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This paper aims to study a disturbance rejection controller to improve the anti-interference capability and the position tracking performance of airborne radar stabilized platform that ensures the stability and clarity of synthetic aperture radar imaging.

This study proposes a disturbance rejection control scheme for an airborne radar stabilized platform based on the active disturbance rejection control (ADRC) inverse estimation algorithm. Exploiting the extended state observer (ESO) characteristic, an inversely ESO is developed to inverse estimate the unmodeled state and extended state of the platform system known as total disturbances, which greatly improves the estimation performance of the disturbance. Then, based on the inverse ESO result, feedback the difference between the output of the tracking differentiator and the inverse ESO result to the nonlinear state error feedback controller (NLSEF) to eliminate the effects of total disturbance and ensure the stability of the airborne radar stabilized platform.

Simulation experiments are adopted to compare the performance of the ADRC inverse estimation algorithm with that of the proportional integral derivative controller which is one of the mostly applied control schemes in platform systems. In addition, classical ADRC is compared as well. The results have shown that the ADRC inverse estimation algorithm has a better disturbance rejection performance when disturbance acts in airborne radar stabilized platform, especially disturbed by continuous airflow under some harsh air conditions.

The originality of this paper is exploiting the ESO characteristic to develop an inverse ESO, which greatly improves the estimation performance of the disturbance. And the ADRC inverse estimation algorithm is applied to ameliorate the anti-interference ability of the airborne radar stabilization platform, especially the ability to suppress continuous interference under complex air conditions.

This paper aims to improve the anti-interference ability of the airborne radar stabilization platform, especially the ability to suppress continuous disturbance under complex air conditions to ensure the clarity and stability of airborne radar imaging.

This paper proposes a new active disturbance rejection control (ADRC) strategy based on the cascade extended state observer (ESO) for airborne radar stabilization platform, which adopts two first-order ESOs to estimate the angular velocity value and the angular position value of the stabilized platform. Then makes the error signal which subtracts the estimated value of ESO from the output signal of the tracking-differentiator as the input signal of the nonlinear state error feedback (NLSEF), and according to the output signal of the NLSEF and the value which dynamically compensated the total disturbances estimated by the two ESO to produce the final control signal.

The simulation results show that, compared with the classical ADRC, the ADRC based on the cascade ESO not only estimates the unknown disturbance more accurately but also improves the delay of disturbance observation effectively due to the increase of the order of the observer. In addition, compared with the classical PID control and the classical ADRC, it has made great progress in response performance and anti-interference ability, especially in the complex air conditions.

The originality of the paper is the adoption of a new ADRC control strategy based on the cascade ESO to ameliorate the anti-interference ability of the airborne radar stabilization platform, especially the ability to suppress continuous interference under complex air conditions.

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.

The control of a quadrotor unmanned aerial vehicle (UAV) is a challenging problem because of its highly nonlinear dynamics, under-actuated nature and strong cross-couplings. To solve this problem, this paper aims to propose a robust control strategy, based on a concept of active disturbance rejection control (ADRC).

The altitude/attitude dynamics of a quadrotor is reformulated into the ADRC framework. Three distinct variations of the error-based ADRC algorithms, with different structures of generalized extended state observers (GESO), are derived for the altitude/attitude trajectory-following task. The convergence of the observation part is proved based on the singular perturbation theory. Through a frequency analysis and a quantitative comparison in a simulated environment, each design is shown to have certain advantages and disadvantages in terms of tracking accuracy and robustness. The digital prototypes of the proposed controllers for quadrotor altitude and attitude control channels are designed and validated through real-time hardware-in-the-loop (HIL) co-simulation, with field-programmable gate array (FPGA) hardware.

The effects of unavailable reference time-derivatives can be estimated by the ESO and rejected through the outer control loop. The higher order ESOs demonstrate better performances, but with reductions of stability margins. Time-domain simulation analysis reveals the benefits of the proposed control structure related to classical control approach. Real-time FPGA-based HIL co-simulations validated the performances of the considered digital controllers in typical quadrotor flight scenarios.

The conducted study forms a set of practical guidelines for end-users for selecting specific ADRC design for quadrotor control depending on the given control objective and work conditions. Furthermore, the paper presents detailed procedure for the design, simulation and validation of the embedded FPGA-based quadrotor control unit.

In light of the currently available literature on error-based ADRC, a comprehensive approach is applied here, which includes the design of error-based ADRC with different GESOs, its frequency-domain and time-domain analyses using different simulation of UAV flight scenarios, as well as its FPGA-based implementation and testing on the real hardware.

The characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To improve the anti-interference performance of spherical robots in practical engineering, this paper proposes a spherical robot motion controller based on auto-disturbance rejection control (ADRC) with parameter tuning.

This paper considers the influences of the spherical shell, internal frame and pendulum on the movement of the spherical robot during the rotation to establish the multi-body dynamics model of the XK-I spherical robot. Due to the serious coupling problem of the dynamic model, the motion control state equation is constructed using linearization and decoupling. The XK-I spherical robot PSO-ADRC motion controller with parameter tuning function is designed by combining the state equation with the particle swarm optimization (PSO) algorithm. Finally, experiments are performed to evaluate the feasibility of PSO-ADRC in an actual case compared to ADRC, PSO-PID and PID.

By analyzing the required time to reach the expected value, the control stability and the fluctuation range of the standard deviation after reaching the expected value, the superiority of PSO-ADRC to ADRC, PSO-PID and PID is demonstrated in terms of the speed and anti-interference ability.

The proposed method can be applied to the robot control field.

A parameter-tuning method for auto-disturbance-rejection motion control of the spherical robot is proposed. According to the experimental results, the anti-interference ability of the spherical robot moving on uneven ground is improved. Therefore, it provides a foundation for the autonomous environmental monitoring of the spherical robot equipped with sensors.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

A laser seeker is an important element in missile guidance and control systems, responsible for target detection and tracking. Its control is, however, a challenging problem due to complex dynamics and various acting disturbances. Hence, the purpose of this study is to propose a systematic design, tuning, analysis and performance verification of a nonlinear active disturbance rejection control (ADRC) algorithm for the specific case of the laser seeker system.

The proposed systematic approach of nonlinear ADRC application to the laser seeker system consists of the following steps. The complex laser seeker control problem is first expressed as a regulation problem. Then, a nonlinear extended state observer (ESO) with varying gains is used to improve the performance of a conventionally used linear ESO (LESO), which enables better control quality in both transient and steady-state periods. In the next step, a systematic observer tuning, based on a detailed analysis of the system disturbances, is proposed. The stability of the overall control system is then verified using a describing function method. Next, the implementation of the NESO-based ADRC solution is realized in a fixed-point format using MATLAB/Simulink and Xilinx System Generator. Finally, the considered laser seeker control system is implemented in discrete form and comprehensively tested through hardware-in-the-loop (HIL) co-simulation.

Through the conducted comparative study of LESO-based and NESO-based ADRC algorithms for the laser seeker system, the advantages of the proposed nonlinear scheme are shown. It is concluded that the NESO-based ADRC scheme for the laser seeker system (with appropriate parameters tuning methodology) provides better control performance in both transient and steady-state periods. The conducted multicriteria study validates the efficacy of the proposed systematic approach of applying nonlinear ADRC to laser seeker systems.

In practice, the obtained results imply that the laser seeker system, governed by the studied nonlinear version of the ADRC algorithm, could potentially detect and track targets faster and more accurately than the system based on the common linear ADRC algorithm. In addition, the article presents the step-by-step procedure for the design, field programmable gate array (FPGA) implementation and HIL-based co-simulation of the proposed nonlinear controller, which can be used by control practitioners as one of the last validation stages before experimental tests on a real guidance system.

The main contribution of this work is the systematic procedure of applying the ADRC scheme with NESO for the specific case of the laser seeker system. It includes its design, tuning, analysis and performance verification (with simulation and FPGA hardware). The novelty of the work is also the combination and practical realization of known theoretical elements (NESO structure, NESO parameter tuning, ADRC closed-loop stability analysis) in the specific case of the laser seeker system. The results of the conducted applied research increase the current state of the art related to robust control of laser seeker systems working in disturbed and uncertain conditions.

The purpose of this paper is to handle the problem of the radial disturbance caused by rotor mass unbalance and load change in a bearingless induction motor (BIM).

The active disturbance rejection controller (ADRC) is used to replace the traditional PI controller, and a cubic interpolation method is used to fit the nonlinear function of ADRC, so as to improve the control performance. Meanwhile, a disturbance observer is applied to the suspension system, and the observed disturbance acceleration is compensated to the suspension system in the form of current; thus, the suppression of the rotor radial disturbance is realized.

The proposed method can effectively suppress the radial disturbance of the rotor, meliorate the suspension performance of the motor and enhance the anti-interference ability of the system. Besides, it has excellent dynamic and static performance.

A radial disturbance control strategy of the BIM based on improved ADRC is proposed is to suppress the radial disturbance of the rotor. The improved ADRC is to enhance the control performance of the system, and the disturbance observer is designed to observe and compensate the disturbance.

This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.

This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.

The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.

The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.

This paper aims to mainly discuss how to suppress the disturbances accurately and effectively in the wind energy conversion system (WECS) of the direct drive surface mount permanent magnet synchronous generator (SPMSG).

The disturbances in wind energy conversion system have seriously negative influence on the maximum power tracking performance. Therefore, a model predictive control (MPC) method of model compensation active disturbance rejection control (ADRC) strategy in parallel connection is designed, which optimizes the speed tracking performance compared with the existing control strategy of MPC and ADRC in series connection. Based on the traditional ADRC, a multi parameter model compensation ADRC strategy is added to better estimate the disturbances. At the same time, a torque feedback strategy is added to compensate the disturbances caused by load torque and further optimize the speed loop tracking performance.

The simulation results show that the designed control method has advantages than the traditional control method in compensating the disturbances and tracking the maximum power more effectively.

The simulation results show that the designed control method is superior to the traditional proportional control method, which can better compensate the internal and external disturbances and track the maximum power more effectively.