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A switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.

The controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.

The switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.

A high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.

This solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.

Omnidirectional mobile robots with a special type of wheel structure can realize flexible motion with all three degrees of freedom in a plane. But the driving method brings large disturbance, which affects motion accuracy and stability. This study aims to improve the motion control accuracy of the omnidirectional mobile platform with MY3 wheels (MY3-OMR), a new fuzzy active disturbance rejection control (FADRC) method with adaptivity is proposed.

Based on the basic mechanical structure and drive characteristics of MY3-OMR, the dynamics model of the system is established. The linear active disturbance rejection control (LADRC) system is designed to reduce the interference of nonlinear factors in this dynamics model. A fuzzy controller is introduced to realize the online adjustment of the parameters of the LADRC, which further improves the anti-disturbance performance of the system.

The control method proposed in this paper is compared and analyzed with other methods by simulation and experiment. Results show that the proposed method has better tracking and robustness, which effectively improves the control accuracy of trajectory tracking of MY3-OMR.

A FADRC method with adaptivity is proposed by combining fuzzy control and LADRC. The motion accuracy and anti-interference ability of the MY3-OMR are improved by this control method, which lays a foundation for the subsequent application of MY3-OMR.

An active disturbance rejection controller (ADRC) based on model compensation is proposed in this paper. The method should first be taken a nominal model of the robot to compensate. Subsequently, the uncertain external disturbance is estimated and compensated is used an expansion state observer (ESO) in real time, which can reduce the estimating range of observation for ESO. The purpose of this paper is to suggest a novel method to improve the system tracking performance, as well as the dynamic and static performance index.

A welding robot is a complicated system with uncertainty, time-varying, strong coupling and a nonlinear system; it is more complex as if it is used in an underwater environment, and it is difficult to establish an accurate dynamic model for an underwater welding robot. Aiming at the tracking control of an underwater welding robot, it is difficult to achieve the control performance requirements by the conventional proportional integral derivative method to realize automatic tracking of the seam.

The simulation experiment is carried out by MATLAB/Simulink, and the application experiment is recorded. The experimental results show that the control method is correct and effective, and the system’s tracking performance is stable, and the robustness and tracking accuracy of the system are also improved.

The seam gets plumper and smoother, with better continuity and no undercut phenomenon.

The purpose of this study is to improve the control performance of wind energy conversion systems (WECSs) by proposing a new sensorless, robust control strategy based on a Smith predictor active disturbance rejection control (SP-ADRC) associated with a speed/position estimator.

The estimator consists of a sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the permanent magnet synchronous generator (PMSG) rotor position and speed. At the same time, the SP-ADRC is applied to the speed control loop of the variable-speed WECS control system to adapt strongly to dynamic characteristics under parameter uncertainties and disturbances.

Numerical simulations are conducted to evaluate the speed tracking performances under various wind speed profiles. The results show that the proposed sensorless speed control improves the accuracy of rotor speed and position estimation and provides better power tracking performance than a regular ADRC controller under fast wind speed variations.

This paper offers a new approach for designing sensorless, robust control for PMSG-based WECSs.

A new sensorless, robust control is proposed to improve the stability and tracking performance of PMSG-based WECSs. The SP-ADRC control attenuates the effects of parameter uncertainties and disturbances and eliminates the time-delay impact. The sensorless control design based on SMO and PLL improves the accuracy of rotor speed estimation and reduces the chattering problem of traditional SMO. The obtained results support the theoretical findings.

This paper aims to propose and verify an improved cascade active disturbance rejection control (ADRC) scheme based on output redefinition for hypersonic vehicles (HSVs) with nonminimum phase characteristic and model uncertainties.

To handle the nonminimum phase characteristic, a tuning factor stabilizing internal dynamics is introduced to redefine the system output states; its effective range is determined by analyzing Byrnes–Isidori normalized form of the redefined system. The extended state observers (ESOs) are used to estimate the uncertainties, which include matched and mismatched items in the system. The controller compensates observations in real time and appends integral terms to improve robustness against the estimation errors of ESOs.

Theoretical and simulation results show that the stability of internal dynamics is guaranteed by the tuning factor and the tracking errors of external commands are globally asymptotically stable.

The control scheme in this paper is expected to generate a reliable way for dealing with nonminimum phase characteristic and model uncertainties of HSVs.

In the framework of ADRC, a concise form of redefined outputs is proposed, in which the tuning factor performs a decisive role in stabilizing the internal dynamics of HSVs. By introducing an integral term into the cascade ADRC scheme, the compensation accuracy of matched and mismatched disturbances is improved.

This study aims to construct a novel maximum power tracking control system for the direct drive permanent magnet synchronous generator (PMSG) of the wind energy conversion system (WECS) to solve the following problems: how to effectively eliminate the system’s model parameter disturbances and speed up the dynamic performance of the system; and how to eliminate harmonics in WECS under different wind speeds.

To obtain the maximum output power of PMSG at WECS under different wind speeds, the following issues should be considered: (1) how to effectively eliminate the system’s model parameter disturbances and speed up the dynamic performance of the system; and (2) how to suppress system harmonics. For Problem 1, adding d–q compensation factors to active disturbance rejection control (ADRC) for the current loop realizes the d–q axis decoupling control, which speeds up the dynamic performance of the system. For Problem 2, the resonant controller is introduced into the ADRC for the current loop to suppress harmonic current in WECS under different wind speeds.

The simulation results demonstrate that the proposed control method is simpler and more reliable than conventional controllers for maximum power tracking.

Compared with traditional controllers, the proposed controller can speed up the dynamic performance of the system and suppress the current harmonic effectively, thus better achieving maximum power tracking.

Accurate glide path tracking is vital to the automatic carrier landing task of unmanned aerial vehicle (UAV). The purpose of this paper is to develop a reliable flight controller that can simultaneously deal with external disturbance, structure fault and actuator fault.

The automatic carrier landing task is resolved into the glide path tracking problem and attitude tracking problem. The disturbance observer-based adaptive sliding mode control scheme is proposed for system stabilization, disturbance rejection and fault tolerance.

Both the Lyapunov method and exemplary simulations can prove that the disturbance estimation error and the attitude tracking error converge in finite time in the presence of external disturbances and various faults.

The presented algorithm is testified by a UAV automatic carrier landing simulation, which shows the potential of practical usage.

The barrier function is introduced to adaptively update both the sliding mode observer gain and sliding mode controller gain, so that the sliding mode surface could converge to a predefined region without overestimation. The proposed flight controller ensures a secure carrier landing task.

The purpose of this paper is to design a third-order linear active disturbance rejection controller (LADRC) to improve the response characteristics and robustness of the electrohydraulic servo system.

The LADRC was designed by replacing the nonlinear functions in each part of ADRC with linear functions or linear combinations, and the parameters of each part of the LADRC were connected with their bandwidth through the pole configuration method to reduce the required tuning parameters, and used an improved grey wolf optimizer to tune the LADRC parameters.

The anti-interference control simulation and experiment on the LADRC, ADRC and proportion integration differentiation (PID) were carried out to test the robustness, anti-interference ability and superiority of the designed LADRC. The simulation and experiment results showed that the LADRC control and anti-interference control had excellent performance, and because of its simple structure and fewer parameters, LADRC was easier to implement and had a better control effect and anti-interference.

For the problems of parameter perturbation, unknown interference and inaccurate model in the electrohydraulic position servo system, the designed third-order LADRC has good tracking accuracy and anti-interference, has few parameters and is conducive to promotion.

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

Quadrotors have been applied in various fields. However, because the quadrotor is subject to multiple disturbances, consisting of external disturbances, actuator faults and parameter uncertainties, it is difficult to control the unmanned aerial vehicle (UAV) to achieve high-precision tracking performance. This paper aims to design a safety controller that uses observer and neural network method to improve the tracking performance of UAV under multiple disturbances. The experiments prove that this method is effective.

First, to actively estimate and compensate the synthetic uncertainties of the system, a finite-time extended state observer is investigated, and the disturbances are transformed into the extended state of the system for estimation. Second, an adaptive neural network controller that does not accurately require the dynamic model knowledge is designed based on the estimated value, where the weights of the neural network can be dynamically adjusted by the adaptive law. Furthermore, the finite-time bounded convergence of the proposed observer and the stability of the system are proved through homogeneous theory and Lyapunov method.

The figure-“8” climbing flight simulation and real flight experiments illustrate that the proposed safety control strategy has good tracking performance.

This paper proposes the safety control structure of the UAV, which combines the extended state observer with the neural network method. Numerical simulation results and actual flight experiments demonstrate the effectiveness of the proposed control strategy.