Research on Active Disturbance Rejection Control Based on Position Disturbance Electro-hydraulic Servo Force

Remotely operated vehicles (ROVs) face challenges in achieving optimal trajectory tracking performance during underwater movement due to external disturbances and parameter uncertainties. To address this issue, this paper proposes a position and attitude control strategy for underwater robots based on a reinforcement learning active disturbance rejection controller. The linear active disturbance rejection controller has achieved satisfactory results in the field of underwater robot control. However, fixed-parameter controllers cannot achieve optimal control performance for the controlled object. Therefore, further exploration of the adaptive capability of control parameters based on the linear active disturbance rejection controller was conducted. The deep deterministic policy gradient (DDPG) algorithm was used to optimize the linear extended state observer (LESO). This strategy employs deep neural networks to adjust the LESO parameters online based on measured states, allowing for more accurate estimation of model uncertainties and environmental disturbances, and compensating the total disturbance into the control input online, resulting in better disturbance estimation and control performance. Simulation results show that the proposed control scheme, compared to PID and fixed parameter LADRC, as well as the double closed-loop sliding mode control method based on nonlinear observers (NESO-DSMC), significantly improves the disturbance estimation accuracy of the linear active disturbance rejection controller, leading to higher control precision and stronger robustness, thus demonstrating the effectiveness of the proposed control strategy.

Proportional Derivative Integral (PID) controllers are extensively used in most of the industrial applications. But often, PID frame work fails to address some serious issues like susceptibility to noise, instability due to integral term etc. On the other hand Active Disturbance Rejection Control (ADRC) addresses these issues quite successfully. The problem considered in this work is to control Automatic Voltage Regulator (AVR) with Linear ADRC (LADRC) under presence of plant parameter uncertainties and sudden load variations.A fifth-order Extended State Observer (ESO) was designed which estimates generalized disturbance which includes both system uncertainties and external disturbances. This information is used to actively cancel the effects of disturbances. The effectiveness of LADRC scheme has been illustrated by comparing with conventional PID tuning method in the presence of plant parameter and sudden load variations. Further to study the frequency response characteristics of control system, transfer function of LADRC has been derived. From the simulations it can be observed that there is significant improvement in system response which can be reconfirmed from the frequency response analysis.

The series manipulator of the demolition robot has different working postures and large self-weight so that the bearing mass of the joint hydraulic cylinder is a variable value, and the change of mass affects the dynamic characteristics of the valve-controlled hydraulic cylinder system. In this paper, an equivalent mass estimation method of the big-arm joint hydraulic cylinder is given, and the natural frequency range of the big-arm hydraulic cylinder-load system is calculated. In order to suppress the influence of the change of the natural frequency and external disturbance of the hydraulic cylinder on the system, the linear active disturbance rejection control is adopted in the closed-loop position control. The simulation results show that the change of load mass of the joint hydraulic cannot be ignored when designing the joint position controller of multi-joint hydraulic manipulator. And the simulation tests prove that the linear active disturbance rejection control strategy keeps good dynamic characteristic and steady-state accuracy for the change of natural frequency and external disturbance of hydraulic cylinder and has good tracking performance for periodic sinusoidal signal. Linear active disturbance rejection control is robust in the variable mass control of the manipulator and meets the requirements of the joint position control of the heavy-duty hydraulic manipulator.

Linear active disturbance rejection control (ADRC) is known for its simplicity and its performance in disturbance attenuation. Currently, tuning of linear ADRC is via the bandwidth idea proposed in [1]. It is first shown that there are some limitations using only two bandwidths to tune the linear ADRC controllers. In this paper, tuning of linear ADRC with extra model dynamic information is investigated. It is shown that the available model dynamic information used in generalized ADRC (GADRC) can be realized by the observer gain and the controller gain of the conventional linear ADRC, thus extends the applicability of conventional linear ADRC. Simulation results show that with extra model dynamic information incorporated, by tuning the observer gain and controller gain, the performance of a conventional linear ADRC can indeed be improved, especially for non-minimum phase and time-delayed processes.

Two new active disturbance rejection control (ADRC) structures for nonlinear systems are introduced: a locally linearized variant and a fully nonlinear formulation. Both approaches incorporate model knowledge to enhance performance but differ in how nonlinear dynamics are integrated into the control and observer design. The first proposed structure employs a state-dependent local approximation of the nonlinear model to generate dynamic controller and observer gains, aiming to balance robustness and accuracy. In contrast, the second one directly embeds the full nonlinear dynamics into both the control law and extended state observer, tightly coupling performance to model fidelity. The proposed methods were experimentally validated on a magnetic levitation system, known for its strong nonlinearity, and compared with a classical linear ADRC (LADRC). Furthermore, stability analysis of the methods was conducted using Lyapunov theory. Results show that the linearized structure consistently improves regulation performance over LADRC and, in most cases, achieves similar results to nonlinear ADRC with lower computational effort. However, the performance of the nonlinear approach may degrade under modeling inaccuracies and limited observer bandwidth. This study highlights that the way model information is integrated–rather than its level of detail–has a decisive impact on control quality. Finally, practical design guidelines are provided to assist in selecting an appropriate ADRC structure for nonlinear applications where robustness, computational efficiency, and limited model knowledge must be balanced.

Aiming at the problem of anti-swing and positioning of underactuated crane, this paper proposes a control strategy of underactuated bridge crane based on Linear Active Disturbance Rejection Control and controller parameter optimization method. Distinguished from other conventional control strategies of bridge crane, this method does not require any approximate decoupling or linearization of the crane model and allows the model to have some certain uncertainty, friction and air resistance of the system are also considered. At the same time, for the parameter tuning problem of the sensors, the bird swarm optimization algorithm is applied to optimize the parameters. And the excellent control performance of this method has been proved by simulation.

To improve the robustness and the anti-disturbance of control system, regulate its stiffness, a scheme concluding linear active disturbance rejection controllers for pneumatic servo system is proposed. Two linear active disturbance rejection controllers are designed respectively to track the motion and pressure reference. The design of a linear active disturbance rejection controller is independent of precisely mathematical model of the system. The extended state observer can track successfully the states and extended state of the system, and it is possible to realize the states feedback and handle the model uncertainty and compensate external disturbance. The simulation results show that pneumatic servo system based on linear active disturbance rejection controllers is robust against modeling uncertainty and external disturbances. The dynamic performance of the system using linear active disturbance rejection controllers also can be improved as well.

Owing to ship's high inertia, strong time lag, non-linearity and under-actuated characteristics, as well as sustaining external disturbances frequently, designing a high performance ship tracking controller is still one of the most important research topics of ship motion control. Active Disturbance Rejection Control (ADRC) is proved to be very effective control method because it is independent of mathematical model of the plant and can compensate the internal and external disturbances dynamically. This paper investigates the applications of ADRC in ship motion tracking control and presents the design method of ADRC controller appropriate for ship tracking control. Firstly, ship motion mathematical model is introduced briefly and the linear ADRC (LADRC) is analyzed. Then considering the nonlinear ship track design model as a third order plant after utilizing variable substitution, a LADRC controller is designed by using fourth order linear extended state observer (LESO). At last, the simulation is performed. Simulation results show that the controller has a good tracking performance and disturbance rejection ability and is robust to the ship motion nonlinear characteristic and the external disturbances. The tracking process is fast, smooth and minor energy consumption.

The stability of the boiler’s main steam temperature is very important for the safe operation of the unit. At present, the mainstream PID control scheme is simple to use and convenient to set, but it cannot accomplish a acceptable ascendancy effect in the face of the main steam temperature control structure; with a long time delay, large inertia. In view of this situation, first of all, this paper introduces the linear active disturbance rejection control (LADRC) technology in a steam temperature control structure. The main loop adopts the linear active disturbance rejection controller and the subloop adopts the P-controller. Then, the particle swarm optimization algorithm is improved and used to modify the parameter of the LADRC, so that the LADRC system adjusted according to the theory can better complete the control task. Finally, a simulation to control the temperature is given, and the results show that the LADRC control system can track quickly and stably; in addition, as against with this traditional PID control strategy, it can achieve strong anti-interference performance.

Active disturbance rejection control for nanopositioning: A robust U-model approach

An attitude decoupling controller based on linear active disturbance rejection control (LADRC) is designed for small quadrotor aircraft, considering the problems existing in the controller based on active disturbance rejection control (ADRC), such as complicated design and parameters tuning difficulties in project implementation. First, the nonlinear and couple model of small quadrotor aircraft were established, and the LADRC was introduced, which described the principles of the ability of decoupling rejection control for multiple-input and multiple-output (MIMO) system and tuning method, then the model was decoupled. After that, the attitude controller based on second-order LADRC is designed and parameters is turned according to the desired settling time. F. Finally, the simulation test of the design was carried out. The simulation results indicate that the designed controller has strong robustness and anti-disturbance performance, and does not have accurate models. Moreover, there is only one parameter needs tuning in this controller, which makes the design easy to be realized and shows great engineering value.

It is unquestionably difficult to achieve precise path-following control for a parafoil system while taking sideslip angle effect into account. To address this challenge and enhance the robustness and flexibility of tracking control, this study presents an improved active disturbance rejection control (IADRC) strategy for parafoil path following based on the surge-guided line-of-sight (SGLOS) guidance law and the multi-strategy marine predator algorithm (MSMPA) optimization. Firstly, a guidance law is designed that simultaneously utilizes surge speed and heading angle for guidance. Then, IADRC is devised to enhance stability by mitigating observational errors from the extended state observer using fal function filters and phase predictions for pre-smoothing sideslip angles as well as abrupt yaw angle fluctuations. Additionally, a controller parameter tuning approach based on the improved MSMPA is proposed. Finally, the simulation results show that this strategy could effectively overcome the influence of wind field disturbances and achieve accurate path following control. Compared with the traditional PID control and linear active disturbance rejection control (LADRC), this method has a higher tracking accuracy and better robustness.

This paper concentrates on the design problem of linear active disturbance rejection control (LADRC) for uncertain systems, whose order and parameters are unknown. In general, LADRC has diversified structural forms due to different order and parameters selection. To clarify the prerequisites for constructing the LADRC strategy, a Laguerre-based LADRC (LLADRC) method is proposed, which provides controller design guidance for systems with unknown models by capturing the impulse response. Then, intensive attention is focused on establishing internal stability conditions of the feedback system and parameter tuning rules of the prescribed controller. To gain a better understanding, the internal correlation between LLADRC and standard LADRC of the same order is analyzed. It is shown that observer and controller gains of the standard LADRC can be tuned via a workable LLADRC to achieve better control performance. Finally, a numerical example and an application design of DC motor speed control are studied, both of which demonstrate the feasibility and validity of the proposed method.

The performance of proton exchange membrane fuel cells is very sensitive to temperature. The electrochemical reaction results directly in temperature variations in the proton exchange membrane fuel cell. Ensuring effective temperature control is crucial to ensure fuel cell reliability and durability. This paper uses active disturbance rejection control in the thermal management system to maintain the operating temperature and the stack inlet and outlet temperature difference at the set value. First, key cooling system modules such as expansion tanks, coolant circulation pumps and radiators based on Simulink were built. Then, physical modeling and simulation of the fuel cell cooling system was carried out. In order to ensure the effectiveness of the control strategy and reduce the parameter tuning workload, an active disturbance rejection control parameter optimization method using an elite genetic algorithm was proposed. When the optimized control strategy responds to input disturbances, the maximum overshoot of the system is only 1.23% and can reach stability again in 30 s, so the fuel cell temperature can be controlled effectively. Simulation results show that the optimized control strategy can effectively control the stack temperature and coolant temperature difference under the influence of stepped charging current without interference or with interference, and has strong robustness and anti-interference capability.

A linear extended state observer (LESO) can just estimate constant disturbances with no steady-state error. To estimate time-varying disturbances more actively and accurately, a phase optimisation law (POL) is proposed. Based on the POL, both a phase optimised extended state observer (POESO) and a phase optimised active disturbance rejection control (POADRC) are proposed. Estimation errors, estimation phases, and frequency response have been analysed and compared. The estimation phase of a POESO always leads the one of a LESO, and a POESO estimates slope disturbances with no steady-state error. Transfer functions of tracking, total disturbance and noise are also obtained. Ability of the POADRC and the linear active disturbance rejection control (LADRC) to cancel out the total disturbance or suppress noise, and their stable regions are also analysed and compared. Both frequency analyses and numerical results show that the POADRC estimates the time-varying disturbances and improve the closed-loop performance more effectively.