A Building Crack Detection UAV System Based on Deep Learning and Linear Active Disturbance Rejection Control Algorithm

The frequency regulation has become one of the major subjects in microgrid power system due to the complexity structure of microgrid. In order to solve this problem, this paper proposes an improved linear active disturbance rejection control algorithm (ILADRC) that can significantly improve system performances through changing feedback control law to reduce the disturbance estimation error of extended state observer. Then, the proposed algorithm is employed in microgrid power system frequency regulation problem, which demonstrates its effectiveness. The parameters of controllers are optimized by particle swarm optimization (PSO) algorithm improved by genetic algorithm (GA). Simulations with different disturbances including sudden and stochastic change of load demand and wind turbine generation are carried out in comparison with previous studies. And robustness testing based on Monte-Carlo approach also shows better performance. So frequency stability of microgrid power system can be well guaranteed by proposed control algorithm.

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.

Permanent magnet synchronous motor (PMSM) is widely used in aerospace, new energy electric vehicles and other fields. In order to solve the problems of poor parameter adaptability and poor disturbance resistance in the PMSM speed control system with traditional PI control algorithm, a linear active disturbance rejection control (LADRC) algorithm for PMSM is proposed in this paper. Then, the physical meaning of each parameter in LADRC and the setting scheme are summarized according to the phenomena encountered in the experimental. Simulation and experiment show that the proposed scheme can improve the robustness of PMSM speed control system.

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 Pointing Acquisition Tracking (PAT) technology, as a powerful guarantee for fast establishment and stable communication of wireless laser communication links, is the key to improve the practicality of shipboard wireless laser communication. In this paper, the initial pointing method of the shipboard laser communication terminal is designed by using the position and attitude information obtained from the GPS/INS module. Since the system optical relationship varies with the coarse tracking mechanism attitude during tracking, the optical decoupling model from the coarse tracking mechanism to the CMOS detector is measured using the optical matrix method. On this basis, the robust linear active disturbance rejection control (LADRC) algorithm is used for spot tracking. Designing the acquisition and tracking experiment of maritime laser communication, using the initial pointing algorithm to obtain the initial pointing angle of the antenna boresight and successfully capture the beacon light. Experiments show that the tracking peak error of coarse tracking is around 40urad, and the standard deviation is below 20urad. the tracking peak error of fine tracking is around 15urad, and the standard deviation is below 10urad. The experimental data show that the tracking algorithm meets the requirements of stable, reliable and high-precision tracking.

To enhance the motion flexibility and environmental adaptability of underwater robots, this study proposes a novel design, Seeker-M, inspired by the locomotion mechanism of the mantis shrimp. The robot imitates the mantis shrimp's multi-pleopod swimming mode and has multi-modal locomotion ability. The robot features a multifunctional flexible spine capable of active bending (maximum angle of 30°) and dynamic center of gravity adjustment (up to 30% of body length). A pitch control system is developed based on this adjustable structure, employing the linear active disturbance rejection control (LADRC) algorithm. Experimental results demonstrate that the LADRC algorithm maintains robust attitude stability under disturbances from pleopod motion, offering an effective approach for underwater attitude control in complex environments.

Self-tuning Control of Manipulator Based on Fuzzy Linear Active Disturbance Rejection Control and Particle Swarm Optimization Algorithm

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.

Nonlinear active disturbance rejection control is much more effective than linear active disturbance rejection control in tolerance to uncertainties and disturbances. However, it brings a great challenge for theoretical analysis, especially the stability analysis. This article proposes a linear matrix inequality method to analyze the absolute stability of generalized nonlinear active disturbance rejection control form which contains multiple nonlinearities with different parameters in both extended state observer and control law for single-input single-output systems. The generalized nonlinear active disturbance rejection control algorithm and the single-input single-output system are transformed into a direct multiple-input multiple-output Lurie system. A sufficient condition to determine its absolute stability based on linear matrix inequality method is given. The Lyapunov function of the Lurie system exists when the group of linear matrix inequalities is feasible. The free parameters and coefficients in Lyapunov function are given by the solution of these linear matrix inequalities. The electromagnetic valve actuator system in camless engine is presented as an application to illustrate how to perform the proposed method for absolute stability analysis and the stable region of parameter perturbations is obtained via the method. Simulation results show that the linear matrix inequality–based method is convenient and effective to determine whether the closed-loop system is absolutely stable.

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.

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.

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 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.