PID Method Research Articles

Movement Control of Three Omni-Wheels Robot using Pole Placement State Feedback and PID Control

Omni wheels robot have high efficiency in robot movement, but also have its own challenges in controlling this robot, especially robots with three omni wheels (3WD). This paper proposes a robot control system using the pole placement state feedback method to control the inner loop which controls the body reference speed, and PID method is used to control the outer loop which controls the robot's position in world coordinates. The results obtained using computer simulations show that the proposed method is able to control the robot's position in world coordinates even though there is an overshoot of 5- 10% on X and yaw axis, however the Y axis performance is overshoot more than 100% because of coupled effect thats still cannot be eliminated.

Design and Verification of Deep Submergence Rescue Vehicle Motion Control System.

A six degree-of-freedom (DOF) motion control system for docking with a deep submergence rescue vehicle (DSRV) test platform was the focus of this study. The existing control methods can meet the general requirements of underwater operations, but the complex structures or multiple parameters of some methods have prevented them from widespread use. The majority of the existing methods assume the heeling effect to be negligible and ignore it, achieving motion control in only four or five DOFs. In view of the demanding requirements regarding positions and inclinations in six DOFs during the docking process, the software and hardware architectures of the DSRV platform were constructed, and then sparse filtering technology was introduced for data smoothing. Based on the adaptive control strategy and with a consideration of residual static loads, an improved S-plane control method was developed. By converting the force (moment) calculated by the controller to the body coordinate system, the complexity of thrust allocation was effectively reduced, and the challenge of thrust allocation in the case of a high inclination during dynamic positioning was solved accordingly. The automatic control of the trimming angle and heeling angle was realized with the linkage system of the ballast tank and pump valve. A PID method based on an intelligent integral was proposed, which not only dealt with the integral "saturation" problem, but also reduced the steady-state error and overshooting. Water pool experiments and sea trials were carried out in the presence of water currents for six-DOF motion control. The responsiveness and precision of the control system were verified by the pool experiment and sea trial results and could meet the control requirements in engineering practice. The reliability and operational stability of the proposed control system were also verified in a long-distance cruise.

Finite-Time Height Control of Quadrotor UAVs

The quadrotor Unmanned Aerial Vehicle (UAV) belongs to an open-loop unstable nonlinear system, which also has the characteristics of underdrive, strong coupling and external disturbance. In the height control of quadrotor UAVs, the traditional sliding mode control (SMC) and PID methods cannot quickly and effectively eliminate disturbance effects caused by gust, aerodynamic drag and other factors, which indicates that the quadrotor UAV cannot return to its predetermined trajectory. To this end, this paper proposes a dual closed-loop finite-time height control method for the quadrotor UAV. The proposed method is able to estimate and compensate for the disturbance in the height control and make up for the lack of anti-disturbance ability in the control process. More specifically, a finite-time Extended State Observer (ESO) and a finite-time super-twisting controller are designed for the velocity control system to compensate for the total disturbance and track the rapidly changing expected signal. An integral sliding mode controller is designed for the height control system. Simulation results show that the proposed method can reduce the chattering phenomenon of traditional SMC and improve both control accuracy and convergence speed.

Design and Experiments of Electro-Hydrostatic Actuator for Wheel-Legged Robot with Fast Force Control Response

The wheel-legged robot combines the functions of wheeled vehicles and legged robots: high speed and high passability. However, the limited performance of existing joint actuators has always been the bottleneck in the actual applications of large wheel-legged robots. This paper proposed a highly integrated electro-hydrostatic actuator (EHA) to enable high-dynamic performance in giant wheel-legged robots (>200 kg). A prototype with a high force-to-weight ratio was developed by integrating a micropump, a miniature spring accumulator, and a micro-symmetrical cylinder. The prototype achieves a large output force of more than 9400 N and a high force-to-weight ratio of more than 2518 N/kg. Compared with existing EHA-based robots, it has a higher force-to-weight ratio and can bear larger loads. A detailed EHA model was presented, and controllers were designed based on sliding mode control and PID methods to control the output position and force of the piston. The model’s accuracy is improved by identifying uncertain parameters such as friction and leakage coefficient. Finally, both simulations and experiments were carried out. The results verified the fast response of force control (step response within 50 ms, the force tracking control frequency about 6.7 Hz) and the developed EHA’s good potential for future large wheel-legged robots.

Quadcopter Navigation System With Waypoint Method Through Flight Controller at Ground Station

In a quadcopter, a navigation system is needed to monitor the position and control the movement of the quadcopter. In recent years, a navigation system based on longitude and latitude coordinates has been developed, namely a waypoint system. This flight control system works to maintain the actual position and direction of the quadcopter to its destination. Thus, the authors designed a navigation control system using the waypoint method on a quadcopter which can walk autonomously from one coordinate point to another coordinate point or destination. This navigation system works using GPS (Global Positioning System), and GY-81 as a magnetometer sensor. The application of the waypoint method can help the robot to determine the direction toward the destination and how far the target is from the robot's current position. This is evidenced in the movement of the robot with an accuracy value of up to 99.48% and an average time to reach the target in about 50-65 seconds. The application of the PID method gives better heading results compared to those without using the PID method. This is evidenced by the stable robot movement and fairly accurate compass sensor readings. Based on the test results using the PID method on the seacoast, the error = 2.15% and the accuracy = 97.85%, while in the test without the PID method on the land surface, the error = 3.33% and the accuracy = 96.6%. For testing using the PID method in paddy fields, an error result = 1.85% and an accuracy result = of 98.1%, while testing without the PID method on the surface of the water obtained an error result = 2.75% and an accuracy result = 97.25%.

Analysis and research on the constant-rate penetration mechanism of the seabed cone penetration test system

The seabed Cone Penetration Test (CPT) system is a common method for investigating offshore soil. This paper focuses on a new subsea CPT method for assessing physical and mechanical properties of marine sediments. The new method enables automatic docking and dismantling of the probe rods underwater. The constant-rate penetration mechanism is the basis and core component of the seabed CPT, allowing the probe rod and cone to penetrate the seafloor sediment. Double hydraulic cylinders are used to meet the high penetration force requirements. To maintain a constant penetration rate of 20 ± 5 mm/s, the model identification of the electro-hydraulic servo system is performed using Simcenter AMESim and MATLAB software, and the relevant transfer function is obtained using the PID method. Based on this transfer function, the sliding mode variable structure controller of the electro-hydraulic servo system is designed to regulate the constant penetration rate of the hydraulic cylinder against varying penetration resistance. In-situ measurements were operated using the new seabed CPT rig in Zhoushan Island. The simulation and testing results confirm that the sliding mode variable structure controller is suitable for controlling the system during actual operation.

An Optimized Fractional-Order PID Horizontal Vibration Control Approach for a High-Speed Elevator

Due to factors such as uneven guide rails and airflow disturbance in the hoistway, high-speed elevators may experience significant vibrations during operation. This paper proposes an optimized fractional-order PID (FOPID) method to suppress vibrations of high-speed elevators. First, an accurate horizontal vibration model is established for the elevator car, in which the car frame and body are separate. Then, taking the control cost and the system performance as objective functions, we obtained an optimized FOPID controller based on multi-objective genetic algorithm optimization. Finally, the effectiveness of the controller in reducing elevator vibration was verified through numerical simulation. The results indicate that the horizontal acceleration controlled by the FOPID controller is reduced by about 68% compared to the case without a controller and about 25% compared to the conventional PID controller.

Adaptive Cruise System Based on Fuzzy MPC and Machine Learning State Observer

Under the trend of vehicle intelligentization, many electrical control functions and control methods have been proposed to improve vehicle comfort and safety, among which the Adaptive Cruise Control (ACC) system is a typical example. However, the tracking performance, comfort and control robustness of the ACC system need more attention under uncertain environments and changing motion states. Therefore, this paper proposes a hierarchical control strategy, including a dynamic normal wheel load observer, a Fuzzy Model Predictive Controller and an integral-separate PID executive layer controller. Firstly, a deep learning-based dynamic normal wheel load observer is added to the perception layer of the conventional ACC system and the observer output is used as a prerequisite for brake torque allocation. Secondly, a Fuzzy Model Predictive Control (fuzzy-MPC) method is adopted in the ACC system controller design, which establishes performance indicators, including tracking performance and comfort, as objective functions, dynamically adjusts their weights and determines constraint conditions based on safety indicators to adapt to continuously changing driving scenarios. Finally, the executive controller adopts the integral-separate PID method to follow the vehicle’s longitudinal motion commands, thus improving the system’s response speed and execution accuracy. A rule-based ABS control method was also developed to further improve the driving safety of vehicles under different road conditions. The proposed strategy has been simulated and validated in different typical driving scenarios and the results show that the proposed method provides better tracking accuracy and stability than traditional techniques.

Temperature Regulation of Hot Vapor Preservation Treatment of Litchi Based on PSO-Fuzzy PID

In this paper, a control method was designed based on particle swarm optimization (PSO)–fuzzy PID (PSO-Fuzzy PID). In order to address the issues of significant nonlinearity and extensive hysteresis in the vapor temperature of litchi hot vapor preservation treatment equipment, as well as the inadequacy of traditional control schemes, a PSO-Fuzzy PID controller was developed through the integration of particle swarm optimization and fuzzy logic algorithms. This controller incorporates a scale factor and quantization factor, building upon the foundation of the Fuzzy PID controller. Additionally, a transfer function model was established for both the heating and disturbance links, utilizing a combination of test data modeling methods and relevant theory. Thirdly, a system simulation model was built to compare and verify PID, Fuzzy PID, and PSO-Fuzzy PID control methods, which were carried out on the MATLAB/Simulink simulation platform. Finally, the litchi load test was conducted to further verify the control performance of the PSO-Fuzzy PID method, where the litchi variety was “Jinggang Hongnuo”. The simulation results showed that the overshoot of the optimized control system was reduced by 93.5% and 42.9% compared with the traditional PID control and Fuzzy PID, and the regulation time was shortened by 46% and 31%, which indicates a better control effect. The test results showed that PSO-Fuzzy PID showed better system stability and accuracy than the fuzzy PID control method in different processing temperature and processing time for litchi’s hot vapor treatment. The maximum temperature difference decreased by 0.56 °C on average and the interference adjustment time was reduced by 7.5 s on average. PSO-Fuzzy PID has a good control effect on the temperature of litchi hot vapor treatment, which can provide a reference for model building and temperature control of other similar fruit and vegetable heat treatment equipment.

Anti-Overturning Capability and Fuzzy PID Speed Control for Four-Way Shuttle Vehicles in Processed Grain Storage

As the four-way shuttle vehicle is prone to overturning in finished grain storage during acceleration and deceleration, an overturning mechanical model is constructed. The design factors analyzed include grain bag height, vehicle and grain bag mass, and the type of grain’s effect on the vehicle’s anti-overturning stability. The critical overturning condition of the shuttle vehicle during operation is also determined as a result of this analysis. With the critical overturning condition, the speed control of the shuttle vehicle based on the fuzzy PID method is carried out to improve the anti-overturning stability. Significant details are made about the fuzzification of input and output variables, determination of membership function, establishment of the fuzzy rule base, fuzzy reasoning, and defuzzification. Finally, the comparative simulation model of fuzzy PID and conventional PID in the MATLAB/Simulink platform showed that the fuzzy PID control method had the advantages of fast convergence and quick response to the speed control of the four-way shuttle vehicle.

Electromechanical Actuator Servo Control Technology Based on Active Disturbance Rejection Control

Electromechanical actuators (EMA) are becoming more and more widely used. As the core technology of EMA, servo control technology determines their performance. In this paper, an active disturbance rejection control (ADRC) method with an improved extended state observer (ESO) is proposed to design a cascade controller of EMA based on permanent magnet synchronous motor (PMSM). The mathematical model of PMSM in a two-phase rotating coordinate system is established, then it is decoupled by an id=0 current control method to realize the vector control of the motor. In a three closed-loop vector control system, a PID controller including current loop, speed loop and position loop is designed. To solve the problems caused by measurement noise, the filter link and system are modeled as a whole, and an improved ESO is constructed. On this basis, an ADRC controller of the speed loop and position loop of PMSM is designed and simulated based on Simulink. Based on the physical test platform, a load step test and load disturbance test of ADRC are completed. The results show that, in comparison to the PID method, the ADRC method shortens the response time by 25% on average, and reduces the overshoot by 60% on average. So, it can be concluded that ADRC has good static and dynamic performance, which has a good guiding role for engineering practice.

An extended state observer-based sliding mode control method for hydraulic servo system of marine stabilized platforms

The marine stabilized platform is a critical apparatus to ensure the stability of offshore equipment and operations with respect to the inertial coordinate system. However, the hydraulic actuating system of the platform is challenging to control due to the severe offshore environment and hydraulic parameter perturbations. Therefore, to improve the stability and anti-disturbance performance of the hydraulic actuators on the marine stabilized platform, an extended state observer-based sliding mode control (ESO-SMC) method is proposed in the paper. We first analyze the kinematic model of the platform and the dynamic model of the hydraulic servo system. Then, ESO-SMC is designed, and its stability is verified. The novel Marine Predator Algorithm (MPA) is used to optimize the parameters in ESO-SMC design. Simulation is performed in MATLAB/Simulink using an engineering ship model and a stabilized platform model on the ship. Compared with the traditional Sliding Mode Control (SMC), Velocity Feedforward PID (VFPID), and PID methods, ESO-SMC performs best in resisting external wave load disturbances and flow gain parameter perturbations. In conclusion, ESO-SMC is a reliable control approach for enhancing the anti-interference performance of the hydraulic servo system on marine stabilized platforms in the simulation.

A Cascade BP Neural Network Tuned PID Controller for a High-Voltage Cable-Stripping Robot

A 10 kV distribution network is a crucial piece of infrastructure to guarantee enterprises' and households' access to electricity. Stripping cables is one of many power grid maintenance procedures that are now quickly expanding. However, typical cable-stripping procedures are manual and harmful to workers. Although numerous automated solutions for grid maintenance have been created, none of them focus on cable stripping, and most of them have large dimensions to guarantee multi-functions. In this paper, a new cable-stripping robot for the 10 kV power system is introduced. The design of a live working cable-stripping robot that is appropriate for installing insulating rods is introduced, taking into account the working environment of 10 kV overhead lines and the structural characteristics of overhead cables. The robot is managed by an auxiliary remote control device. A cascade PID control technology based on the back propagation neural network (BPNN) method was developed, as the stripper robot's whole system is nonlinear and the traditional PID controller lacked robustness and adaptability in complex circumstances. To validate the structural feasibility of the cable-stripping robot, as well as the working stability and adaptability of the BPNN-PID controller, a 95 mm2 cable-stripping experiment are carried out. A comparison of the BPNN-PID controller with the traditional PID method revealed that the BPNN-PID controller has a greater capacity for speed tracking and system stability. This robot demonstrated its ability to replace manual stripping procedures and will be used for practical routine power maintenance.

The Design of Rice Milling and Screening Systems Uses the DC Motor PID Method

Rice is one of the staple foods of most Indonesian people, the processing of rice derived from rice plants goes through many stages, one of which is rice milling and sifting. This research aims to make it easier for farmers to do milling and screening, the system will utilize DC motor rotation which is suitable for application in milling and screening, this system also utilizes electrical energy obtained from sunlight so it is more efficient and environmentally friendly. The milling DC motor will use the PID method with a value of P=25, I=50 and D=5 with a setpoint of 250, while the winnowing motor will use a PWM setting of 200 with a voltage of 7.07 V and a motor RPM of 348. This study also has digital scales. which can easily find out the results in units of grams with a maximum capacity of 5,000 grams. The prototype of this rice grinder and sifter has a success rate of testing sensors and motors in the range of 50%, even though the milling results can be said to be less than optimal, the screening results can work according to function, as well as solar panels that can optimally provide power to move the actuators and sensors. sensors in this system.

A segmented optimal PID method to consider both regulation performance and damping characteristic of hydroelectric power system

Hydropower has become the main force of grid frequency regulation due to its regulation flexibility and rapid response characteristics. However, when the operating conditions are changed, the continued pursuit of a faster response speed deteriorates the damping characteristics of the system with wider water-head, causing low-frequency oscillations, threatening the power station's safety and stability and the power grid. In this study, an improved quantized damping method is applied. The settling time and damping coefficient variation under different PID parameters and operating conditions are recorded, revealing the contradiction between regulation performance and damping characteristics. Then the segmented optimal PID controller is proposed to balance this contradiction. The twin-delayed deep deterministic policy gradient learning algorithm enables the controller to find the optimal policy online. With the settling time-damping threshold control strategy, the controller optimizes parameters according to operating conditions, and changes parameters when reaching the threshold. The results show that, compared with using a set of PID parameters, the damping of the hydropower system is increased by 0.35 from negative to positive. In contrast, the settling time increases by 11.63s within limits. The proposed controller ensures the safe and coordinated operation of the power grid and the power station of the hydroelectric power system with a wide water-head.

Learning-based robust optimal tracking controller design for unmanned underwater vehicles with full-state and input constraints

In this article, the optimal tracking control problem for unmanned underwater vehicles (UUVs) with full-state and input constraints under the presence of external disturbances and internal dynamic uncertainties is addressed. To achieve preassigned state constraints on UUVs, the traditional UUVs model is transformed into an unconstrained one by using two different nonlinear mappings (NMs). Then the robust tracking control problem of traditional UUVs model under position/Euler angles and velocity constraints is transformed to an optimal control problem of the transformed system without any constraints. A learning-based optimal control method is designed to solve the optimal control problem of the transformed system by employing the optimized backstepping (OB) paradigm and reinforcement-learning (RL) technique, achieving uniformly ultimately boundedness (UUB) subject to optimal cost. To deal with lumped disturbances for the velocity control loop, a neural-network (NN) identifier is employed and incorporated into actor–critic architecture, attaining robust tracking performance. Due to the adopted nonquadratic cost function with respect to the control input, the optimal control solution is established in the form of a hyperbolic tangent function to handle the input constraints. Compared with traditional PID method and MPC approach, the proposed controller can improve tracking performance of UUV by 32.04% and 79.64%, respectively.

Motion control and path optimization of intelligent AUV using fuzzy adaptive PID and improved genetic algorithm.

This study discusses the application of fuzzy adaptive PID and improved genetic algorithm (IGA) in motion control and path optimization of autonomous underwater vehicle (AUV). The fuzzy adaptive PID method is selected because it is considered to be a strongly nonlinear and coupled system. First, this study creates the basic coordinate system of the AUV, and then analyzes the spatial force from the AUV to obtain the control model of the heading angle, climb angle, and depth. Next, the knowledge of fuzzy adaptive PID and IGA technology on AVU are investigated, then fuzzy adaptive PID controllers and path optimization are established, and experimental simulations are carried out to compare and analyze the simulation results. The research results show that controllers and IGA can be used for the motion control and path optimization of AUV. The advantages of fuzzy adaptive PID control are less overload, enhanced system stability, and more suitable for motion control and path optimization of AUV.

Flight Controller Design for Altitude Control of a Quadcopter using PID and Fuzzy Methods

A quadcopter can be manually controlled or can be autonomous. Therefore, a control system is needed to support the quadcopter's movement. PID and fuzzy control are used in this research to adjust the quadcopter's altitude position. The control system proposed in this research is to keep the quadcopter at a certain altitude. The control system design uses a PID controller, where the control parameters are obtained using the Ziegler-Nichols 2 tuning method. Ziegler-Nichols 2 tuning method is used to obtain the parameters Kp, Ti, and Td. PID control tuning becomes a reference for fuzzy control design in determining input and output membership functions and the rules. Also, in this study, the flight controller board design is proposed. The experiment results show that the PID control has a faster rise time of 0.2 seconds, a better maximum overshoot of 1.56%, a quicker settling time of 1.69 seconds, and a steady-state error of 0% compared to the fuzzy control. The result shows that the use of PID control is more suitable for proposed quadcopter plants because it requires a fast output response.

Cooling Optimization Strategy for a 6s4p Lithium-Ion Battery Pack Based on Triple-Step Nonlinear Method

In a battery cooling system, by adopting a cooling optimization control strategy, the battery temperature under different external environments and load currents can be adjusted to ensure performance and safety. In this study, two modes of the thermal management system are established for the 6s4p (six serial and four parallel batteries in a stage) battery pack. A single particle model, considering battery aging, is adopted for the battery. Furthermore, a cooling optimization control strategy for the battery is proposed based on the triple-step nonlinear method, and then the optimization effect is validated under two C-rate charge–discharge cycles, NEDC cycles, and US06 cycles. Moreover, an extended PID control strategy is constructed and compared with the triple-step nonlinear method. A comparison of pump power, thermal behavior, and aging performance indicate parallel cooling is more advantageous. This verifies the validity of the triple-step nonlinear method and shows its advantages over the extended PID method. The present study provides a method to investigate the thermal behavior and aging performance of a battery pack in a BTM system, and fills in the research gaps in the cooling optimization control strategy for battery packs.

Nonlinear finite‐time control of hydroelectric systems via a novel sliding mode method

A nonlinear finite-time sliding mode control is proposed in this paper for the governing of complex hydroelectric systems with the finite/fixed setting time. The proposed control method is derived from the finite-time stability and sliding mode control theories. The finite settling time is calculated and bounded, not depending on the initial conditions of the system. The solution trajectory of the controlled hydroelectric system can reach the sliding manifold in a fixed settling time, regardless of initial values. Based on the Lyapunov theory, the controlled hydroelectric system also converges to a reference state within the fixed settling time. A simulation of a high-dimensional hydroelectric system verifies the feasibility of the proposed method. In addition, a comparison between the proposed method and the conventional PID method demonstrates the advantages of the proposed method in the shorter settling time and smaller overshoot. The proposed control method allows for the design of a flexible controller and provides an improvement in dynamic performance.