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In this article, a new predictor‐based anti‐disturbance control scheme is proposed for discrete‐time systems with input delay subject to time‐varying uncertainties, by only using the system output measurement. A high‐order extended state observer is firstly constructed to simultaneously estimate the system state, unknown disturbance and its high‐order difference with specification. Two alternative designs of the system state and disturbance predictors are then presented to construct an advanced anti‐disturbance control scheme. The disturbance attenuation performance of the resulting closed‐loop system is quantitatively analyzed. Moreover, a matrix‐inequality‐based sufficient condition is established to evaluate robust stability of the closed‐loop system under time‐varying uncertainties. Finally, a benchmark example is adopted to demonstrate the effectiveness and advantages of the proposed control schemes over the existing methods. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to introduce a layered control strategy that aims to enhance the overall vehicle driving performance by implementing an advanced intelligent control method to minimise the spring mass acceleration fluctuation while ensuring sufficient suspension workspace to balance the contradiction between suspension workspace and vehicle driving comfort. Method: In this study, a hierarchical control framework is proposed, where the upper controller employs a constrained adaptive non-singular fast terminal sliding mode controller (NFESO-NFTSM) based on nonlinear filters and extended state observers to generate the target force, and the lower controller employs a constrained adaptive robust controller (ACARC) to accurately track the target force. Firstly, a specialised nonlinear filter is used to integrate the main control objective (spring mass acceleration) and the suspension workspace into a single controlled variable, and a Lyapunov function is used to ensure that the control variable converges to zero and stays within the permissible range. Secondly, the Extended State Observer (ESO) is utilised to estimate disturbances arising from the high level of model nonlinearity and uncertainty, and known disturbances are fed back into the ESO to improve the accuracy of disturbance estimation and compensation. Third, the output of the ESO is incorporated into the control law of a non-singular fast terminal sliding mode controller to enable real-time adaptation to the suspension system state. Finally, a constrained adaptive robust control technique is developed to address the nonlinearities and uncertainties in the electrohydraulic actuator parameters and the actuator saturation problem. Results: The layered control strategy combining nonlinear filtering with constrained adaptive non-singular terminal sliding mode control (NFESO-NFTSM-ACARC) based on extended state observer effectively balances the trade-offs between vehicle driving comfort and suspension workspace, significantly reduces the acceleration of the spring-loaded mass, and improves the overall driving comfort of the vehicle. Conclusion: The hierarchical control strategy proposed in this study provides an effective method for vehicle chassis design, which can significantly improve driving comfort while ensuring suspension workspace. [ABSTRACT FROM AUTHOR]

In this work, a fully actuated system (FAS) control scheme for the quadrotor UAV formation is designed. Deploying the FAS techniques, two controllers are designed for position and angle tracking so that the UAV formation is driven along the given trajectory with enhanced internal stability. Considering the scenario where the environment disturbances and actuator faults affect UAV systems, an extended state observer (ESO) is designed to estimate the uncertainty. Subsequently, the effect of the fault and uncertainty is compensated in the FAS controller to enhance the accuracy. As a result, the proposed formation coordination controller ensures that the UAV team completes the desired flight mission. According to the simulation results, the proposed method is more accurate and robust against the disturbance and fault with the accurate estimation compared with traditional methods. [ABSTRACT FROM AUTHOR]

In the textile industry, yarn tension control is directly related to product quality and production efficiency. Addressing the nonlinearities, uncertainties, and external disturbances encountered by tension control systems, this work initially establishes a mathematical model to describe the dynamic characteristics of yarn tension. Building upon this foundation, a yarn tension sliding mode control strategy based on an extended state observer (ESO) is proposed. This strategy employs the ESO to estimate and compensate for system uncertainties and disturbances. Subsequently, a sliding mode controller is designed for the compensated system, utilizing hyperbolic tangent functions for the reaching law, thereby enhancing the dynamic performance of the yarn tension control system. The stability of the controller is analyzed using Lyapunov theory. Recognizing the complexity of controller parameter tuning, an improved grey wolf optimizer (GWO) is introduced for further adjustment and optimization of the controller parameters. Finally, comparative simulations demonstrate that the designed controller maintains rapid response and high-precision dynamic characteristics even in the presence of external disturbances and noise. This underscores the promising application prospects of the proposed method in practical systems. [ABSTRACT FROM AUTHOR]

Numerous techniques have been proposed in the literature to improve the performance of high‐gain observers with noisy measurements. One such technique is the linear extended state observer, which is used to estimate the system's states and to account for the impact of internal uncertainties, undesirable nonlinearities, and external disturbances. This observer's primary purpose is to eliminate these disturbances from the input channel in real‐time. This enables the observer to precisely track the system states while compensating for the various sources of uncertainty that can influence the system's behaviour. So, in this paper, a novel nonlinear higher‐order extended state observer (NHOESO) is introduced to enhance the performance of high‐gain observers under noisy measurement conditions. The NHOESO is designed to observe the system states and total disturbance while eliminating the latter in real time from the input channel. It is capable of handling disturbances of higher‐order derivatives, including internal uncertainties, undesirable nonlinearities, and external disturbances. The paper also presents two innovative schemes for parametrizing the NHOESO parameters in the presence of measurement noise. These schemes are named time‐varying bandwidth NHOESO (TVB‐NHOESO) and online adaptive rule update NHOESO (OARU‐NHOESO). Numerical simulations are conducted to validate the effectiveness of the proposed schemes, using a nonlinear uncertain system as a test case. The results demonstrate that the OARU technique outperforms the TVB technique in terms of its ability to sense the presence of noise components in the output and respond accordingly. However, it is noted that the OARU technique is slower than the TVB technique and requires more complex parameter tuning to adaptively account for the measurement noise. [ABSTRACT FROM AUTHOR]

Overhead cranes play a pivotal role in various industrial applications. This paper presents two methodologies for suppressing the payload's swing and completing the accurate positioning. The original crane model is initially transformed into a chained form. Two nonlinear controllers are devised to regulate the trolley's position and achieve the payload's anti-swing control. The first approach utilizes backstepping, extended state observer, and filter technique to effectively estimate system state and disturbance and make the closed-loop system uniformly ultimately bounded. In contrast, the second method involves sliding mode control and finite-time disturbance observer to ensure the finite-time convergence of the resulting closed-loop system and the accurate disturbance estimation. Finally, simulation results are provided to validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

An adaptive sliding mode controller (SMC) design with a reinforcement-learning parameter optimization method is proposed for variable-speed trajectory tracking control of underactuated vessels under scenarios involving model uncertainties and external environmental disturbances. First, considering the flexible control requirements of the vessel's propulsion system, the desired navigation speed is designed to satisfy an S-curve acceleration and deceleration process. The rate of change of the trajectory parameters is derived. Second, to address the model uncertainties and external disturbances, an extended state observer (ESO) is designed to estimate the unknown bounded disturbances and to provide feedforward compensation. Moreover, an adaptive law is designed to estimate the upper bound of the unknown disturbances, ensuring system stability even in the presence of asymptotic observation errors. Finally, the Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm is employed for real-time controller parameter tuning. Numerical simulation results demonstrate that the proposed method significantly improves the trajectory tracking accuracy and dynamic response speed of the underactuated vessel. Specifically, for a sinusoidal trajectory with an amplitude of 200 m and a frequency of 0.01, numerical results show that the proposed method achieves convergence of the longitudinal tracking error to zero, while the lateral tracking error remains stable within 1 m. For the circular trajectory with a radius of 300 m, the numerical results indicate that both the longitudinal and lateral tracking errors are stabilized within 1 m. Compared with the fixed-value sliding mode controller, the proposed method demonstrates superior trajectory tracking accuracy and smoother control performance. [ABSTRACT FROM AUTHOR]

Recent application studies of deep reinforcement learning (DRL) in power electronic systems have successfully demonstrated its superiority over conventional model-based control design methods, stemming from its adaption and self-optimisation capabilities. However, the inevitable gap between offline training and real-life application presents a significant challenge for practical implementation, owing to its insufficient robustness. With this in mind, this paper proposes a novel robust DRL controller by fusing an extended state observer (ESO) for the DC–DC buck converter system feeding constant power loads (CPLs). To be specific, the mismatched lumped terms are reconstructed by an ESO in real time, and then fed forward into the agent's action, aiming to improve the adaptability to parameter variations of the real-life converter systems. By carefully conducting simulation and experimental tests, the robustness enhancement ability of the proposed framework compared with model-free DRL and conventional PI controllers are clearly verified. [ABSTRACT FROM AUTHOR]

This paper presents a novel and comprehensive control framework for the Rotary Inverted Pendulum (RIP), focusing on a hybrid control strategy that addresses the limitations of conventional methods in nonlinear and complex systems. The proposed controller synergistically combines an Optimized Fuzzy Logic Controller (OFLC) with Sliding Mode Control (SMC), leveraging the strengths of both techniques to achieve superior performance. The integration of Particle Swarm Optimization (PSO) into the OFLC significantly enhances its adaptability and precision, while the SMC law provides robust disturbance rejection and system stability. Another key innovation in this framework is the incorporation of an Extended State Observer (ESO), which ensures accurate state estimation and reduces sensor dependency. The most significant physical outcome of this work is the demonstrated improvement in the system's stability and robustness, even under external disturbances and uncertainties, showcasing the potential of the proposed control framework to achieve precise, stability control in nonlinear systems like the RIP. Extensive simulations validate the effectiveness of the proposed controller, demonstrating significant improvements in stability, disturbance rejection, and control precision, even under disturbance. The results highlight the potential of this approach as a robust solution for complex control systems, offering a significant advancement in the field of nonlinear system control with wide-ranging applications. [ABSTRACT FROM AUTHOR]

AbstractAccurate estimation of unmeasured system states and disturbances in a pressurized water reactor (PWR) is essential for effective control, operation optimization, and safety monitoring. To this end, this paper investigates the estimation of unmeasured system states and disturbances of the PWR system during load-following operation. First, a mathematical model for the PWR system is established based on the two-point kinetics equations with one equivalent delayed neutron precursor group. Subsequently, an extended state observer (ESO) integration scheme, incorporating two coupled ESOs, is constructed to estimate unmeasured system states, including relative density of delayed neutron precursor, average fuel temperature, total reactivity, xenon concentration, and iodine concentration, along with time-varying disturbances, with the use of measurements of the PWR system only. According to the Lyapunov stability theorem, it is proved that the estimation error dynamic of the proposed ESO integration scheme is uniformly ultimately bounded stable. Finally, simulation results confirm that the proposed ESO integration scheme provides higher estimation accuracy and stronger robustness against measurement noises, model uncertainties, and external disturbances compared to both a high-gain observer and a high-order sliding mode observer. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a double-loop tracking control strategy with finite-time convergence is investigated for a switched-trajectory quadrotor subjected to gust winds in air–ground cooperation. To handle the complexity of switched-trajectory tracking, an adaptive tracking differentiator is presented in an outer loop to arrange transition processes. Fast integral terminal sliding mode control is also used in the outer loop to improve convergence speed and tracking accuracy. The gust winds are estimated and compensated by a nonlinear extended state observer and a nonlinear controller with finite-time convergence in an inner loop, respectively. Convergency analyses are presented with the double-loop tracking control strategy for the switched-trajectory quadrotor. Comparison experiments with existing studies show superior performances of the proposed control method for the quadrotor in air–ground cooperation under gust winds. [ABSTRACT FROM AUTHOR]

To enhance the performance and robustness of predictive torque control amidst modeling errors and parameter variations in switched reluctance motor (SRM) drive systems, this paper proposes a model-free predictive torque control strategy utilizing a linear extended state observer. Initially, a novel torque error dynamic compensation method is introduced, enabling accurate mapping of phase torque to phase current. This method is characterized by its simplicity, ease of parameter setting, and its capability to bypass the complexities of solving the torque inverse model. Subsequently, an improved model-free predictive control algorithm is developed for current regulation. This algorithm substitutes the SRM's nonlinear model with a super local model and employs a linear extended state observer to estimate internal disturbances, such as model errors and parameter variations. The primary advantage of this algorithm is its data-driven nature, eliminating the dependence on precise mathematical models of the motor drive system. Ultimately, the reference voltage, generated by combining the current and disturbance estimation values from the linear extended state observer, is modulated via PWM and conveyed to the power converter to facilitate torque smoothing control. The efficacy of the proposed control method in enhancing parameter robustness and reducing torque ripple in SRM drive systems has been corroborated through simulations and experimental studies. [ABSTRACT FROM AUTHOR]

In tunnel section forming operations, the boom-type roadheader tracking target trajectory with high precision is greatly significant in avoiding over and under excavation and improving excavation efficiency. However, there exist complex cutting loads, measurement noise, and model uncertainties, seriously degrading the tracking performance of traditional nominal model-based controllers. Hence, this study first fully analyzes the kinematics of all members of the cutting mechanism and establishes its complete multi-body dynamic model using the Lagrange method. Furthermore, a dual extended state observer is designed to estimate the mechanical system's angular velocity and unmodeled disturbances and actuators' uncertain nonlinearities. In particular, introducing a nonlinear filter replaces the traditional first-order filter in dynamic surface technology, overcoming the "explosion of complexity" while attenuating the conservatism of gains tuning. Then, a dual extended state observer-based prescribed performance dynamic surface controller is developed for roadheaders for the first time. Simultaneously, integrating an improved error transformation function into controller design effectively avoids the online computational burden caused by traditional logarithmic operations. Utilizing Lyapunov theory, the cutting system's prescribed transient response and steady-state performance are guaranteed. Finally, the proposed controller's effectiveness is verified by comparative experiments on the roadheader. • A multi-body dynamic model considering all members of the cutting mechanism is established in detail. • A dual extended state observer is designed to estimate velocity, matched and mismatched disturbances of the cutting system. • A prescribed performance dynamic surface controller is developed, first achieving prescribed performance trajectory tracking for roadheaders. • In prescribed performance control, a logarithmic-free transformation function is developed, attenuating controller design complexity. [ABSTRACT FROM AUTHOR]

In this paper, a feedback controller based on the extended state observer is proposed for fully actuated systems. First, a generalized proportional–integral observer is designed to estimate states and disturbances simultaneously. Using the linear parameter varying approach and the convexity principle, a linear matrix inequality condition is given to obtain the observer gains. Second, on the basis of the full-actuation property and the estimated states, a feedback controller, utilizing estimated disturbances to compensate for system disturbances, is designed to make all the states of the closed-loop system uniformly ultimately bounded. In addition, if disturbances are constant or slow time-varying, the observation errors and the states of closed-loop system are all exponentially convergent. Two illustrations are provided to show the validity and practicality of the proposed approach. Simulation results show that the estimated disturbances can follow the true values with relatively small errors, so compensating the system disturbances with estimated values can effectively reduce the ultimate bounds of states of the closed-loop system. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper deals with the neural network identification-based model predictive heading control problem in a wave glider. First, based on a kinematic model of the wave glider subjected to external disturbance and system uncertainty, a state space model of the wave glider is established. Then, a neural network identification-based model predictive heading controller (NNI-MPHC) is designed for the wave glider. The heading controller mainly includes three components: a model predictive controller, a neural network-based model identifier, and a linear reduced-order extended state observer. Third, a design algorithm of the NNI-MPHC is presented. The algorithm is demonstrated through simulation, where the results show the following: (i) The designed NNI-MPHC is remarkably capable of guaranteeing the tracing effects of the wave glider. (ii) Comparing the NNI-MPHC and existing heading controllers, the former is better than the latter in terms of tracking accuracy and rapidity and robustness to model uncertainty and/or external disturbances. [ABSTRACT FROM AUTHOR]

Tension control in yarn winding is crucial for maintaining product quality and process continuity in the textile industry, particularly in the presence of varying rotational speeds, winding radii, and external disturbances. To address this issue, this paper proposes a yarn tension sliding mode control method based on a finite-time extended state observer for rapid and accurate tension regulation. Firstly, considering the dynamic characteristics of the tension control system, both internal and external disturbances are expanded into a total disturbance state, and a finite-time extended state observer is established to accurately estimate the system state and total disturbance. Secondly, based on the estimated state, a nonsingular terminal sliding mode control scheme is designed, with an appropriate exponential convergence law chosen to ensure that the system reaches the sliding surface within finite time. The finite-time stability of the estimation error and system tracking error is analyzed using the Lyapunov method. Finally, the simulation results demonstrate that the proposed control scheme effectively achieves finite-time stability of both estimation and tracking errors, and exhibits favorable dynamic characteristics.

For a class of permanent magnet synchronous motors (PMSM) characterized by strong coupling, significant nonlinearity, load uncertainties, and external disturbances, this paper investigates an extended state observer-based direct model-free adaptive predictive compensation control (ESO-dMFAPCC) method for speed regulation. Initially, a dynamic linearization model of a PMSM system with unknown external disturbances is developed. Subsequently, a novel direct model-free adaptive predictive compensation controller, theoretically equivalent to an ideal controller, is proposed. An extended state observer (ESO) is designed to estimate the state variable, capturing the characteristics of the external disturbance and system uncertainty. On this basis, control gains with online adaptive capabilities are designed to achieve adaptive speed control for the PMSM system. The primary advantage of the proposed control method lies in its novel framework for directly constructing a predictive compensation controller, which simplifies the controller structure design process by reducing it to a parameter-optimization problem. Moreover, utilizing only the PMSM system’s input/output (I/O) data, the proposed ESO-dMFAPCC is purely data-driven and exhibits strong robustness against external disturbances. Furthermore, the stability of the closed-loop PMSM system is rigorously analyzed. Finally, the simulation results demonstrate that, compared to PI control, sliding mode control (SMC), and model-free adaptive predictive control (MFAPC), the proposed method offers superior dynamic performance while significantly enhancing the anti-disturbance capabilities of the PMSM system.

Abstract Hydraulic actuated quadruped robots have bright application prospects and significant research values in unmanned area investigation, disaster rescue and other scenarios, due to the advantages of high payload and high power to weight ratio. Among these fields, inevitable collision of robots may occur when contact with unknown objects, step on empty objects, or collapse, all of which have an impact on the working hydraulic system. To overcome the unknown external disturbances, this paper proposes an active disturbance rejection control (ADRC) strategy of double vane hydraulic rotary actuators for the hip joints of the quadruped robots. Considering the order of the valve-controlled actuator model, a three-stage tracking differentiator, a four-stage extended state observer, and a state error feedback controller are designed relatively, and the extended state observer is adopted to observe and compensate the uncertainty of external load torque of the system. The effectiveness of the ADRC method is verified in simulation environment and a single joint experimental platform. Moreover, the impact experiments of the limb leg unit are carried out after introducing the proposed ADRC strategy into hip joint, the limb leg unit of quadruped robots presents better impact resistance ability.

• A fixed-time dynamic surface attitude controller for the tethered chained satellite system has been designed. • The proposed algorithm explicitly considers control input constraints. • An extended state observer is introduced to achieve output feedback and lumped disturbance estimation. • The filter error of dynamic surface control is eliminated by the compensation module. A fixed-time attitude stabilization scheme based on dynamic surface control (DSC) is proposed for the attitude of the three-body chained tethered system during tether deployment. Considering that the angular velocity of the satellite is difficult to measure, an extended state observer (ESO) is introduced to simultaneously compensate for the adverse effects of flexible panel vibrations and uncertain inertia tensors. On this basis, a fixed-time convergence attitude control scheme using DSC is designed, accounting for filtering error compensation. To offset the limitations of traditional fixed-time control strategies that ignore actuator saturation, an auxiliary system is introduced to incorporate control input constraints directly into controller design. The stability of the closed system is analyzed based on Lyapunov theory. Finally, the effectiveness and superiority of the proposed algorithm are verified by numerical simulation. [ABSTRACT FROM AUTHOR]

The control of the field outlet temperature of a parabolic trough solar field (PTSF) is crucial for the safe and efficient operation of the solar power system but with the difficulties arising from the multiple disturbances and constraints imposed on the variables. To this end, this paper proposes a constraint optimal model-based disturbance predictive and rejection control method with a disturbance prediction part. In this method, the steady-state target sequence is dynamically corrected in the presence of constraints, the lumped disturbance, and its future dynamics predicted by the least-squares support vector machine. In addition, a maximum controlled allowable set is constructed in real time to transform an infinite number of constraint inequalities into finite ones with the integration of the corrected steady-state target sequence. On this basis, an equivalent quadratic programming constrained optimization problem is constructed and solved by the dual-mode control law. The simulation results demonstrate the setpoint tracking and disturbance rejection performance of our design under the premise of constraint satisfaction. [ABSTRACT FROM AUTHOR]

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of adaptive nonsingular fast terminal sliding mode fixed-time tracking control method for rigid spacecraft without angular velocity measurement. First, a novel fixed-time extended state observer is proposed to obtain accurate estimates of both unmeasurable angular velocities and integrated disturbance. Then, based on this sufficient qualification, an adaptive fast nonsingular terminal sliding mode controller is designed to make the state of the following spacecraft track a target spacecraft even when the tracking system has an actuator fault. Adaptive technology is introduced to compensate for the effect of observation error on the controller. Using the Lyapunov function and fixed-time property, it is proved that the control scheme can ensure that the attitude tracking error converges to the neighborhood of the origin in a fixed time and is independent of the initial conditions. Finally, numerical simulation examples are carried out to evaluate the effectiveness of the proposed fixed-time method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the robust attitude tracking problem for quadrotors on the three-dimensional special orthogonal group SO(3) with finite-time convergence via disturbance-observer-based control technique. A finite-time geometric extended state observer is deduced on SO(3), which is an almost-global stable one without singularity or unwinding phenomenon happening in large-scale attitude control systems. Notably, the estimated performance is significantly enhanced compared to other conventional disturbance observers as no coordinate parameterization is made. Based on the estimated results, an adaptive geometric fast terminal sliding mode control law on SO(3) is introduced to alleviate the chattering effect and guarantee robust attitude tracking. An auxiliary system is then constructed to deal with the input saturation problem. The almost-global finite-time stability of the whole closed-loop system is then verified via Lyapunov analysis. Finally, simulations and flight experiments demonstrate the strong robustness and fast convergence rate of the proposed method against other geometric controllers and those utilizing attitude representations in Euler angle form. [ABSTRACT FROM AUTHOR]

To improve the speed buffering and position tracking accuracy of medium–high-speed permanent magnet synchronous motor (PMSM), a sensorless control method based on an improved sliding mode observer is proposed. By the mathematical model of the built-in PMSM, an improved adaptive super-twisting sliding mode observer is constructed. Based on the LSTA-SMO with a linear term of observation error, a sliding mode coefficient can be adjusted in real time according to the change in rotational speed. In view of the high harmonic content of the output back electromotive force, the adaptive adjustment strategy for the back electromotive force is adopted. In addition, in order to improve the estimation accuracy and resistance ability of the observer, the rotor position error was taken as the disturbance term, and the third-order extended state observer (ESO) was constructed to estimate the rotational speed and rotor position through the motor mechanical motion equation. The proposed method is validated in Matlab and compared with the conventional linear super twisted observer. The simulation results show that the proposed method enables the observer to operate stably in a wide velocity domain and reduces the velocity estimation error to 6.7 rpm and the position estimation accuracy error to 0.0005 rad at high speeds, which improves the anti-interference capability. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes an adaptive output feedback prescribed performance controller based on the extended state observer (ESO) for hydraulic systems with unmodeled dynamics. Considering the constraint on tracking errors, we have defined an improved convergence time-controllable prescribed performance function. It achieves the predetermined performance of the error signal for the original system by stabilizing the transformed system. In other words, the tracking error will remain within the specified constraint bounds over time. Unlike most existing prescribed performance control methods, this approach combines the advantages of finite-time performance functions and is derived from a modified transformation function related to tracking error and an asymmetric barrier function. It not only removes the constraints associated with initial error conditions, guaranteeing globally superior control performance but also offers flexibility in handling general cases of symmetric or asymmetric output constraints. Furthermore, an ESO is designed to estimate the unmeasured states and unknown dynamics through the output position signal, which avoids contamination of the velocity and acceleration signals by measurement noise and effectively mitigates the influence of most unfavorable factors on control performance. Building upon this foundation, we have developed a low-complexity control approach that integrates performance constraints with the ESO using filter-based backstepping techniques. Ultimately, the stability of the closed-loop system is substantiated using the Lyapunov method, and the effectiveness of the developed approach is validated through simulation. [ABSTRACT FROM AUTHOR]

In this paper, the problem of highly performance motion control of tank bidirectional stabilizer with dead zone nonlinearity and uncertain nonlinearity is addressed. First, the electromechanical coupling dynamics model of bidirectional stabilizer is developed finely. Second, the dead zone nonlinearity in bidirectional stabilizer is characterized as the combination of an uncertain time-varying gain and a bounded disturbance term. Meanwhile, an adaptive robust controller with dead zone compensation is proposed by organically combining adaptive technique and extended state observer (ESO) through backstepping method. The adaptive technique is employed to reduce the impact of unknown system parameter and dead zone parameter. Furthermore, the ESO is constructed to compensate the lumped uncertainties including unmodeled dynamics and dead zone residual, and integrated together via a feedforward cancellation technique. Moreover, the adaptive robust control law is derived to ensure final global stability. In stability analysis, the asymptotic tracking performance of the proposed controller can be guaranteed as the uncertainty nonlinearities in tank bidirectional stabilizer are constant. It is also guaranteed to achieve bounded tracking performance when time-varying uncertainties exist. Extensive co-simulation and experimental results verify the superiority of the proposed strategy. • A mechatronic dynamics model of the tank bidirectional stabilizer is developed, which is accurately modeled including couplings, nonlinearities and uncertainties. • The parametric adaptive function is constructed to update the unmeasurable dead zone parameters online, and the extended state observation technique is introduced to eliminate the dead zone nonlinearity and unmodeled dynamics. • The Lyapunov stability analysis demonstrates that the asymptotic tracking capability is guaranteed when the system uncertainty is constant, and the uniformly bounded tracking performance is guaranteed owing to the existence of time-varying uncertainties. • Comparative analysis of co-simulation and experiment confirms the effectiveness and feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper presents a simple and effective sensorless control strategy based on extended state observers (ESOs) to enhance the performance of brushless DC (BLDC) motors. First, an ESO is used to estimate the back-electromotive force (EMF) without additional filters. Second, another ESO is incorporated into the quadrature phase-locked loop (QPLL) to enable the implementation of an active harmonic compensator to reduce noise harmonics induced by the estimated back-EMF. By using the P-Q theory, the proposed compensator calculates a compensation signal to be directly injected into the QPLL based on ESO. The results analysis shows that the proposed strategy significantly reduces torque ripples and speed/position estimation errors under a wide range of speeds. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the process of coal mine drilling, controlling the rotary speed is important as it determines the efficiency and safety of drilling. In this paper, a linear extended state observer (LESO) based backstepping controller for rotary speed is proposed, which can overcome the impact of changes in coal seam hardness on rotary speed. Firstly, the influence of coal seam hardness on the drilling rig's rotary system is considered for the first time, which is reflected in the numerical variation of load torque, and a dynamic model for the design of rotary speed controller is established. Then an LESO is designed to observe the load torque, and feedforward compensation is carried out to overcome the influence of coal seam hardness. Based on the model of the compensated system, a backstepping method is used to design a controller to achieve tracking control of the rotary speed. Finally, the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments, the steady-state error of the rotary speed in field is 1 r/min, and the overshoot is reduced to 5.8%. This greatly improves the stability and security, which is exactly what the drilling process requires. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low trajectory tracking accuracy, serious chattering and poor robust performance of ball screw feed systems in traditional sliding mode control (SMC), in this paper, a global nonsingular fast terminal sliding mode control (GNFTSMC) strategy based on improved double power reaching law (DPRL) and extended state observer (ESO) is proposed. Firstly, the system state variable is introduced into the power term of DPRL, so that the improved DPRL has the characteristics of variable speed reaching, which solves the contradiction between the reaching rate and the sliding mode chattering. Secondly, ESO is designed to observe the state of the system and match the external disturbance to improve the anti-interference performance of the system. Finally, GNFTSMC is designed for the ball screw feed system, and the global sliding mode factor is introduced to improve the trajectory tracking accuracy of the system. The results show that the proposed control strategy can effectively improve the tracking accuracy and anti-interference performance of the system. [ABSTRACT FROM AUTHOR]

The suspension system of the Electromagnetic Suspension (EMS) maglev train is crucial for ensuring safe operation. This article focuses on data-driven modeling and control optimization of the suspension system. By the Extended Dynamic Mode Decomposition (EDMD) method based on the Koopman theory, the state and input data of the suspension system are collected to construct a high-dimensional linearized model of the system without detailed parameters of the system, preserving the nonlinear characteristics. With the data-driven model, the LQR controller and Extended State Observer (ESO) are applied to optimize the suspension control. Compared with baseline feedback methods, the optimization control with data-driven modeling reduces the maximum system fluctuation by 75.0% in total. Furthermore, considering the high-speed operating environment and vertical dynamic response of the maglev train, a rolling-update modeling method is proposed to achieve online modeling optimization of the suspension system. The simulation results show that this method reduces the maximum fluctuation amplitude of the suspension system by 40.0% and the vibration acceleration of the vehicle body by 46.8%, achieving significant optimization of the suspension control. [ABSTRACT FROM AUTHOR]