A Novel Nonlinear Active Disturbance Rejection Controller for Speed Control of Electric Drives

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.

Nonlinear characteristics are very common in marine steam turbine, such as control input constraints and external disturbances. Based on the active disturbance rejection control (ADRC), an anti-windup scheme is proposed to eliminate the undesired effects of nonlinear characteristics in the control system. In this scheme, firstly, a method of setting parameter is designed for nonlinear active disturbance rejection control (NLADRC). Then, two kinds of anti-windup schemes are proposed in this paper for NLADRC in the presence of control input constraints and external disturbances. Finally, simulation study is carried out for a first order delay object with actuator constraints, simulation results show that both schemes can achieve good anti-windup performance. The method is further extended to marine steam turbine control, with simulation results demonstrating that both methods have their own advantages.

In this paper, an improved nonlinear active disturbance rejection control (INLADRC) approach is proposed for load frequency control of hybrid microgrid with communication delay. The INLADRC technique includes a nonlinear extended state observer (NESO) to estimate the system states and a nonlinear controller for the cancellation of the generalized disturbance acting on system. The effect of communication delay in the hybrid microgrid system is alleviated via the incorporation of an auxiliary structure that also restores the synchronization between the inputs of NESO. The efficacy of the proposed approach is validated via a comprehensive analysis, wherein step variations as well as random perturbations are considered in solar power, wind power and load demand. Further, the performance of proposed technique is also corroborated via consideration of real time solar and wind data. Moreover, the robustness of INLADRC technique is investigated in presence of parametric uncertainty, model-plant mismatch, delay time mismatch as well as varying communication delay. An extensive comparative analysis is a testimony to the effectiveness of INLADRC approach.

Two new active disturbance rejection control (ADRC) structures for nonlinear systems are introduced: a locally linearized variant and a fully nonlinear formulation. Both approaches incorporate model knowledge to enhance performance but differ in how nonlinear dynamics are integrated into the control and observer design. The first proposed structure employs a state-dependent local approximation of the nonlinear model to generate dynamic controller and observer gains, aiming to balance robustness and accuracy. In contrast, the second one directly embeds the full nonlinear dynamics into both the control law and extended state observer, tightly coupling performance to model fidelity. The proposed methods were experimentally validated on a magnetic levitation system, known for its strong nonlinearity, and compared with a classical linear ADRC (LADRC). Furthermore, stability analysis of the methods was conducted using Lyapunov theory. Results show that the linearized structure consistently improves regulation performance over LADRC and, in most cases, achieves similar results to nonlinear ADRC with lower computational effort. However, the performance of the nonlinear approach may degrade under modeling inaccuracies and limited observer bandwidth. This study highlights that the way model information is integrated–rather than its level of detail–has a decisive impact on control quality. Finally, practical design guidelines are provided to assist in selecting an appropriate ADRC structure for nonlinear applications where robustness, computational efficiency, and limited model knowledge must be balanced.

The control stability and accuracy of quad tiltrotor UAVs is improved when encountering external disturbances during automatic flight by an active disturbance rejection control (ADRC) parameter self-tuning control strategy based on a radial basis function (RBF) neural network. Firstly, a nonlinear flight dynamics model of the quad tiltrotor UAV is established based on the approach of component-based mechanistic modeling. Secondly, the effects of internal uncertainties and external disturbances on the model are eliminated, whilst the online adaptive parameter tuning problem for the nonlinear active disturbance rejection controller is addressed. The superior nonlinear function approximation capability of the RBF neural network is then utilized by taking both the control inputs computed by the controller and the system outputs of the quad tiltrotor model as neural network inputs to implement adaptive parameter adjustments for the Extended State Observer (ESO) component responsible for disturbance estimation and the Nonlinear State Error Feedback (NLSEF) control law of the active disturbance rejection controller. Finally, an adaptive attitude control system for the quad tiltrotor UAV is constructed, centered on the ADRC-RBF controller. Subsequently, the efficacy of the attitude control system is validated through simulation, encompassing a range of flight conditions. The simulation results demonstrate that the Integral of Absolute Error (IAE) of the pitch angle response controlled by the ADRC-RBF controller is reduced to 37.4° in comparison to the ADRC controller in the absence of external disturbance in the full-states mode state of the quad tiltrotor UAV, and the oscillation amplitude of the pitch angle response controlled by the ADRC-RBF controller is generally reduced by approximately 50% in comparison to the ADRC controller in the presence of external disturbance. In comparison with the conventional ADRC controller, the proposed ADRC-RBF controller demonstrates superior performance with regard to anti-disturbance capability, adaptability, and tracking accuracy.

This paper is concerned with the problems of robust switching control for near-space morphing vehicles (NMVs) with a large range of parameter uncertainty and external disturbance. For this purpose, a novel linear/nonlinear active disturbance rejection switching control method for the longitudinal dynamical model of NMVs based on the type-2 fuzzy logic system is proposed. Both linear active disturbance rejection control (LADRC) and nonlinear active disturbance rejection control (NLADRC) were designed for the velocity and altitude subsystems of NMVs. Then, the stability analysis of the cascade closed-loop and switching control systems were carried out. Furthermore, a switching control strategy based on the interval type-2 fuzzy logic system was developed, and the change rules of aerodynamic parameters with Mach number and angle of attack were examined. Finally, the experimental results validated the superior switching performance of the proposed control strategy.

This paper investigates the problem of stabilisation control of hydroelectric generating units. Firstly, the fully actuated system model of the linear hydraulic turbine is established by using the theory of fully actuated system. Then the control law is designed by using the direct parameterisation method, which can configure the closed-loop poles of the hydraulic turbine system expectation or region and ensure the stable operation of the hydraulic turbine regulating system with a small control gain. Finally, a nonlinear active disturbance rejection control method is proposed for the internal and external disturbances in the control of the fully actuated system. The simulation results demonstrate the effectiveness of the proposed control method.

ABSTRACTIn order to reduce the error and phase delay of the classical extended state observer (ESO) in estimating the system state and disturbance, in this paper, we combine ESO and tracking differentiator (TD) to construct a tracking differential extended state observer (TDESO). The observation error and observation speed of TDESO are also discussed. Then a nonlinear active disturbance rejection control system improved by TDESO for a linear plant is transformed into a Lurie system. Moreover, the circular criterion is used to analyse the absolute stability of the transformed Lurie system. Finally, TDESO is optimised and an improved linear state error feedback (PLSEF) is proposed to improve the rapidity of the system by using simulation and time domain analysis. And a second-order system is used to illustrate the performance of the proposed scheme. The simulation results show that our algorithm is effective.

To explore the brake control strategy more suitable for heavy-duty multi-axle special vehicles, a comparative analysis of anti-lock brake system (ABS) control strategies based on heavy multi-axle special vehicles was carried out. Use Matlab/Simulink to build a heavy-duty single-wheel anti-lock control system including dynamics model, slip rate model, tire model, braking model and controller model. The current main control strategies are adopted: no ABS, logic Threshold control, PID control, sliding mode variable structure control, fuzzy PID control and nonlinear active disturbance rejection control are simulated and compared.The research results show that: (1) The comparison of anti-lock braking control strategies for heavy-duty multi-axle special vehicles can be achieved simply and quickly through Matlab/Simulink heavy-duty single-wheel parametric model simulation; (2) Several control strategies have obvious advantages and disadvantages , Needs to be selected according to actual needs; (3) Comprehensive control strategy characteristics and special vehicle requirements, nonlinear auto disturbance rejection control is more suitable for heavy-duty multi-axle special vehicle braking control.

In this paper, a nonlinear active disturbance rejection control (ADRC) scheme is designed to control the pneumatic muscle actuator system. To reflect the impact of the sampling period, a continuous-discrete extended state observer (CDESO) is employed to estimate the so-called total disturbance, which describes the unmodeled complexities. Then, a nonlinear composite controller is used, where the estimates provided by the CDESO act as the feedforward term. The sufficient conditions to guarantee the stability of the CDESO and the overall controlled system are provided, respectively. Finally, a number of practical experiments are conducted on a pneumatic motion platform in order to verify the applicability of the proposed method.

Active disturbance rejection control (ADRC) is a relatively new but very practical technology, which shows much promise in replacing PID as industry workhorse with unmistakable advantage in performance and practicality. This paper mainly concerns with a problem of fundamental nature: the asymptotic stability of nonlinear ADRC based control system, and applies ADRC to the ball-beam system to check the presented methods and the performance of ADRC. Firstly, the general nonlinear ADRC algorithm is introduced; then the asymptotical stability problem is transformed into that of determining whether a matrix or interval matrix is Hurwitz; finally the results of theoretical analysis are verified in simulations and experiments using the ball-beam platform, demonstrating the convenience and effectiveness of the proposed methods, in addition to the good performance of ADRC.

The electric propulsion system is composed of permanent magnet synchronous motor equipped with propeller load. Due to the strong coupling of propeller speed and load torque, they considerably characterize dynamic response and disturbance suppression capabilities of the speed controller. Traditional nonlinear active disturbance rejection control (NADRC) is less effective in dealing with a step change of command speed and large disturbance. In order to provide faster response and stronger disturbance rejection potential, an enhanced NADRC strategy is proposed in this article. Initially, a linear extended state observer is applied to preliminary estimate the total disturbance. Then, using the designed weight regular function, this estimation is introduced into the nonlinear extended state observer with a cascade structure. The convergence, stability, and disturbance estimation performance of the proposed strategy are then analyzed. Finally, experimental validation is performed based on a constructed experimental platform. The results show that the proposed method reasonably enhances the speed response and antidisturbance performances.

With the rapid development of power electronic technology and the permanent magnet industry, Permanent Magnet Synchronous Motor (PMSM) is widely used in high-tech industries such as aerospace and transportation with excellent performance. However, PMSM is a time-varying system with multiple variables and strong coupling, making its control strategy rather complex. It is becoming increasingly important to improve the control strategy. Addressing the issues of easy saturation, poor robustness in PI controllers, and the inconvenience of injecting third-harmonic from the outside into the three-phase three-leg topology to enhance torque density, which leads to insufficient control precision in the PMSM servo system, a nonlinear active disturbance rejection controller (NLADRC) is proposed as the control strategy for the third-harmonic injection-based field-oriented control (FOC). Compared to the PMSM servo system without the injection of third-harmonic, the proposed system exhibits better disturbance rejection capability and higher torque density. Through simulations of the PMSM servo system with the injection of third-harmonic, the proposed control strategy is verified to have good response speed and control performance.

In this paper, a systematic procedure for controller design is proposed for a class of nonlinear underactuated systems (UAS), which are non-feedback linearizable but exhibit a controllable (flat) tangent linearization around an equilibrium point. Linear extended state observer (LESO)-based active disturbance rejection control (ADRC) is shown to allow for trajectory tracking tasks involving significantly far excursions from the equilibrium point. This is due to local approximate estimation and compensation of the nonlinearities neglected by the linearization process. The approach is typically robust with respect to other endogenous and exogenous uncertainties and disturbances. The flatness of the tangent model provides a unique structural property that results in an advantageous low-order cascade decomposition of the LESO design, vastly improving the attenuation of noisy and peaking components found in the traditional full order, high gain, observer design. The popular ball and beam system (BBS) is taken as an application example. Experimental results show the effectiveness of the proposed approach in stabilization, as well as in perturbed trajectory tracking tasks.

During the trajectory tracking of robotic manipulators, many factors including dead zones, saturation, and uncertain dynamics, greatly increase the modeling and control difficulty. Aiming for this issue, a nonlinear active disturbance rejection control (NADRC)-based control strategy is proposed for robotic manipulators. In this controller, an extended state observer is introduced on basis of the dynamic model, to observe the extend state of model uncertainties and external disturbances. Then, in combination with the nonlinear feedback control structure, the robust trajectory tracking of robotic manipulators is achieved. Furthermore, to optimize the key parameters of the controller, an improved particle swarm optimization algorithm (IPSO) is designed using chaos theory, which improves the tracking accuracy of the proposed NDRC strategy effectively. Finally, using comparative studies, the effectiveness of the proposed control strategy is demonstrated by comparing with several commonly used controllers.