Fuzzy PI Controller Research Articles

Design and implementation of a robust fuzzy adaptive PI controller for inherently unstable systems

Design and implementation of a robust fuzzy adaptive PI controller for inherently unstable systems

Adaptive fuzzy PI control for the dynamic operation of the transcritical CO2 thermal system in electric vehicles

Process control is essential for ensuring the stable and efficient operation of EVs’ transcritical CO2 thermal management systems. Traditional PI control generally shows an insufficient dynamic response for the variable and complex operating conditions and then causes fluctuant process control. This study proposed an adaptive fuzzy PI control strategy to provide real-time varying PI gains for fast-tracking response and fluctuation suppression, considering the compressor discharge pressure, coolant, and air outlet temperature. A high-fidelity transcritical CO2 thermal model in EVs was first built in the Amesim platform to simulate real-time operation, and the adaptive fuzzy PI control algorithm was then developed to optimize the process control. The co-simulation is conducted to validate the effectiveness and adaptability of the proposed control methodology by comparing it with a benchmark traditional PI control strategy. The results indicated that the proposed adaptive fuzzy PI could provide a 9.22 % overshoot suppression for discharge pressure, a maximal 22.29 % overshoot inhibition and 86 s settling time reduction for the air outlet temperature, and a 25 % settling time reduction for the coolant temperature control. In addition, the fuzzy PI improved the start-up characteristics by avoiding excessive response. Such findings demonstrate that the proposed fuzzy PI control algorithm can effectively optimize the dynamic operation of the transcritical CO2 thermal system in EVs.

Fuzzy PI vibration suppression control strategy for space double flexible telescopic manipulator with fractional disturbance observer

The space double flexible telescopic manipulator (SDFTM) with time-varying length, is called the space flexible manipulator and can carry out reciprocating linear telescopic motion along its axis. It possesses characteristics such as lightweight flexibility, small space occupation, large turning radius, and a wide working range. These features can assist astronauts in performing complex tasks in dangerous outer space environments and offer broad application prospects. However, due to the highly nonlinear and time-varying length characteristics of the space flexible manipulator, its dynamic modeling becomes more complex and challenging. Moreover, during the rotation of the space flexible manipulator, its inherent flexible behavior can trigger vibration phenomena, significantly impacting the execution accuracy of on-orbit tasks. Therefore, proposing control methods to address vibration issues is an effective approach. Thus, achieving stable and precise operation of the space flexible manipulator necessitates the precise establishment of its dynamic model and the development of high-precision control algorithms, which have become key research directions. Firstly, a time-varying dynamic modeling method of the space manipulator is proposed by combining the Lagrange principle and flexible beam vibration theory. Unlike the traditional method, which only considers the limit length of the space manipulator under static conditions, the dynamic process of the space manipulator presented during actual operation is fully considered, which greatly improves the modeling accuracy. Then, a time-varying model based on the fuzzy PI real-time control strategy (FD-FZPI) with fractional order disturbance observer (FO-DOB) is proposed. Based on the robust stability principle, a more accurate FO-DOB is proposed based on integer order DOB, coupled with a fuzzy PI controller to compensate for the external disturbance and modeling error of the space manipulator. Finally, numerical simulation analysis is carried out, and the results show that the average parameter difference between the time-varying dynamic model and the static dynamic model can reach about 5.2 %, which indicates the accuracy of the proposed dynamic modeling method. At the same time, the proposed FD-FZPI control strategy achieves about 14.6 % performance improvement over the traditional DOB-PI control method, indicating that the proposed control strategy can effectively suppress the flutter fluctuation of the space manipulator and achieve accurate and stable dynamic tracking.

Comparison of the Performance of Type-1 and Interval Type-2 Fuzzy PI Controllers for Liquid Level Control in a Coupled Tank System

In this study, liquid level control in a coupled tank system is realized with PI controllers whose parameters are adapted using fuzzy logic approximation methods. Type-1 fuzzy PI control, interval type-2 fuzzy PI control and classical PI+Feedforward control methods are applied to the tank system in real time for different reference liquid levels. The performances of the controllers are compared in terms of system response parameters such as rise time, settling time and overshoot percentage. In addition, the performance evaluation of the controllers over a certain period of time is also compared by calculating integral-based concepts that express error performance metrics such as integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The obtained results show that the type-2 fuzzy PI controller shows the best performance, followed by type-1 fuzzy PI control and classical PI+FF controller, respectively.

Research on Distributed Dual-Wheel Electric-Drive Fuzzy PI Control for Agricultural Tractors

In order to solve the problem that, when the vehicle speed of an agricultural distributed dual-wheel electric-drive tractor changes or the system is disturbed by off-load, the traditional PI control cannot be adjusted in time, resulting in the overshoot of steering control or control delay, meaning it then cannot travel along the target trajectory quickly and accurately, a parameter-adaptive dual-dimensional fuzzy PI speed and steering adjustment controller was proposed, which can adjust the PI parameters in real time based on the deviation between vehicle speed, steering, and reference value, as well as the rate of deviation change. Firstly, based on the operational characteristics of agricultural tractors, a dynamic model of a distributed dual-wheel tractor was established, and a hardware-in-the-loop (HIL) test bench was set up. Fuzzy PI controller algorithms for vehicle speed and steering were designed and developed. In addition, simulations and tests were carried out under no-load and off-load tractor operating conditions with MATLAB/Simulink, respectively. The results indicate that, compared with a traditional PI controller, the fuzzy PI controller exhibits a faster control response and better robustness, reducing overshoot by approximately 60% and the steady-state response time by approximately 25%. When subjected to off-load disturbances, the maximum trajectory offset is controlled within 0.08 m, and the maximum trajectory offset is reduced by 45% compared with a traditional PI controller; therefore, the fuzzy PI control algorithm proposed in this paper makes the tractor’s running trajectory more stable and has stronger anti-interference ability towards off-load disturbances.

Verification and Validation of Advanced Control Systems for a Spinal Joint Wear Simulator.

Wear simulation aims to assess wear rates and their dependence on factors like load, kinematics, temperature, and implant orientation. Despite its significance, there is a notable gap in research concerning advancements in simulator control systems and the testing of clinically relevant waveforms. This study addresses this gap by focusing on enhancing the conventional proportional-integral-derivative (PID) controller used in joint simulators through the development of a fuzzy logic-based controller. Leveraging a single-input multiple-output (SIMO) fuzzy logic control system, this study aimed to improve displacement control, augmenting the traditional proportional-integral (PI) tuning approach. The implementation and evaluation of a novel Fuzzy-PI control algorithm were conducted on the Leeds spine wear simulator. This study also included the testing of dailyliving (DL) profiles, particularly from the hip joint, to broaden the scope of simulation scenarios. While both the conventional PI controller and the Fuzzy-PI controller met ISO tolerance criteria for the spine flexion-extension (FE) profile at 1 Hz, the Fuzzy-PI controller demonstrated superior performance at higher frequencies and with DL profiles due to its real-time adaptive tuning capability. The Fuzzy-PI controller represents a significant advancement in joint wear simulation, offering improved control functionalities and more accurate emulation of real-world physiological dynamics.

Fuzzy Based Quick Acting DC Link Voltage Controller for Three Phases of D-Statcom Connected to the Microgrid

The microgrid systems are the combinations of solar photovoltaic, wind energy, fuel cell and battery systems, as well as conventional generators for backup. The micro grid system barriers that are encountered for their integration to the network. In power systems, voltage stability and power quality are major problems. Due to fluctuations in dc link voltage, changes in load may have an effect on the compensation. This work offers a fuzzy logic-based supervisory approach to enhance the performance of the dc link transient. The controllers employ proportional and integral gain changes with fuzzy logic PI controllers integrated with distribution static synchronous compensator (D-STATCOM). These changes occur in the transient response phase right after a load fluctuation. In order to verify the suggested controller, mathematical equations are given to compute the gains of the traditional controller using fuzzy-logic PI fast-acting dc-link voltage controllers for obtaining similar quick transient reaction. Fuzzy logic PI controller enhancements that employ greater sampling during the transient period and expert knowledge of system behavior enhance the controller's performance. Compared to a standard PI controller, a dc link error reduces the capacitor voltage during a load shift. Utilizing the suggested method and the outcomes of MATLAB simulations, it will be demonstrated that efficiency and the voltage's quick settling time.

A comprehensive optimization method for dual redundancy aviation electric propulsion control system

Abstract This paper comprehensively optimizes and improves the traditional vector control method to improve the control performance of dual-redundancy electric aircraft and ensure the stability of its system operation in complex meteorological environments. First, the PI controller of the speed loop is replaced with the designed fuzzy PI controller, and its quantization factor and scale factor parameters are adjusted using a beetle antennae search algorithm (BAS) to enhance the system’s ability to respond quickly and resist interference. Secondly, a sliding mode load observer was designed to feed forward the observed values to the speed loop output, solving the torque and current ripple problems caused by the direct input of the redundant electric propulsion system when the aircraft switches from a single-redundant cruise state to a dual-redundant high-speed state. Finally, the design method was simulated and validated using MATLAB/SIMULINK, verifying the feasibility of the design.

M3C outer loop control strategy based on variable universe fuzzy PI control

M3C outer loop control strategy based on variable universe fuzzy PI control

Maximum Torque Control of Permanent Magnet-Assisted Synchronous Reluctance Motor Using Fuzzy PI

Abstract This paper proposes a fuzzy PI-based Maximum Torque Per Ampere (MTPA) control for Permanent Magnet-Assisted Synchronous Reluctance Motor (PMASynRM). The aim is to address issues such as overshooting and slow response in the operation of the PMASynRM by optimizing MTPA control under traditional PI using a fuzzy PI control algorithm. This approach enhances the system’s responsiveness and disturbance rejection capabilities. The article builds a simulation model for the maximum torque-to-current ratio control of PMASynRM using fuzzy PI control in MATLAB/Simulink, comparing it with traditional PI control. Simulation results indicate that the fuzzy PI motor control system exhibits lower overshoot, faster response speed, and better robustness compared to traditional PI control.

Ultra-high-precision pneumatic force servo system based on a novel improved particle swarm optimization algorithm integrating Gaussian mutation and fuzzy theory

In this study, an ultra-high-precision pneumatic force servo system (UPFSS) is proposed. On the one hand, a novel air-floating pneumatic cylinder (AFPC) with an air-floating piston capable of independent air supply and exhaust is developed for this system, and its special flow channel design allows the air-floating piston to be suspended in the cylinder without being constrained by the pressure in the chambers. The friction force of the AFPC is less than 0.0049 N. On the other hand, a leakage chamber is constructed to simulate the clearance between the air-floating piston and the cylinder wall, and a fuzzy proportional integral (FPI)-based pressure control system (PCS) is designed for the simulated leakage chamber. Furthermore, a novel particle swarm optimization algorithm integrating Gaussian mutation and fuzzy theory (IGF-PSO) is presented. After testing, the IGF-PSO algorithm is found to have outstanding optimization performance. Then, the parameters of the FPI controller are optimized through the IGFPSO algorithm. Experimental comparisons reveal that the steady-state error achieved by the parameter-optimized pressure controller in response to the leakage condition is about 38 % smaller than that achieved by the pressure controller with parameters obtained using the trial-and-error method. Finally, the UPFSS is tested by using the optimized PCS to supply compressed air to the chamber of the AFPC. The results show that the UPFSS achieves a steady-state error of no more than 0.0279 N in the continuous step response within the range of 240 N.

Mitigation of Ethiopian industry sector power quality problems using ultra-capacitor based dynamic voltage restorer

Nowadays, power quality issues; specifically, voltage sag, swell, harmonics, and interruptions have become significant challenges for customers in Ethiopia. These problems can lead to equipment damage, production losses, reduced trust, and increased unsold energy for utility providers. To address these issues, the implementation of Flexible Alternating Current Transmission Systems (FACTS) and Custom Power Devices (CPD) is crucial. In this study, we focus on Desta Garment PLC, an Ethiopian garment industry. Due to faults in a nearby substation, the factory's feeder line frequently experiences voltage sag, swell, and interruptions. As a result, the factory faces partial shutdowns and occasional hours-long interruptions. To mitigate these voltage quality problems, we propose the use of an Ultra Capacitor-based Dynamic Voltage Restorer (DVR). The DVR has been carefully selected and implemented with advanced control strategy which is adaptive fuzzy proportional integral controller. We collected one year of data from the factory and conducted simulations using MATLAB, comparing scenarios with and without the DVR. The simulation results demonstrate that the proposed mitigation technique significantly enhances voltage sag and swell conditions. Importantly, the performance aligns with both IEEE 1250–1995 and IEEE 519–1992 standards. This study highlights the effectiveness of the Ultra Capacitor-based DVR in improving power quality and ensuring stable operations for Desta Garment PLC. By addressing voltage fluctuations, the factory can maintain productivity and minimize disruptions.

Temperature control research for laser-induction hybrid strengthening process

Temperature control research for laser-induction hybrid strengthening process

Investigation of Force-Controlled Polishing of Complex Curved PMMA Parts on a Machining Center

During the polishing process of complex curved PMMA parts, the polishing force is an important factor affecting the surface quality and optical performance. In this paper, a force-controlled polishing device integrated into a machining center to maintain the polishing force is investigated. In order to achieve the real-time active control of the polishing force, the linear voice coil motor and force sensors are used for motion and measurement. A compact structure was designed to couple the linear motion of the voice coil motor with the rotation for polishing. The force-controlled polishing system with a high real-time hardware architecture was developed to perform complex curved polishing path movement with precise force control. Next, the polishing force between the device and the workpiece was analyzed to obtain the mathematical model of the device. Considering the impact during the approaching phase of polishing, a fuzzy PI controller was proposed to reduce the overshoot and response time. To implement the control method, the controller model was established on Simulink and the control system was developed based on TwinCAT 3 software with real-time computing capability. Finally, a polishing experiment involving a complex curved PMMA part was conducted by a force-controlled polishing device integrated into a five-axis machining center. The results show that the device can effectively maintain the polishing force to improve surface quality and optical performance.

Realization of Fuzzy-PI Controller-Based Path Planning of Differential Drive Mobile Robot

This paper uses a cascade-connected fuzzy-PI controller to control the position and speed of a differential drive and four-wheel drive of an autonomous mobile robot for optimal path planning. The angular speed information obtained from the encoder of each motor and the instantaneous position and angle information of the robot were calculated. The angle and position error between the reference points and these values is applied to the fuzzy logic controller as an input signal. The robot angular and linear speed data obtained from the fuzzy logic output were converted into reference speed values with kinematic equations to be applied to the motors. The speed controls of the motors were carried out with a PI controller based on these reference values. The study was performed both as a simulation in the MATLAB program and experimentally in the laboratory environment for one and more reference coordinates. In the experimental study, reference values were sent to the robot via Bluetooth with the Android application designed. At the same time, the instant data of the robot was also collected on the Android device through the same application. These data collected in Excel format were transferred to the computer via e-mail and the graphics were drawn in the MATLAB program. When the results were examined, it was seen that both speed and position control were successfully implemented with the fuzzy-PI controller for optimum path planning of the robot.

Enhancing upper-limb rehabilitation robot: autonomous self-adaptive resistance generation using EMG-based Fuzzy-PI control

ABSTRACT Upper-limb rehabilitation is a technique for improving muscle development and nervous function in stroke patients through repetitive rhythmic hand movements. However, conventional robot-assisted therapy cannot generate the natural resistant responses seen in therapy administered by therapists, leading to critical limitations in its effectiveness compared to conventional therapy. To overcome this limitation, we propose a novel strategy enabling a rehabilitation robot to generate self-adaptive resistance using electromyography (EMG) autonomously signals from the patient. A position-based force control system based on Fuzzy-PI (proportional and integral) control was successfully implemented in robot-assisted upper-limb rehabilitation. Performance evaluation comprised two primary aspects: examining rehabilitation durations and assessing movement smoothness through jerk values. Experimental outcomes revealed that the self-adaptive control (SAC) strategy, which automatically adjusts resistance, outperforms the non-adaptive control (NAC) approach. SAC demonstrated notable superiority in movement smoothness and extended the duration of upper-limb rehabilitation tasks nearly twofold compared to NAC. Furthermore, applying the jerk concept, and assessing motion smoothness, indicated that SAC exhibited more controlled and seamless movements than NAC. The alignment between participant surveys and the outcomes of parallel tests confirms the validity of the study's conclusions. Thus, this research makes a significant contribution towards improving the effectiveness of robot-assisted therapy in stroke rehabilitation.

Controller Design of a Novel Interleaved Parallel Bi-Directional DC-DC Converter

To improve the dynamic performance of the output voltage of the new interleaved shunt bi-directional DC-DC converter, a double closed-loop control method of voltage and current based on fuzzy PI control is proposed. Firstly, based on the study of the operating principle and steady-state performance of the new interleaved parallel DC-DC converter, a small-signal mathematical model of the interleaved parallel bidirectional DC-DC converter with different modes is established, and based on the model, the transfer functions from duty cycle to output voltage and inductor current are derived, and accordingly, the double-closed-loop controller of the bidirectional DC-DC converter is designed. Then the design method of the fuzzy PI controller is described in detail, and the fuzzy control is applied to the voltage outer loop of the double closed-loop control so that the system can adjust the PI parameters in real time. Simulation experiments are carried out by Matlab/Simulink to compare the simulation experimental waveforms using fuzzy PI control and conventional PI control, and it is verified that the fuzzy PI control improves the output voltage response speed of the new interleaved shunt bi-directional DC-DC converter, reduces the voltage peak of the system, and reduces the overshoot.

Optimizing the fuzzy PI controller for quadruple tank system using multi-objective Jaya algorithm

This article proposes the Jaya optimization algorithm for the multi-objective optimization of parameters for a Fuzzy Proportional-Integral (Fuzzy PI) controller, referred to as MOJaya. The purpose is to control the water level of a quadruple-tank system (QTS). The controlled plant is a nonlinear and uncertain Multiple-Input Multiple-Output (MIMO) system, which is affected by various factors such as parameter uncertainties, external disturbances, and significant time delays. These factors have a considerable impact on the stability of the control system. The parameters of the fuzzy controller and the normalization coefficients of the Fuzzy PI controller are optimized offline using the multi-objective Jaya optimization (MOJaya) algorithm. To demonstrate the effectiveness of the proposed algorithm, it was compared with the Fuzzy PI and PI-MOJaya algorithms. The simulation results indicate that the proposed algorithm outperforms the other algorithms in terms of control quality.

A fast and structurally simple control scheme based on a fuzzy supervisory approach for wireless power transfer systems

AbstractWireless power transfer (WPT) is a promising technology and has attracted many researchers’ attention due to its inherent advantages such as reliability, safety, flexibility, and low maintenance costs. For WPT systems, the output voltage varies according to the variable loads and the coupling coefficient conditions, affecting system stability and efficiency. In this regard, this study is concerned with the tracking control problem of WPT systems based on fuzzy supervisory proportional–integral (PI) controller and a phase shift modulation technique, which is for the first time proposed by this paper. By introducing appropriate fuzzy rules, the proposed control scheme not only can track the desired output voltage but also has better robust behaviour to deal with the problem of variations of circuit elements and coupling coefficients. That is, the proposed fuzzy supervisory PI control scheme can perform better than the traditional PI controller. Analysis of the designed control method and simulation results validate the superiority of the proposed method over the traditional PI controller in all conditions, which can make it a suitable choice for the applications of electric vehicle charging systems. The analysis is supported by experimental measurements.

Power Source Converter Based on a Variable-Domain Fuzzy PI Control

The inadequacy of conventional control strategies for multi-phase interleaved parallel circuits in terms of adaptive adjustment makes it difficult to meet the power source design requirements for transient electromagnetic detection systems. This paper introduces a novel approach, the variable-domain fuzzy proportional–integral (PI) adaptive control strategy. This strategy dynamically adjusts the fuzzy domain in real time based on the input error magnitude, ensuring improved control effectiveness. By leveraging the benefits of both the functional scaling factor and the fuzzy reasoning scaling factor, we design scaling factors for the input and output domains to enhance control precision. The focus of this study is on a four-phase interleaved parallel converter, emphasizing the design of the variable-domain fuzzy PI control strategy for the voltage outer loop within the traditional dual closed-loop structure. An experimental prototype with a 220 Vac input, 380 V output, and a power rating of 1000 W is constructed. A comparative analysis between fuzzy control and variable-domain fuzzy PI control is conducted in the voltage outer loop of the dual closed-loop control. Results reveal that dual closed-loop control with variable-domain fuzzy PI control for the voltage outer loop significantly enhances system stability. The startup time to reach the steady state is reduced to 0.632 s, with an overshoot of 28.8 V. Transitioning from 25% load to full load takes only 0.096 s, resulting in a minimal drop of 21.4 V and an overshoot of 13.4 V. Similarly, switching from full load to 25% load in 0.167 s exhibits an overshoot of only 19.6 V. The adaptive regulation capability of the converter is markedly improved, showcasing smaller overshoots and higher-level controlling effectiveness.