Dynamic velocity tracking control of differential-drive mobile robot based on LADRC

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 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.

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.

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.

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.

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.

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.

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.

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.

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

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.

In this paper, linear active disturbance rejection control (LADRC) is investigated for the load frequency control (LFC) systems with wind turbine. The wind power is considered as a stochastic load to the power grid. To compensate the stochastic disturbance with LADRC, we adopt a two-stage design method. First an LQG controller is designed to handle the stochastic nature of the load, then the intrinsic link between LQG and LADRC is analyzed and the designed LQG controller is converted to a conventional LADRC so that the LADRC maintains the same property of rejecting stochastic disturbance with the LQG controller. Simulation results show that the designed LADRC with the proposed method can damp the stochastic load disturbance very well.

To enhance the control performance and improve the disturbance rejection capability of the manipulator, a Linear Active Disturbance Rejection Control (LADRC) method with self-tuning parameters is proposed, based on the improved dung beetle optimizer (LCDBO). LADRC can estimate and compensate for the unmodeled dynamics and external disturbances in the system as a total disturbance. However, its parameters are strongly coupled and difficult to tune. Therefore, this paper introduces the improved dung beetle optimizer. Lévy flight and Cauchy mutation strategies are incorporated into the standard dung beetle optimizer (DBO) to further boost the optimizer’s performance and realize the optimal adjustment of the LADRC parameters. Applied to the manipulator trajectory tracking control problem, the LCDBO algorithm achieves a faster convergence speed and higher solution precision compared to the original DBO algorithm. When the controller parameters optimized by the LCDBO algorithm are applied to the manipulator trajectory tracking problem with disturbance torques, it results in high trajectory tracking accuracy and excellent disturbance rejection performance.

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.