Auto Disturbance Rejection Control Research Articles

Research on the EMA Control Method Based on Transmission Error Compensation

This research investigates the impact of nonlinear clearance factors on position tracking accuracy in the servo drive system of a harmonic reducer. The study introduces a technique for modeling and compensating for transmission errors, thereby improving position tracking accuracy through online compensation combined with an auto-disturbance rejection controller. Initially, the mathematical model of the permanent magnet synchronous motor is outlined, and the current loop and speed loop control models are derived. Subsequently, an electromechanical actuator (EMA) simulation model with clearance is established, and detailed simulation analysis is conducted to verify the impact of clearance on tracking accuracy. A model for online compensation of transmission errors is then developed. Following the principles of active disturbance rejection control (ADRC), a second-order ADRC is formulated for real-time compensation of transmission errors in EMA position mode. Finally, through no-load and load experiments, the change in position tracking error with and without transmission error compensation is compared and analyzed. The results demonstrate that utilizing automatic disturbance rejection control with transmission error compensation achieves the highest position tracking accuracy. Compared to the proportion integration differentiation (PID) control method, the root mean square of position tracking error is reduced by approximately 12.8% and 17.3% under no-load and load conditions, respectively. By compensating for position errors online, the accuracy of the EMA position can be improved.

Synchronous Control of High-Speed Train Lift Wing Angle of Attack Drive System Based on Chaotic Particle Swarm Optimization and Linear Auto-Disturbance Resistant Controller

In this study, a control scheme is proposed based on Chaotic Particle Swarm Optimization (CPSO) to enhance the Linear Auto-Disturbance Rejection Controller (LADRC). The focus is on addressing the challenge of high-precision variations in angle-of-attack through dual-motor cooperative control within the lifting wing of a high-speed train. The scheme initiates with the design of a dual-loop structure for LADRC, integrating position and current control. The position loop is further refined. Subsequently, the CPSO algorithm is employed to optimize the parameters of the LADRC controller. Ultimately, the loop is closed by feeding back the position error in the cross-coupled structure to the current loop, thereby achieving high-precision control. The performance of the proposed structure is validated through both Matlab/Simulink simulations and an experimental platform. The experimental results demonstrate that CPSO-LADRC, in comparison to traditional LADRC and Proportion-Integration-Differentiation (PID) control, exhibits an increase in the maximum response time by 3.76 s and 3.3 s, respectively, a reduction in overshoot by 1.12% and 0.8%, as well as a decrease in the maximum synchronization error by 0.45 cm and 1 cm, respectively. These findings validate the effectiveness of the proposed synchronous loop controller method in simplifying computational complexity, enhancing system responsiveness, robustness, and synchronization performance. Additionally, our approach facilitates precise angle-of-attack transformation for the lifting wings of high-speed trains effectively.

Micro-vibration control of spaceborne payload with smart parallel struts

Currently, the observation resolution of Earth observation satellites and space telescopes is progressively increasing. However, vibrations induced by solar panel vibrations, control torque gyroscopic reaction forces, and internal satellite noise significantly impede the observation accuracy of space-borne precision optical payloads. To mitigate the impact of vibrations on precision payload, it is necessary to incorporate isolation devices into the transmission path between the payload and spacecraft bus. This paper aims to design a six-degree-of-freedom parallel struts for active control of vibration in sensitive payloads. An optical payload isolation system is constructed using a Gough-Stewart parallel configuration with flexible hinges. The dynamic model of the system is established by the Newton-Euler method. The dynamic characteristics and response of the isolation system are analyzed. Then the active controller is designed based on the Fuzzy Auto-Disturbance Rejection Control strategy, and the effectiveness of the controller is simulated and compared with the fuzzy Proportion Integration Differentiation (PID) control algorithm. The results show that the active parallel struts exhibit excellent vibration isolation performance and possess strong robustness, which provides a theoretical reference for further space applications.

Speed Tracking and Anti-Slip Control for Heavy Freight Trains Considering the Conicity of the Wheel

To ensure the safe and punctual transportation of freight trains, it is crucial for the train to travel at the targeted speed on the track. This paper proposes a scheme for speed tracking and anti-slip control for freight trains. The speed tracking is implemented through predictive auto disturbance rejection control (PADRC), which includes a flexible Smith estimation module capable of accurately predicting the output of large time delay systems, such as freight trains. The key to anti-slip control relies on the precise observation of the radial velocity and slip rate. Therefore, an unscented Kalman filter observer is designed in this article, incorporating an adaptive parameter adjustment mechanism to enhance observation accuracy. The anti-slip parameters obtained from this observer can then be used to determine the anti-slip control scheme. The effectiveness of this scheme is demonstrated through simulations of the HXD1 electric traction locomotive’s driving process, using line data from the Geku line section in China. Compared to conventional active disturbance rejection control, PADRC reduces speed fluctuation by 55%, and freight trains under anti-slip control decrease the slip speed by 90%.

Intelligent ADRC‐based inertia control for offshore wind farm

AbstractThis paper proposes a virtual inertia control strategy for wind farms based on auto disturbance rejection controller with artificial bee colony (ABC) algorithm. First, based on the system frequency dynamic response equation, an active disturbance rejection controller is designed according to the non‐linear feedback control law and the extended state observer to improve the anti‐interference capability of the virtual inertia control system. Second, in order to solve the problem of difficulty in tuning the parameters of the active disturbance rejection control (ADRC), an ABC algorithm based on nectar collection behaviour was proposed to iteratively optimize the parameters of ADRC. Finally, the proposed control method is effectively verified based on Matlab/Simulink. The simulation results show that compared with traditional algorithms, the proposed ABC‐ADRC can effectively control the rotor speed to adjust the frequency of the power grid system, achieve power sharing and adaptive noise elimination, reduce the complexity of parameter settings, not only improve anti‐interference ability, but also enhance the robustness of the system.

Research on the control strategy of LCL grid-connected inverters based on improved auto disturbance rejection.

The grid-connected inverter is the key to ensure stable, reliable, safe, and efficient operation of the power generation system; the quality of the grid-connected output current waveform directly affects the performance of the entire power generation system. To improve the anti-interference performance and reduce the output current harmonic content of the grid-connected inverter, an improved control strategy that combined repetitive control (RC) and auto disturbance rejection control (ADRC) is designed in this paper. Firstly, decoupled the ADRC to realize the individual adaptation between tracking performance parameters and anti-interference performance parameters of the controller, through which the difficulty of adjusting parameters is reduced. Secondly, the control approach is devised by adding RC to ADRC. To demonstrate the effectiveness of the proposed method in this paper, detailed experimental studies are conducted using proportional integral control, traditional ADRC, and the proposed method under normal power grids, weak power grids, and periodic disturbances. And dynamic performance simulation experiment is done to verify the dynamic performance of the self-disturbance rejection controller before and after the addition of RC links. The results indicated the effectiveness and feasibility of the proposed method. Finally, after simulation, the steady state and dynamic performance are conducted on a hardware testing platform. The impacts of the obtained results indicate the effectiveness and feasibility of the control algorithm proposed, the ability to suppress intermediate frequency disturbances is improved, the bandwidth of the auto disturbance rejection controller is expanded, and the harmonic content of the output current is depressed.

An Integrated Control Approach for Shifting Process of Single-Axis Parallel Hybrid Electric Vehicle with a Multi-Speed AMT Gearbox

When a single-axis parallel hybrid electric vehicle (HEV) equipped with a multi-speed AMT gearbox is in its shifting process, the superposition of dynamic characteristics of multiple power sources and the intervention and withdrawal of AMT transmissions can easily cause significant vehicle longitudinal jerk. To achieve rapid and smooth output changes during the shifting process, this paper proposes an integrated multi-stage robust shifting control method for a single-axis parallel hybrid electric vehicles with a multi-speed AMT gearbox. First, models of key driveline components are constructed, and the shifting process is divided into five stages to provide a clear description of the control problem. Subsequently, we reproduce an integrated multistage robust control method to achieve favorable switching performance and control robustness under external disturbances. We propose a data-driven model predictive control strategy based on additional constraints in the torque unloading and recovery phases. Simultaneously, we present a joint control algorithm that integrates the optimal control and disturbance suppression in the speed synchronization phase. In addition, we develop a sliding mode auto-disturbance rejection control algorithm to achieve accurate position tracking of the shift actuator in the pickup and engage phases. Finally, simulations and bench tests are carried out to verify the effectiveness of the robust control method under different driving conditions. The results demonstrate that the proposed control method can not only coordinate the torque across different power sources and clutch while minimizing vehicle longitudinal jerk, shift time, and friction work, but also provides apparent robustness to model uncertainties and external disturbance. Therefore, the proposed method may offer a theoretical reference for the actual vehicle controller during shifting.

Research on improved linear auto-disturbance rejection control of hybrid energy storage in optical storage microgrid

Photovoltaic power generation has uncertainties such as randomness and volatility. In order to ensure the stable operation of the power system, hybrid energy storage technology is introduced to improve the voltage stability of the optical storage microgrid. Traditional PI control still needs some help in response speed and overshoot. Facing the hybrid energy storage microgrid system with nonlinear and strong coupling characteristics, in order to improve power quality and reduce bus voltage fluctuation and impact, this paper designs an improved active disturbance rejection control (ADRC) integrated energy storage control system based on a fuzzy algorithm, Based on the traditional double closed-loop PI control, the fuzzy LADRC is used to replace the voltage outer loop, and the system model is built on the MATLAB/Simulink platform for simulation. The results show that the proposed control strategy has a smaller overshoot, faster dynamic response time, and good anti-interference ability compared with the traditional PI and ADRC, which improves the dynamic performance of the photovoltaic energy storage system while stabilizing the bus voltage fluctuation and ensures the stable operation of the powergrid.

Research on Influence of Eccentricity on Submersible Motor and its Solution

The working efficiency and stability of submersible motor are very important for energy utilization, and dynamic eccentricity is the main factor affecting its efficiency and fatigue life. This paper takes a 2-pole 60kW vertical three-phase cage induction motor with static eccentricity as the research object. Through finite element analysis, the mechanical structure and coordination of submersible motor shaft and spiral pump are analyzed. The influence caused by motor shaft eccentricity is regarded as external interference received by the system. The idea of auto disturbance rejection controller to eliminate this disturbance, thereby restraining the negative effects caused by motor shaft eccentricity. By using the state expansion observer of the active disturbance rejection model to estimate and compensate the internal disturbance and uncertainty of the system in real time, the rotation error of the shaft of the submersible motor is eliminated, and the motion inconsistency between the rotor of the screw pump and the shaft of the submersible motor caused by shaft eccentricity is suppressed.

Disturbance Rejection Speed Control Based on Linear Extended State Observer for Isokinetic Muscle Strength Training System

Isokinetic muscle strength training is a type of rehabilitation therapy that can effectively improve the motor dysfunction of limbs and enhance joint muscle strength. In active isokinetic training, how to plan the speed reasonably and improve the performance of speed control to fit individualized needs is the core problem of isokinetic muscle strength training equipment control. In this study, a control strategy for isokinetic muscle strength training equipment is proposed, which identifies the user&#x2019;s motion intention and performs speed planning according to the user&#x2019;s motion participation so that the equipment produces a dynamic damping effect. This ensures active interaction between the user and the equipment and meets the force-speed requirements of elbow joint muscle training. To handle the uncertain disturbance in the training process, a linear extended state observer is used to estimate the disturbance term, and a tracking differentiator and nonlinear error feedback control are used to improve the speed tracking performance. The experimental results show that the proposed control scheme realizes effective speed control in isokinetic muscle strength training. <i>Note to Practitioners</i>&#x2014;The bottleneck of isokinetic muscle strength training equipment control system lies in how to plan the speed according to the patient&#x2019;s movement intention reasonably, and how to improve the performance of speed control in the process of rehabilitation training. This paper designs a speed auto disturbance rejection control strategy for isokinetic muscle strength training system with external interference and model uncertainty in practical application. The experimental results show that the performance of the controller is better than the traditional PI controller, and it can realize isokinetic muscle training. This study provides a method for practitioners interested in developing control systems for isokinetic rehabilitation training equipment.

Modulation index detection and stabilization technique of phase modulator in resonant fiber optic gyro base on sampling demodulation

A new modulation index detection and stabilization technique (MIDST) based on sampling demodulation is proposed to reduce the influence of phase modulator (PM) thermal instability on resonant fiber optic gyro (RFOG). Firstly, the factors causing the PM thermal instability and the influence on RFOG are analyzed. Then, a phase modulation index detection technique is proposed to detect the fluctuation of modulation index without complicating the optical path configuration of RFOG. Finally, considering the temperature fluctuation, a modulation index stabilization loop based on auto disturbance rejection controller (ADRC) is designed to stabilize the phase modulation index. In experiments, modulation index can be detected in real time and accurately, and the fluctuation is reduced from 10% to 0.3% over 100 °C temperature range (−40 °C to ＋60 °C) with MIDST. The stability of scale factor and the suppression effect of backscattering noise could be improved effectively.

Modified ADRC Design of Permanent Magnet Synchronous Motor Based on Improved Memetic Algorithm

In this paper, a novel modified auto disturbance rejection control (ADRC) design of a permanent magnet synchronous motor based on the improved memetic algorithm (IMA) is proposed. Firstly, there is an obvious system ripple caused by the defect that the optimal control function used in traditional ADRC cannot be differentiable and smooth at the segment point; aiming at weakening the system ripple effectively, the proposed method constructs a novel differentiable and smooth optimal control function to modify the ADRC design. Furthermore, aiming at improving the integration parameters optimization effect effectively, a novel improved memetic algorithm is proposed for obtaining the optimal parameters of ADRC. Specifically, an IMA with high-quality balance based on an adaptive nonlinear decreasing strategy for the convergence factor, Gaussian mutation mechanism, improved learning mechanism with the high-quality balance between competitive and opposition-based learning (OBL) and an elite set maintenance mechanism based on fusion distance is proposed so that these strategies can improve the optimization precision by a large margin. Finally, the experiment results of the PMSM speed control practical cases show that the ADRC based on IMA has an apparent better optimization effect than that of fuzzy PI, traditional ADRC based on the genetic algorithm and an improved ADRC based on improved moth-flame optimization.

Fault ride-through capability improvement in a DFIG-based wind turbine using modified ADRC

In this paper, an overview of several strategies for fault ride-through (FRT) capability improvement of a doubly-fed induction generator (DFIG)-based wind turbine is presented. Uncertainties and parameter variations have adverse effects on the performance of these strategies. It is desirable to use a control method that is robust to such disturbances. Auto disturbance rejection control (ADRC) is one of the most common methods for eliminating the effects of disturbances. To improve the performance of the conventional ADRC, a modified ADRC is introduced that is more robust to disturbances and offers better responses. The non-derivability of the fal function used in the conventional ADRC degrades its efficiency, so the modified ADRC uses alternative functions that are derivable at all points, i.e., the odd trigonometric and hyperbolic functions (arcsinh, arctan, and tanh). To improve the efficiency of the proposed ADRC, fuzzy logic and fractional-order functions are used simultaneously. In fuzzy fractional-order ADRC (FFOADRC), all disturbances are evaluated using a nonlinear fractional-order extended state observer (NFESO). The performance of the suggested structure is investigated in MATLAB/Simulink. The simulation results show that during disturbances such as network voltage sag/swell, using the modified ADRCs leads to smaller fluctuations in stator flux amplitude and DC-link voltage, lower variations in DFIG velocity, and lower total harmonic distortion (THD) of the stator current. This demonstrates the superiority over conventional ADRC and a proportional-integral (PI) controller. Also, by changing the crowbar resistance and using the modified ADRCs, the peak values of the waveforms (torque and currents) can be controlled at the moment of fault occurrence with no significant distortion.

Rotor position angle control of permanent magnet synchronous motor based on sliding mode extended state observer

ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.

Study of torque pulsation control of switched reluctance motor by auto-disturbance rejection control

The switched reluctance motor drives the rotor based on the principle of minimum reluctance, which is structurally simpler, but the doubly salient structure of the stator and rotor leads to severe torque pulsation. This paper briefly introduces the switched reluctance motor and the auto-disturbance rejection controller for suppressing the torque pulsation of the switched reluctance motor. Then, the auto-disturbance rejection controller was simulated in the MATLAB software, and it was compared with the direct torque control strategy. The results showed that the switched reluctance motor installed with the self-reluctance controller reached the set rotational speed faster, with a smoother torque change; when the set speed changed abruptly, it was adjusted to the new rotational speed faster, with a smooth and stable torque change; when the load torque changed abruptly, it was adjusted to the new torque smoother and faster, and the adjustment to the rotational speed was also faster.

Application of the Gray Wolf Optimization Algorithm in Active Disturbance Rejection Control Parameter Tuning of an Electro-Hydraulic Servo Unit

A valve-controlled hydraulic cylinder system has the characteristics of uncertainty and time-variance, and the electro-hydraulic servo unit encounters shock, vibration, and other external interference when working, which seriously affect the stability of the valve-controlled hydraulic cylinder system. Therefore, it is necessary to introduce an active disturbance rejection controller (ADRC) into the electro-hydraulic servo control. However, there are many ADRC parameters, and it is difficult to set these only with expert experience. Therefore, we propose applying the gray wolf optimization algorithm (GWO) to the ADRC, to auto-tune the parameters and find the optimal solution. In addition, the advantages of the GWO in ADRC parameter tuning are proven and analyzed. The simulation and experimental results showed that the GWO algorithm had a faster mean time for parameter tuning and the smallest fitness value (integrated time and absolute error), compared to the particle swarm optimization algorithm and genetic algorithm. Moreover, a valve-controlled cylinder system, after parameter tuning by the gray wolf optimization algorithm, could accurately adjust the parameters of the auto-disturbance rejection controller, with a faster response speed, smaller overshoot, and better anti-disturbance ability.

Parameter tuning of auto disturbance rejection controller based on improved glowworm swarm optimization algorithm

PurposeThis paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.Design/methodology/approachThis study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.FindingsThe authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.Originality/valueThe innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.

High-speed train speed tracking control based on active disturbance rejection control strategy

The speed tracking control of high-speed trains has the characteristics of nonlinearity, time delay, and multi-factor interference. Aiming at this, a train speed tracking algorithm based on active disturbance rejection control strategy is proposed. First, establish a train control model based on the train dynamics model. Secondly, design a second-order active disturbance rejection controller to set and compensate for unknown disturbances, and then convert the known train parameters to the controlled object for system simulation, the target speed curve is tracked, which proves the feasibility of the auto disturbance rejection control algorithm. Finally, compare traditional PD control algorithms in terms of anti-jamming performance and tracking error. The results show that the high-speed train speed controller based on active disturbance rejection control has greatly improved the tracking speed accuracy and the robustness of the control system.

A control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid unmanned aerial vehicles

Fuel cell/battery hybrid energy storage system (HESS) powered unmanned aerial vehicle (UAV) has the outstanding advantage of long endurance time. Trajectory tracking motion is a commonly used task execution mode of UAVs, especially in autonomous UAVs. This study aims at developing a control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid UAVs. Its position tracking control adopts model predictive control (MPC) and an extended state observer to eliminate the modeling errors and effect of interference. The attitude tracking control adopts an auto-disturbance rejection controller having a quick response. The obtained control parameters are given as an input to the energy management block. Energy management strategies (EMSs) based on online dynamic programming and hierarchical MPC have been proposed. The results obtained from a simulation show that the proposed trajectory tracking control architecture can track the target trajectory stably with a small tracking error. The tracking performance is stable under interference. Experimental results show that dynamic programming is solved online with good control performance. Compared to ordinary EMSs, dynamic programming and hierarchical MPC can increase endurance time by 2.69% and 1.27%, respectively. The proposed control architecture verifies the coordination of energy management and trajectory tracking control, and prospected the advantages of the combination of fuel cell and autonomous driving for long endurance UAVs in the future.

Active disturbance rejection motion control of spherical robot with parameter tuning

PurposeThe characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To improve the anti-interference performance of spherical robots in practical engineering, this paper proposes a spherical robot motion controller based on auto-disturbance rejection control (ADRC) with parameter tuning.Design/methodology/approachThis paper considers the influences of the spherical shell, internal frame and pendulum on the movement of the spherical robot during the rotation to establish the multi-body dynamics model of the XK-I spherical robot. Due to the serious coupling problem of the dynamic model, the motion control state equation is constructed using linearization and decoupling. The XK-I spherical robot PSO-ADRC motion controller with parameter tuning function is designed by combining the state equation with the particle swarm optimization (PSO) algorithm. Finally, experiments are performed to evaluate the feasibility of PSO-ADRC in an actual case compared to ADRC, PSO-PID and PID.FindingsBy analyzing the required time to reach the expected value, the control stability and the fluctuation range of the standard deviation after reaching the expected value, the superiority of PSO-ADRC to ADRC, PSO-PID and PID is demonstrated in terms of the speed and anti-interference ability.Practical implicationsThe proposed method can be applied to the robot control field.Originality/valueA parameter-tuning method for auto-disturbance-rejection motion control of the spherical robot is proposed. According to the experimental results, the anti-interference ability of the spherical robot moving on uneven ground is improved. Therefore, it provides a foundation for the autonomous environmental monitoring of the spherical robot equipped with sensors.