Optimized linear active disturbance rejection control for pneumatic servo systems via least squares support vector machine

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.

The dual observation of periodic and aperiodic interferences cannot be balanced by traditional linear extended state observer (T-LESO). Therefore, the speed fluctuations caused by uncertain periodic and aperiodic interferences in the interior permanent magnet synchronous motor control system cannot be suppressed by the traditional linear active disturbance rejection controller. To resolve the aforementioned problem, an improved linear active disturbance rejection controller (I-LADRC) in which multifrequency quasi-resonant filtering decoupling linear extended state observer and generalized linear extended state observer (G-LESO) are cascaded is proposed. In this controller, the interference feedforward control method of T-LESO is first changed, the observer bandwidth <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ω_o</i> and controller bandwidth <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ω_c</i> in the transfer function based on the interference term are decoupled from each other, reducing the difficulty of parameter tuning. On this basis, a multifrequency quasi-resonant filter is embedded in the decoupled linear extended state observer (LESO), so that periodic interferences can be accurately observed. For G-LESO, a fourth-order LESO is adopted to enable more accurate observation of aperiodic high-order interferences. The outer loop controller based on I-LADRC is designed, and the correctness and effectiveness of this method are verified through experiments.

Hydrogen energy storage systems are becoming increasingly accepted owing to their environmental friendliness. The efficiency and performance of these systems largely depend on the attributes of their power electronic interface systems. Among the promising solutions is a multiport-isolated DC-DC converter with characteristics of reduced component count, fewer conversion stages, and galvanic isolation. However, this system presents a challenge due to its inherent cross-coupling effect, complicating precise control. To address this, linear active disturbance rejection control (LADRC) is a viable option, leveraging dynamic/disturbance properties observed by linear extended state observers. LADRC serves as a decoupling controller, mitigating the cross-coupling effect. However, LADRC has several gains, and selecting them can be a difficult task, often requiring manual tuning. To streamline this process, this paper proposes utilising particle swarm optimisation to determine the optimum gains of LADRC. By employing this approach, the implementation of LADRC is facilitated with reduced design efforts while ensuring effective decoupling control within the system. Simulations are conducted to validate the performance of the optimised gain LADRC.

The paper applies wavelet de-noising in linear active disturbance rejection control (LADRC). To decrease the noise in real time, the method of sliding window is designed. When the frequency and intensity of disturbance noise in the system are large, the control effect of LADRC will be reduced greatly. To solve that, the real-time de-noising algorithm is concatenated between the noisy output and the linear extended state observer (LESO). The results of simulations show that, in LADRC, the applied real-time de-noising algorithm is effective.

This paper presents a robustness study of a Linear Active Disturbance Rejection Control (LADRC) framework. A dynamic simulative study is carried out on a two-wheeled differential drive mobile robot (DDMR) velocity control. A dynamic model of the robot with actuators has been considered, including uncertain parameters and a coupling between the linear and angular velocities, and the two angular velocities, the robot motion is also a subject of external disturbances which can degrade the performance of classical controllers. However, In LADRC, the unmeasured dynamics and external disturbances are considered as an additional state variable, it is then estimated by a linear Extended State Observer (LESO) and compensated in the control law. The simulation results show the efficiency of proposed LADRC-based controller in the reduction of the effect of dynamic variations. The LADRC robustness is compared with a proportional-integral-derivative controller (PID). Better results in terms of disturbance rejection have been reported for the LADRC.

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.

It is difficult to establish an exact mathematical model for the induction motor and the robustness is poor of the vector control system using PI regulator. This paper adopts the linear active disturbance rejection controller (LADRC) to control inductor motor. LADRC doesn't need the exact mathematical model of motor and it can not only estimate but also compensate the general disturbance that includes the coupling items in model of motor and parameters perturbations by linear extended state observer (LESO), so the rotor flux and torque fully decouple. As a result, the performance is improved. To prove the above control scheme, the proposed control system has been simulated in MATLAB/SIMULINK, and the comparison was made with PID. Simulation results show that LADRC has better performance and robustness than PID.

Asynchronous motors are widely used in industry and agriculture because of their simple structure, low cost, and easy maintenance. However, due to the coupling and uncertain factors of the actual operation of the motor, a traditional controller cannot achieve a satisfactory control effect. A linear active disturbance rejection controller (LADRC), featuring good robustness and adaptability, was proposed to improve the control efficiency of a nonlinear, uncertain plant. A linear extended state observer (LESO) is the core part of a L. The accuracy of the observation of state variables and unknown disturbances is related to the control effect of the controller. The performance of a traditional LESO is not high enough, and thus an error differential is introduced by analyzing the principle of LESO to improve its observation performance. The improved LADRC applies to the vector speed control of the induction motor. Additionally, low-speed and high-speed no-load starting, sudden load, electromagnetic torque, and three-phase stator current of the induction motor was simulated using MATLAB (Developed by MathWorks in Natick, MA, USA, and dealt by MathWorks Software (Beijing) Co., Ltd. in Beijing, China). Theoretical analysis and simulation results show that the ADRC based on the improved linear expansion observer was better than the traditional linear ADRC in terms of the dynamic and static performance and robustness.

In the paper, a linear extended state observer (LESO) is designed for ship heading control with wave disturbance via linear active disturbance rejection control (LADRC). In frequency domain, the tracking ability and disturbance rejection capability of LESO has been analyzed in details. Furthermore, the tradeoff between the closed-loop stability and the system requirements, i.e., rudder, input actuator, can be achieved via parameter tuning, together with active disturbance filtering. Ship heading control is used to as a case study to prove the efficacy of the proposed LESO with simulation experiments.

The control strategy research of the time-delay system is a focused issue in the control field. In order to furthermore improve the performance of the first-order time-delay inertial system, firstly, a new Smith predictor structure is proposed, which solves the constraint that the conventional Smith predictor needs to match the actual object model. Secondly, the performance and parameter function of the new Smith predictor are discussed in theory to provide the basis for parameter tuning. Finally, a new Smith predictor combined with linear active disturbance rejection control (LADRC) is proposed to solve the problem that the two input signals of the linear extended state observer (LESO) are not synchronized on the time scale, and the stability of the new Smith + LADRC time-delay control system is proved theoretically for known and unknown controlled complex objects. Simulation analysis is conducted to verify the robustness of the proposed strategy under the condition of the different parameters. The results indicate that the proposed strategy has better performance than the conventional method in response speed, overshoot, adjustment time, and stability.

During orbital maneuvers, spacecraft attitude control is subjected to complex internal and external disturbances caused by factors such as thruster misalignment and mass uncertainties. In this paper, a rigid-flexible coupling dynamic model is developed, incorporating rigid-body translation, attitude rotation, and flexible solar-panel vibrations. A linear active disturbance rejection controller (LADRC), constructed on the basis of a linear extended state observer (LESO), is then designed. By analyzing the frequency-domain characteristics of the LESO, the influence of observer bandwidth on disturbance estimation is clarified. Simulation results show that, compared with conventional PID control, the proposed LADRC achieves faster attitude-error convergence under thrust-eccentric disturbances, significantly improving attitude stability and disturbance-rejection performance during orbital maneuvers.

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.

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.

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.

In order to improve the dynamic response speed and the steady-state performance of the DC side bus voltage of the wind power grid-connected inverter, a mathematical model of a typical three-phase voltage type PWM (Pulse Width Modulation, PWM) grid-connected inverter was established, and its traditional voltage-current double closed loop with proportional-integral control method was analyzed. Then a second-order linear active disturbance rejection controller that does not depend on system model information was designed to replace the traditional voltage outer loop proportional-integral controller, thus a new double closed-loop control structure was formed to control it. The frequency domain theory was used to analyze the convergence of the third-order linear extended state observer and the influence of the total disturbance on the performance of the third-order linear extended state observer. The parameter tuning scheme of the designed controller was given. Finally, the 1.5 MW direct-driven permanent magnet wind power generation system was built in the Matlab/Simulink software and the control effects of the two control modes under different working conditions are compared. The simulation results show that the control scheme designed in this paper is superior to the traditional proportional-integral controller which has good anti-interference characteristics and robustness. Especially it has a good stability effect on DC side bus voltage fluctuations.