Fuzzy PID Controller Research Articles

Development of a Matlab-Based Fuzzy PID Controller and The Simulation

Fuzzy PID control is a process control technique combining the advantages of fuzzy logic and PID control. It maintains precise control over processes by combining fuzzy logic and proportional-integral-derivative (PID) controllers. With this method, it is possible to achieve higher levels of accuracy and stability in controlling process variables such as temperature, pressure, flow rate, and position. This makes Fuzzy PID control an ideal cordial application requiring precise process control. Fuzzy PID control uses the PID parameter tuning experience to make the fuzzy controller automatically tune its parameters, giving PID control a better control effect. In this paper, a fuzzy PID controller is designed to control the temperature of an electric boiler. The control effects of PID control, fuzzy control, and fuzzy PID control are compared by simulation analysis. The simulation results show that the unclear PID control effect is ideal and has a good application prospect.

Simulation of Comfort Algorithm for Automatic Driving of Urban Rail Train

Abstract The automation and intelligence of transportation vehicles is the focus and hotspot of the future research and development of the entire transportation industry, which can effectively improve a series of social problems such as traffic accidents, exhaust pollution, and traffic jams caused by the current increase in the number of transportation vehicles. With the rapid development of rail transit in our country, more and more people choose urban rail transit for travel, which is greatly convenient for travel. The comfort of Automatic Train Operation (ATO) system is an inevitable consideration when people choose it. Aiming at the comfort of ATO system, this paper designs a train operation target curve that can meet the comfort index of train. At the same time, two simulation models are established by using the SIMULINK module of MATLAB software to compare the experiments. One model is the train simulation model based on PID control, and the other model is the train simulation model based on fuzzy PID. The final simulation results show that fuzzy PID control has stronger superiority in train comfort in the process of train motion simulation, and the traditional PID control is not as good as fuzzy PID control in train comfort.

PID control of evaporation temperature control system based on fuzzy RBF neural network

In this thesis, a fuzzy RBF neural network PID (RBFfnn-pid) control method is designed for temperature deviation concerning the steam curing temperature control system in the steam curing kettle of the aerated concrete block production line. The temperature control system (TCS) models of steam curing are established respectively under the control of fuzzy PID and RBFfnn-pid. Then, the control effect is analyzed by simulation in different situations. The results show that, under this condition of step signal inputting, the RBFfnn-pid control method shortens the rising time by 160 s and reduces the overshoot by 8% compared with the fuzzy PID controlling means. When the system is in a stable state, then the interference signal is added, which in contrast to the controlling means of fuzzy PID, the time for adjusting the RBFfnn-pid control to the set value is shortened by 70 seconds and there is no overshoot. The RBFfnn-pid control method enables the controlling parameters of the steaming temperature control system to be adjusted to the optimum quickly and iteratively, which improves the temperature control accuracy.

Optimal Control of VAV Air Conditioning Terminal in the Polar Cruise Public Area

As a key system to ensure residential comfort, the control mode of the polar cruise air conditioning system directly relates to the comfort of the cabin environment and the economy of ship operation. Aiming at the characteristics of uncertainty and regulation time delay in the load change of the VAV air conditioning system in the public area of polar cruise ships, this paper models the mechanism of the VAV terminal system and conducts simulation experiments on the Matlab/Simulink simulation platform. By comparing the difference between the traditional PID control strategy and the fuzzy PID control strategy in the control effect, it provides a reference for the optimal control of the polar cruise air conditioning system.

Energy Management Strategy Considering Energy Storage System Degradation for Hydrogen Fuel Cell Ship

Abstract A hybrid energy system (HES) including hydrogen fuel cell systems (FCS) and a lithium-ion (Li-ion) battery energy storage system (ESS) is established for hydrogen fuel cell ships to follow fast load transients. An energy management strategy (EMS) with hierarchical control is presented to achieve proper distribution of load power and enhance system stability. In the high-control loop, a power distribution mechanism based on a particle swarm optimization algorithm (PSO) with an equivalent consumption minimization strategy (ECMS) is proposed. In the low-level control loop, an adaptive fuzzy PID controller is developed, which can quickly restore the system to a stable state by adjusting the PID parameters in real time. Compared with the rule-based EMS, hydrogen consumption is reduced by 5.319%, and the stability of the power system is significantly improved. In addition, the ESS degradation model is developed to assess its state of health (SOH). The ESS capacity loss is reduced by 2% and the daily operating cost of the ship is reduced by 1.7% compared with the PSO-ECMS without considering the ESS degradation.

Comparison of several PID controls for quad-rotor UAV under wind disturbance

For achieving the stable flying of the UAV with wind disturbance, it is necessary to select an appropriate flight control system. This paper takes the quad-rotor UAV as the research object. First of all, it briefly introduces the structure and working principle of the UAV. Then it designs classical PID controller, cascade PID controller, fuzzy PID controller based on the system model. Finally, it uses MATLAB/Simulink to simulate the effectiveness of the control algorithm, and analyzes and compares the control effects of the three controllers. From the results of the experiment, it can be seen that the fuzzy PID controller can control the quad-rotor UAV more stably than the classical PID controller and cascade PID controller.

Fuzzy proportional–integral–derivative control system of electric drive downhole cutting tool based on genetic algorithm

An electric drive downhole tubing cutting tool is the key equipment for tubing cutting in pressurized gas well workover operation. Cutting force control in radial feed movement of the cutting blade is the key to ensuring the successful cutting of tubing. In this article, the relationship model between cutting blade feed speed and cutting force is established by Matlab. Based on the mathematical model of cutting head rotation and blade feed movement, combined with the relationship between blade feed and cutting force obtained from cutting experiments. To keep the cutting force of the blade constant in the cutting process. Genetic algorithm was used to optimize the fuzzy proportional–integral–derivative control, and the automatic control scheme of the electric drive downhole tubing cutting tool was constructed. Based on Matlab/Simulink, the cutting force control simulation of the tubing cutting process is carried out. The performance of fuzzy proportional–integral–derivative control optimized by the genetic algorithm is compared with that of other standard controllers. The results show that the response speed and stability of the fuzzy proportional–integral–derivative control system are better than other algorithms. The steady-state error of the controller in the steady-cutting stage is < 5% based on the ground-cutting experiment of tubing, which meets the actual engineering needs and verifies the reliability and accuracy of the control system.

Real-Time Interval Type-2 Fuzzy Control of an Unmanned Aerial Vehicle with Flexible Cable-Connected Payload

This study presents the design and real-time applications of an Interval Type-2 Fuzzy PID (IT2-FPID) control system on an unmanned aerial vehicle (UAV) with a flexible cable-connected payload in comparison to the PID and Type-1 Fuzzy PID (T1-FPID) counterparts. The IT2-FPID control has significant stability, disturbance rejection, and response time advantages. To prove and show these advantages, the DJI Tello, a commercial UAV, is used with a flexible cable-connected payload to test the robustness of PID, T1-FPID, and IT2-FPID controllers. First, the optimal coefficients of the compared controllers are found using the Big Bang–Big Crunch algorithm via the nonlinear UAV model without the payload. Second, once optimised, the controllers are tested using several scenarios, including disturbing the payload and the coverage path planning area to examine their robustness. Third, the controller performance results are evaluated according to reference achievement and point-based tracking under disturbances. Finally, the superiority of the IT2-FPID controller is shown via simulations and real-time experiments with a better overshoot, a faster settling time, and good properties of disturbance rejection compared with the PID and the T1-FPID controllers.

Online PID Tuning Strategy for Hydraulic Servo Control Systems via SAC-Based Deep Reinforcement Learning

Proportional–integral–derivative (PID) control is the most common control technique used in hydraulic servo control systems. However, the nonlinearity and uncertainty of the hydraulic system make it challenging for PID control to achieve high-precision control. This paper proposes a novel control strategy that combines the soft actor-critic (SAC) reinforcement learning algorithm with the PID method to address this issue. The proposed control strategy consists of an upper-level controller based on the SAC algorithm and a lower-level controller based on the PID control method. The upper-level controller continuously tunes the control parameters of the lower-level controller based on the tracking error and system status. The lower-level controller performs real-time control for the hydraulic servo system with a control frequency 10 times higher than the upper controllers. Simulation experiments demonstrate that the proposed SAC-PID control strategy can effectively address disturbances and achieve high precision control for hydraulic servo control systems in uncertain working conditions compared with PID and fuzzy PID control methods. Therefore, the proposed control strategy offers a promising approach to improving the tracking performance of hydraulic servo systems.

Speed Control Method for the Working Shaft of the Complex Hydraulic Drive System Based on IFE-WOA Improved Fuzzy PID Controller

ABSTRACT The precise control of a complex hydraulic drive system, which is mostly dependent on the speed control of the system working shaft, contributes to an improvement in product quality. In this paper, a novel working shaft speed control method for complex hydraulic drive system is proposed. First, a mathematical model of the operation of the working shaft and related components is established, and the fuzzy PID controller is designed to regulate the working shaft speed of the complex hydraulic drive system based on fuzzy rules. A whale optimization algorithm improved by intuitionistic fuzzy entropy is proposed to optimize the parameters of fuzzy PID controller in light of the possibility that the selection of parameters of fuzzy PID controller will have an impact on the final control effect. By applying an improved fuzzy PID controller to fit working shaft speed of three complex hydraulic drive system, the control performance of the controller is evaluated. The experimental results demonstrate that the tracking accuracy and immediate efficiency of the proposed method for working shaft speed control of the complex hydraulic drive systems are significantly better than those of the fuzzy PID controller and the fuzzy PID controller optimized with the unimproved whale optimization algorithm, proving the proposed method has strong engineering practical application capacity and can more effectively fulfill the working shaft speed control needs of the complex hydraulic drive system.

Control of Oxygen Excess Ratio for a PEMFC Air Supply System by Intelligent PID Methods

The hydrogen fuel cell is a quite promising green device, which could be applied in extensive fields. However, as a complex nonlinear system involving a number of subsystems, the fuel cell system requires multiple variables to be effectively controlled. Oxygen excess ratio (OER) is the key indicator to be controlled to avoid oxygen starvation, which may result in severe performance degradation and life shortage of the fuel cell stack. In this paper, a nonlinear air supply system model integrated with the fuel cell stack voltage model is first built, based on physical laws and empirical data; then, conventional proportional-integral-derivative (PID) controls for the oxygen excess ratio are implemented. On this basis, fuzzy logic inference and neural network algorithm are integrated into the conventional PID controller to tune the gain coefficients, respectively. The simulation results verify that the fuzzy PID controller with seven subsets could clearly improve the dynamic responses of the fuel cells in both constant and variable OER controls, with small overshoots and the fastest settling times of less than 0.2 s.

Fuzzy Fractional Order PID Tuned via PSO for a Pneumatic Actuator with Ball Beam (PABB) System

This study aims to improve the performance of a pneumatic positioning system by designing a control system based on Fuzzy Fractional Order Proportional Integral Derivative (Fuzzy FOPID) controllers. The pneumatic system’s mathematical model was obtained using a system identification approach, and the Fuzzy FOPID controller was optimized using a PSO algorithm to achieve a balance between performance and robustness. The control system’s performance was compared to that of a Fuzzy PID controller through real-time experimental results, which showed that the former provided better rapidity, stability, and precision. The proposed control system was applied to a pneumatically actuated ball and beam (PABB) system, where a Fuzzy FOPID controller was used for the inner loop and another Fuzzy FOPID controller was used for the outer loop. The results demonstrated that the intelligent pneumatic actuator, when coupled with a Fuzzy FOPID controller, can accurately and robustly control the positioning of the ball and beam system.

Research on Magnetic Characteristics and Fuzzy PID Control of Electromagnetic Suspension

This paper proposes an electromagnetic suspension with an electromagnetic actuator, which can improve the riding comfort and stability of the vehicle without changing the safety of traditional MacPherson suspension. First, the electromagnetic suspension structure is introduced, and the principle of the proposed actuator is described in detail. Second, a magnetic flux density model of a single PM ring (permanent magnetic ring) and a magnet assembly are built, and a theoretical analysis of the magnetic flux density is carried out for comparison. Then, the magnetic flux distribution of the magnetic field is simulated and analyzed using the finite element method (FEM), and is compared with theoretical and other experimental data. Finally, a vehicle dynamics model with 7 DOF is built, and vehicle simulations based on the fuzzy PID algorithm are carried out on a C-grade road surface and a deceleration strip. The theoretical results and simulation analyses of the FEM indicate that compared with the MacPherson suspension, the root mean square values of the acceleration of centroid acceleration for the electromagnetic suspension are increased by 59.08% and 33.34%, respectively, on a C-grade road surface and a deceleration strip, and other physical quantities have also been improved. The structure and characteristics of the proposed electromagnetic suspension that improve the riding comfort of the suspension and enhance the stability of the MacPherson suspension are feasible.

Squirrel search algorithm based intelligent controller for interconnected power system

ABSTRACT In this paper, a novel controller, namely fractional order fuzzy proportional-integral-derivative (FOFPID) has been proposed for the dual area power system of hydro-thermal-gas units (DAHTG). The squirrel search algorithm (SSA) is implemented to achieve the optimal values of the controller tuning parameters. Further, various non-linearity constraints, such as governor dead band (GDB), generation rate constraint (GRC) and communication time delays (CTDs) have also been considered to test the effectiveness of the proposed controller in a real-time environment. The step load of 10% is provided as the disturbance under the regulation. In addition, the coordinated strategy of a static synchronous series compensator (SSSC) device and superconducting magnetic energy storage (SMES) is employed in the proposed system to enhance the system’s performance. Further, the accuracy, effectiveness and robustness of the proposed controller are revealed through the comparative analysis with classical PID and traditional fuzzy PID controllers. Furthermore, presented controller efficacy is revealed with the other recently reported control techniques by implementing it on the two-area thermal system with GDB. The comparative analysis shows the better performance of the proposed controller than these two. Finally, the sensitivity analysis is performed to check the controller robustness.

Vibration characteristics control of hybrid radial gas foil bearing-rotor system: Simulation and experiment

Currently, tiny, high-speed rotating machines frequently employ air foil bearings. Air is employed as the working medium, however, when the rotor speed is high, the rigidity of the air film is insufficient, which restricts the usage of air foil bearings. This study utilizes the external gas supply method of hydrostatic gas bearings to strengthen the air film stiffness of air foil bearings. The original air foil bearings are combined with external gas supply piping to create the hybrid gas foil bearing(HGFB), which may be utilized to increase the air film support stiffness of the bearings through the external gas supply. Additionally, by altering the gas supply pressure, this bearing may be used to actively manage the vibration characteristics of the shaft system, allowing the bearing performance to be adjusted to changing operating conditions. The static and dynamic properties of the HGFB with a 24 mm diameter are solved in this study using Newton's iterative approach and the finite difference method. The bearing-rotor system is modeled using this information. An Analysis is done on the impact of various air supply pressures and throttle hole widths on bearing performance and vibration characteristics of the shaft system. In this article, the vibration parameters of the bearing-rotor system are tested using an open-loop control test. The open-loop control experiment on the vibration response of the bearing-rotor system is performed using HGFBs with orifice sizes of 0 mm, 0.2 mm, 0.4 mm, 0.6 mm, 0.8 mm, and 1.0 mm. The experimental results confirm the accuracy of the simulation results. Correspondingly, this paper conducted closed-loop control comparison experiments on the vibration properties of the bearing-rotor system using the PID control method and the fuzzy PID control method in succession. It then evaluated the control effect of the two control strategies on the vibration of the bearing-rotor system and managed to improve the conventional PID control method used for gas bearings.

Membrane humidity control of proton exchange membrane fuel cell system using fractional-order PID strategy

Dynamic humidity control is a crucial factor affecting the working performance of proton exchange membrane fuel cell (PEMFC) system. Proper membrane humidity can guarantee power generation performance, improve energy utilization efficiency, prevent irreversible degradation of the proton exchange membrane (PEM). In this paper, a dynamic control model for PEMFC humidity management is proposed, and a fractional-order PID (PIλDμ) control strategy is introduced to balance the membrane humidity of PEMFC. The results show that comparing with traditional PID control methods, the PIλDμ control shows shorter response time, lower overshoot in membrane humidity control, and higher power generation efficiency in PEMFC system. In addition, the performance of the PEMFC using PIλDμ control method at different pressure and temperature conditions is discussed. The power generation efficiency of the PEMFC under PIλDμ control is improved, which is 2.1 %, 3.9 % higher than that of fuzzy PID and conventional PID control method.

The Recovering Stability of a Towing Taxi-Out System from a Lateral Instability with Differential Braking Perspective: Modeling and Simulation

The traditional method of taxiing for civil aircraft, which relies on their engines, may be surpassed by the new method of towing taxi-out due to its superior advantages such as reduced energy consumption, lower emissions, and higher efficiency. However, the towing taxi-out system poses a challenge to lateral stability due to the concentration of mass at the rear, leading to severe instability when turning at high speeds. To address this issue, a nonlinear civil aircraft towing and taxiing system model and a linear four-degree-of-freedom civil aircraft towing and taxiing system reference model were established using TruckSim and Matlab/Simulink software. The fuzzy proportional–integral–derivative controller was utilized, with the braking torque of each wheel serving as the control variable and the real-time yaw rate difference and its rate of change as the fuzzy control input. The controller was compared and validated with a traditional PID controller. The results of the simulation showed that the fuzzy PID control has better nonlinear characteristics and stronger adaptability to operating conditions compared to traditional PID control, providing timely, effective, adaptive, and robust control effects for the vehicle dynamics model. Under the fuzzy PID control, the peak yaw speed of the civil aircraft decreased to 10 degrees per second under double-shift conditions, representing an increase of 23.1%. Furthermore, the lateral stability and safety of the towing taxi-out system were improved, as evidenced by the reduction in the yaw rate of the tractor and civil aircraft under the hook condition. The use of this controller provides valuable technical guidance and support for the practical development and safe application of the towed glide mode.

Research on a Three-Dimensional Fuzzy Active Disturbance Rejection Controller for the Mechanical Arm of an Iron Roughneck

In the position control of the mechanical arm of an iron roughneck (MAIR), a controller with high responsiveness, high accuracy, and high anti-interference capability is necessary. An MAIR consists of two proportional-valve-controlled single-extension (PVCSE) hydraulic cylinders, and a traditional proportional–integral–derivative (PID) controller cannot easily achieve the accuracy and robustness requirements of the hydraulic cylinders. In this paper, a three-dimensional fuzzy active disturbance rejection controller (TF-ADRC) is proposed for an MAIR, which adds a three-dimensional fuzzy module to a classical active disturbance rejection controller (ADRC) to adjust the controller output according to the tracking of differential deviation, deviation change rate, and deviation change acceleration rate. Firstly, the trajectory planning of the MAIR was carried out using the quintic polynomial interpolation method to improve the smoothness of the target trajectory. Then, the reliability of the established model was verified by experiments. Finally, the comprehensive performance of a PID controller, fuzzy PID controller, ADRC, and TF-ADRC were compared based on the AMESim-Simulink model. The system with the TF-ADRC exhibits higher position control accuracy and better anti-interference capability than the system with a PID or Fuzzy PID controller, and accuracy is higher compared with the common ADRC.

Boundary Guidance Strategy and Method for Urban Traffic Congestion Region Management in Internet of Vehicles Environment

Accelerated urbanization has increased regional traffic congestion. To alleviate traffic congestion in a homogeneous road network, combined with the advantage of real-time traffic information obtained by the Internet of Vehicles (IoVs), a boundary guidance strategy for traffic congestion region is proposed. The strategy considers the optimal operation state of traffic congestion region and is divided into two categories according to different destinations of traffic demands. Meanwhile, a method for the boundary guidance strategy is presented in which the macroscopic fundamental diagram (MFD) is used to determine the optimal accumulation, a traffic flow equilibrium model is established to calculate the real-time accumulation, and a fuzzy adaptive PID control algorithm is designed to calculate the optimal traffic inflow of the traffic congestion region. Furthermore, an example is selected for simulation. The results show that the boundary guidance strategy can effectively improve the operational state of the road network and alleviate traffic congestion. Finally, the influence of connected vehicle penetration rate on the strategy is discussed. The simulation results show that the strategy can improve the operation state of the road network under mixed traffic flow, and the higher the penetration rate, the more significant its effect on alleviating traffic congestion.

Research on the three-dimensional visual management and control for marine intelligent mould bed based on digital twin

ABSTRACT Mould bed is crucial for supporting the ship subsection and controlling its deformation during shipbuilding. However, its visualisation and control process intelligence are often inadequate, leading to reduced accuracy and efficiency in ship subsection construction. Aiming at the problem, a three-dimensional (3D) visual monitoring method for the marine intelligent mould bed is proposed based on digital twin, and the overall framework of the management and control system is designed. Meanwhile, a fuzzy PID control principle optimised by the genetic algorithm is proposed to better control the deformation of the ship subsection. On this basis, the verification of the developed system is carried out based on the physical intelligent mould bed, and the 3D visual management and control of the marine intelligent mould bed are realised. It provides a foundation for improving the accuracy and efficiency of ship subsection construction.