Active Disturbance Rejection Control Method Research Articles

Coupled translation and attitude tracking control for multi-satellite electromagnetic formation flight based on dual quaternion

Electromagnetic formation flight technology utilizes electromagnetic force and torque between satellites to control satellites’ relative position and attitude without consuming propellant, thus having broad application prospects. However, the dynamics of electromagnetic formation flying are nonlinear and strongly coupled, posing challenges to the 6-DOF control of electromagnetic formation and the magnetic dipole allocation of satellites. The frequency division multiplexing method can approximate decoupling formation dynamics by loading multi-frequency AC carriers onto satellite magnetic dipoles and is likely to achieve more control functions. A design method for AC carriers based on frequency division multiplexing is proposed to decouple formation dynamics while controlling electromagnetic force and torque. This paper further provides an analytical solution for the magnetic dipoles of the electromagnetic force/torque equations. In addition, in response to external disturbances, model uncertainty, and the inability to obtain relative velocity and angular velocity information of the formation system, this paper establishes a 6-DOF coupling model based on dual quaternion and implements tracking control using the active disturbance rejection control method. Based on the internal force characteristics of the electromagnetic formation, an expression for the equilibrium distribution of reaction wheel torque is derived to avoid some reaction wheels’ rapid accumulation of angular momentum. Numerical simulation results show the effectiveness of the proposed control method.

A composite fractional order active disturbance rejection control method for a class of uncertain systems with multiple disturbances

SummaryThe existing active disturbance rejection control (ADRC) method may not provide sufficient disturbance rejection to multiple mismatched disturbances for the fractional order systems. In this paper, a composite disturbance rejection approach is developed for a class of fractional order uncertain systems, by synthesizing the fractional order ADRC (FOADRC) approach and a disturbance observer (DO)‐based compensation scheme. Taking advantage of more disturbance information and a filter structure, an improved DO is developed to achieve precise estimation of disturbances in the presence of sensor noises. In addition, a state transformation is developed to convert the system into a simple integral chain model with only matched disturbances. Then a composite control law is designed to compensate the disturbances and provide satisfying dynamic performance. The efficiency of the proposed method is demonstrated by a numerical simulation and an actual servo control simulation, as well as the comparison with two kinds of the existing ADRC methods and the commonly used integral sliding mode control (I‐SMC) method.

Integrated guidance and control design by active disturbance rejection method for high-velocity target interceptor with DCS thruster

The present paper proposes a novel integrated guidance and control (IGC) method for engaging with high-speed targets such as ballistic projectiles. considering an extreme short period of terminal engagement due to high relative velocity between target and interceptor, it is particularly important for IGC law to show desirable performance in the presence of various uncertainties (e.g. variation in aerodynamic coefficients) and disturbances (e.g. target maneuver and drag). This article extends the ICG law for mismatched and feedback form equations based on the Active Disturbance Rejection Control (ADRC) method using the back-stepping technique and the Reduced-order Extended State Observer (RESO). The primary consideration is the application of thrusters on the center of mass as the Divert Control System (DCS), along with the daisy-chain technique for control allocation between the fins and thruster commands. Contrary to previous research, the filter and angle measurement error are modeled for the seeker as a crucial parameter to highlight the significance of the thruster. The simulation results indicate the efficiency of the developed method for near-miss or hit-to-kill engagement with tactical ballistic targets. It is shown that the thruster plays a significant role in high-altitude engagements, specifically in the presence of non-ideal seeker. Finally, using the Monte Carlo simulation, it is proved that adding inner loops to the developed technique will not remove the IGC’s advantage over the conventional approach and Non-singular Terminal Sliding Mode (NTSM) guidance law.

Research on high-bandwidth linear active disturbance rejection control method for variable speed turboshaft engine

Abstract The wide flight range and high torsional vibration frequency of high-speed helicopters impose stricter criteria for the high-bandwidth control of turboshaft engines. Consequently, research is underway to implement a high-bandwidth control method for turboshaft engines using the linear active disturbance rejection control (LADRC) theory. Initially, the LADRC is designed based on the mathematical model of the integrated helicopter/engine system. To address the challenge of maintaining control quality with varying speed reference commands for the power turbine, an improved LADRC method with tracking differentiators (TD) is developed. Numerical simulations comparing the control effectiveness of LADRC with TD to cascade PID and conventional LADRC methods are conducted. The results demonstrate that the improved LADRC gains have a wider tuning range than the LADRC controller, and the power turbine speed tracking effect of LADRC with TD is optimal. It is more conducive to accomplish high-bandwidth control of turboshaft engine with variable rotational speed.

Online learning-based active disturbance rejection control of autonomous surface vehicles with HIL simulations

Modeling and control of autonomous surface vehicles (ASVs) is a challenging task due to the requirement of real-time adaptation to internal hydrodynamic parameter variations and external ocean disturbances induced by wind, waves, and ocean currents. In this paper, an online learning-based active disturbance rejection control method is proposed by combining real-time model learning and anti-disturbance control. Specifically, a filtering learning extended state observer (FLESO) is proposed for online identifying the unknown hydrodynamic parameters, the unknown control input gain, and estimating system uncertainties composed of the unknown external disturbances and dynamic modeling errors, with guaranteed convergence. Then, a self-learning anti-disturbance control law is developed based on the FLESO, enabling self-learning anti-disturbance speed tracking without prior knowledge of model parameters. A salient feature of the proposed method is that the unknown hydrodynamic parameters, the unknown control input gain, and the unknown system uncertainties can be estimated online simultaneously. Lyapunov stability analysis is employed to verify the stability of the closed-loop system. The effectiveness of the proposed online learning-based active disturbance rejection control method is demonstrated through HIL simulations.

A novel collaborative control algorithm for maximum power point tracking of wind energy hydraulic conversion system

AbstractWind has been admitted as one of the most promising renewable energy resources in multinational regionalization policies. However, the energy conversion and utilization are challenging due to the technique reliability and cost issues. Hydraulic wind turbine (HWT) may solve the above problems. HWT is taken as a research object, and the maximum power point tracking (MPPT) control strategy is proposed collaborating with active disturbance rejection control (ADRC) and linear quadratic regulator (LQR) control methods, to solve multiplicative nonlinearity problems in the plant models and the influence of external disturbance on control performance in the MPPT control process. A nonlinear simulation model is built to explain the main findings from the experiments and obtain a better understanding of the effect of time‐varying system parameters and random fluctuation in wind speed. The collaborative control algorithm is experimentally verified on a 24‐kW HWT semi‐physical test platform that results in a promising energy conversion rate, plus the hydraulic parameters can satisfy the demand, accordingly. Ultimately, the potential challenges of implementing this technique in a smart wind energy conversion system are discussed to give a further design guidance, either theoretically or practically.

Output feedback stochastic MPC for tracking control of quadrotors with disturbances

AbstractIn this paper, the trajectory tracking problem of controlling a constrained quadrotor with unmeasurable system states in an environment with stochastic wind‐gust disturbance is considered. The mathematical model of the quadrotor is divided into the translational system and the rotational system, while only the measurement output of the quadrotor can be accessed. A new output‐based control method is developed for solving this problem. In the translational control system, an output feedback stochastic model predictive control (MPC) algorithm is proposed to generate the optimal control sequence with less conservativeness, by taking into account the information on the distribution of the disturbances and the uncertainty resulting from the attitude tracking error. The closed‐loop probabilistic constraints satisfaction, the recursive feasibility and the stability of the algorithm are further proved. In the rotational system, the active disturbance rejection control (ADRC) method to estimate and compensate for external disturbances is leveraged and robust control for attitude tracking is accomplished. The convergence of the disturbance estimator and the stability proof are provided. Finally, the robustness and effectiveness of the proposed control strategy are verified by an illustrative example.

Variable structure control based active disturbance rejection control of unstable non-minimum phase delayed processes

The standard active disturbance rejection control (ADRC) method does not work for controlling unstable, non-minimum phase delayed systems. To solve this issue, a variable structure control (VSC) based ADRC approach is proposed for controlling unstable non-minimum phase industrial processes in this work. Tuning of control parameters for optimal control performances is accomplished with the particle swarm optimization (PSO) based approach. The performance of the proposed VSC-based ADRC approach is numerically studied on an unstable non-minimum phase (UNMP) process with delay and a u-tube steam generator (UTSG) level control system. It is found that the proposed control method is able to provide a fast response, zero steady-state error, and robustness against process uncertainties and load disturbances.

Active Disturbance Rejection Control Method for Marine Permanent-Magnet Propulsion Motor Based on Improved ESO and Nonlinear Switching Function

In the control of marine permanent-magnet propulsion motors, active disturbance rejection control has attracted much attention because it can deal with external load disturbances and uncertainties of motor parameters at the same time. However, the conventional second-order ADRC has the problem of slow disturbance observation speed. To this end, this paper proposes an improved third-order extended state observer using the proportional–integral disturbance update law to improve the tracking performance and anti-external disturbance ability of the motor control system. Then, aiming at the problem that the structure does not effectively use the current information, resulting in large speed fluctuations when the load changes, the measured value of the q-axis current is used as the disturbance feedforward compensation item to further improve the load disturbance suppression ability of the motor. Finally, in order to suppress the influence of the current periodic disturbance caused by unmodeled dynamics on the steady-state accuracy of the motor, a nonlinear switching function with bounded gain and an IIR low-pass filter are designed to suppress the periodic disturbance without affecting the dynamic performance of the system. Combined with the established ship propeller load model, the effectiveness of the method is verified on the motor experimental platform: When suddenly changing 75% of the propeller load, the motor speed decreases by about 20%, and the adjustment time is 0.1 s, which improves the performance by more than 70% compared to PI control and conventional ADRC methods.

Disturbance rejection control of shaking table based on adaptive-model-based state estimator

Real-time hybrid simulation (RTHS) is an important method for the seismic testing of building structures. This method requires high control accuracy for the waveform reproduction of a shaking table. An active disturbance rejection control (ADRC) method is introduced to control the shaking table in this research. In view of the difficulty of parameters setting caused by the large deviation of the extended state observer (ESO) to the state estimation of the shaking table, a model-based adaptive state estimator (AMSE) is designed that uses the model information to estimate the state, and introduces an adaptive strategy to dynamically compensate for the amplitude and phase deviation of the model. The total disturbance is observed by the ESO. Additionally, an AMSE-based ADRC is proposed to achieve high-precision seismic waveform reproduction. The separation principle of the designed system is proved by the Routh–Hurwitz criterion, and the pole assignment bandwidth method is proposed to improve the control performance of the system by flexibly assigning the controller poles. Finally, the shaking table experiments are designed for different specimens. These experiments verify the advantages of the proposed method for state estimation and parameter setting and can effectively improve the stability and control accuracy of shaking table control.

Discrete-Time Active Disturbance Rejection Current Control of PM Motor at Low Speed Using Resonant Sliding Mode

A discrete-time active disturbance rejection control (ADRC) method using resonant sliding mode is proposed to solve the disturbance characteristics of the current loop of permanent magnet (PM) motor at low speed. The extended state observer (ESO) is used to estimate the disturbance, but there is a contradiction between disturbance rejection and noise rejection in parameter design of ESO, which will affect the accuracy of the estimation, especially at low speed. In order to solve the problem, sliding mode control is combined with ADRC, while traditional integral sliding mode control still has poor rejection effect on the specific frequency harmonics. The resonant sliding mode is proposed to add resonance term to the integral sliding mode surface, which mitigates the impact of the disturbance that ESO fails to estimate on the tracking accuracy. Therefore, resonant sliding mode in the feedback control law of ADRC (RSM-ADRC) is employed to current loop to reduce the steady-state error. Meanwhile, the stability of the proposed algorithm is verified by discretization method. The steady and dynamic performances of the four control methods are compared through experiments to verify the feasibility and effectiveness of the proposed method. For example, when the reference current of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis is 0A and 1A respectively at 50rpm, the total harmonic distortion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current decreases from 1.68% to 0.64% and the 6th harmonic of current also drops to 0.135%. Despite the sudden change of inductance parameters, the steady-state current response is largely unaffected.

Active disturbance rejection coordinated control for integrated solar combined cycle system considering system inertia difference

The integrated solar combined cycle system (ISCC) primarily consists of solar thermal power generation equipment and gas turbines. This system effectively mitigates the inherent randomness associated with power generation due to weather conditions while simultaneously providing electric and heat loads. However, due to the difference in response speed of various power generation equipment, it is difficult to respond quickly as the strength of illumination and electricity-heat load demand change, seriously affecting the system's stability operation. This paper proposes an active disturbance rejection control (ADRC) method for the ISCC system considering the different response speeds of generation equipment. Firstly, the mathematical model of the ISCC system is established, in which the system's response speed is improved through the inertial power compensation method. Then, the ADRC method is used to reduce the disturbance caused by uncertain factors, such as solar radiation intensity and load demand change, to ensure the balance between electric and thermal power supply and demand. Finally, based on the measured weather data from National Renewable Energy Laboratory (NREL), the proposed method's performance is evaluated, compared with the hybrid H2/H∞ control method and the auto-coupling proportional integral differential (ACPID) control method. Comparison results show that the ADRC method has better control effectiveness and dynamic response performance, powerfully shortens the system stability time, and reduces overshoot.

Dynamic Surface-Based Adaptive Active Disturbance Rejection Control of Electrohydrostatic Actuators

The control accuracy and stability of the electrohydrostatic actuator (EHA) are directly impacted by parameter uncertainty, disturbance uncertainty, and non-matching disturbance, which negatively impacts aircraft rudder maneuvering performance and even results in rudder chatter. A dynamic surface-based adaptive active disturbance rejection control (DSAADRC) is proposed as a solution for these issues. It does this by developing a novel parametric adaptive law driven by the combination of tracking error, parameter estimation error, and state estimation error to estimate the unknown parameters, using three low-order ESOs to estimate and compensate the uncertain disturbances online, and employing a dynamic surface method to obtain the differential values of virtual control signals in the backstepping method to deal with non-matching disturbances. In this research, a Lyapunov stability analysis demonstrates that the method can achieve the position tracking accuracy of the EHA under time-varying external disturbances after first establishing an EHA dynamics model with nonlinearity and uncertainty, followed by the design of an adaptive active disturbance rejection control method based on dynamic surfaces for the uncertainties and perturbations. In contrast to control strategies like Robust Control (RC) and Adaptive Robust Control (ARC), simulation and experiment comparison shows that the method has stronger anti-disturbance under time-varying external disturbances.

Adaptive Optics Tip-Tilt Correction Based on Smith Predictor and Filter-Optimized Linear Active Disturbance Rejection Control Method.

A tip-tilt mirror (TTM) control method is designed to enhance the control bandwidth and ensure the rejection performance of the adaptive optics (AO) tip-tilt correction system. Optimized with the Smith predictor and filter, linear active disturbance rejection (LADRC) is adopted to achieve the tip-tilt correction. An AO tip-tilt correction experimental platform was built to validate the method. Experimental results show that the proposed method improves the control bandwidth of the system by at least 3.6 times compared with proportional-integral (PI) control. In addition, under the same control bandwidth condition, compared with the Smith predictor and proportional-integral (PI-Smith) control method, the system is more capable of rejecting internal and external disturbances, and its dynamic response performance is improved by more than 29%.

GPI observer-based active disturbance rejection control for a morphing quadrotor

Quadrotors are widely used in transportation, aerial photography, agricultural protection, and other important fields. Nevertheless, quadrotors with a fixed structure will face great challenges when crossing through or entering narrow spaces for operations. To improve quadrotor crossing ability in different environments, a morphing quadrotor is designed in this paper, and four servo motors are added to independently change four arm rotation angles. Meanwhile, the dynamic model and dynamic control allocation matrix are established. In addition, considering that the internal dynamic variation caused by morphologic changes and external disturbances may compromise system stability, a control method based on the generalized proportional integral (GPI) observer is proposed to increase the system robustness, and the corresponding stability analysis is provided. Finally, simulation results demonstrate the effectiveness of the proposed GPI observer-based active disturbance rejection control method.

Convergence analysis on a tracking differentiator used in active disturbance rejection control

This paper presents convergence analysis for a tracking differentiator of an active disturbance rejection control method which is widely applied but lacks theoretical analysis. Since a nonlinear piecewise function is used in the tracking differentiator, the convergence analysis is difficult for tracking errors. Convergence proof processes of the tracking differentiator are divided into three situations based on the nonlinear piecewise function. Tracking errors of the tracking differentiator are proved to be uniformly ultimately bounded considering three situations, and relationships between upper bounds of tracking errors and adjustment parameters are founded by a Lyapunov approach, which provides a basis for parameters adjustment. Finally, simulation and experiment results verify the effectiveness of the proposed convergence analysis.

Study on Fuzzy Sliding Mode Active Disturbance Rejection Control Method for Horizontal Vibration of High-Speed Elevator Car System

Study on Fuzzy Sliding Mode Active Disturbance Rejection Control Method for Horizontal Vibration of High-Speed Elevator Car System

Nonlinear active disturbance rejection control for deformable mirror

The disturbance in the adaptive optical system includes not only the low-frequency broadband disturbance but also the high-frequency narrow-band disturbance caused by the vibration of system components and atmospheric turbulence. A nonlinear active disturbance rejection control (NLADRC) method is proposed to solve the control problem of a deformable mirror under high-frequency narrow-band disturbance. This method does not completely depend on the mathematical model, and the algorithm structure is simple. The differential tracker flattens the abrupt part of the signal, and the extended state observer is used to estimate the disturbance in real time. Finally, the nonlinear control rate is used to compensate the disturbance. The simulation results show that compared with the classical PID control and the classical linear active disturbance rejection control, the NLADRC method can effectively improve the bandwidth of the control system and show good suppression performance against high-frequency narrow-band disturbance, and the system is more robust. Both in time domain and frequency domain, it can accurately track the system state, reduce the system delay and system error, and has better dynamic performance.

A Novel Active Disturbance Rejection Control of PMSM Based on Deep Reinforcement Learning for More Electric Aircraft

In this article, a novel active disturbance rejection control (ADRC) based on deep reinforcement learning (DRL) is proposed to improve the performance of permanent magnet synchronous motor (PMSM) for more electric aircraft (MEA). MEA motors have the requirements of safety and stability so that a new ADRC method is put forward based on the limitation of nonlinear error attenuation function of traditional ADRC. The flux weakening control model of PMSM is firstly established. Then the ADRC model is built and applied to the speed loop of the control system. In order to reduce the number of control parameters and the jitter of the control law, deep neural network is employed to replace the traditional control law. Markov decision process is integrated into the novel ADRC to establish DRL model. A method based on twin delayed deep deterministic (TD3) policy gradient algorithm is proposed to train the neural network and optimize the DRL model. Model predictive control and traditional ADRC are used as comparison algorithms. Simulation and experiments show the effectiveness and superiority of the proposed method.

Performance Analysis of Improved ADRCs for a Class of High-Order Processes With Verification on Main Steam Pressure Control

Several improved active disturbance rejection control (ADRC) methods, including input modified ADRC (MADRC), input delay ADRC (DADRC), Smith predictor-based ADRC (SPADRC) and Smith-like based ADRC (SLADRC), have been proposed to tackle <inline-formula><tex-math notation="LaTeX">$\bm {K/(Ts+1)^{n}}$</tex-math></inline-formula>-type high-order processes. This paper aims to investigate their control performance theoretically, such as the input disturbance rejection and measurement noise rejection capabilities. It is proved that these improved ADRCs with the same parameters have the same measurement noise rejection capability. Besides, quantitative tuning rules of MADRC and SLADRC are derived based on their desired dynamic equations. Compared with proportional-integral controller and regular ADRC, their effectiveness is verified by comparative simulations and experiments, where MADRC obtains the best control performance with good robustness. Finally, successful field applications of MADRC on the main steam pressure process further illustrate its application potential in complicated industrial processes.