuning Fuzzy-PID Controller

Background and objectiveThe aim of this study is to evaluate the performance of conventional PID that is tuned using Zeigler-Nichols continuous cycling, Fuzzy Logic Controller (FLC) and self-tuning Fuzzy-PID (self-tuning FPID) methods to control the rate of CO2 removal from a membrane oxygenator during extracorporeal blood purification process. MethodsSweep gas flow rate is chosen as the manipulated variable of arterial CO2 partial pressure (pCO2) in blood. The performance of these controllers is evaluated based on their response in controlling task and also by the calculation of three performance indices, namely Integral Absolute Error (IAE), Integral Squared Error (ISE) and Integral Time Absolute Error (ITAE). The robustness of the controllers using these tuning methods is then assessed for set point tracking and load disturbance rejection tests. ResultsResults indicated that the self-tuning FPID is observed as the best controller compared to conventional PID and FLC with lower oscillation, overshoot and shorter settling time. As for quantitative measurement, self-tuning FPID outshines the other controllers with 0.854, 1.084 and 41.450 for IAE, ISE and ITAE, respectively in set point tracking task while 0.532 IAE, 0.016 ISE and 28.970 ITAE measured for load disturbance rejections. ConclusionIt can be concluded that self-tuning FPID is the best controller to be used in the automation of extracorporeal circulation control for both set point tracking and load disturbance rejection tests.