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In this paper, an integrated estimation guidance and control (IEGC) system is designed based on the command filtered backstepping approach for circular field-of-view (FOV) strapdown missiles. The three-dimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint. The boundary time-varying integral barrier Lyapunov function (IBLF) is employed in backstepping design to constrain the body line-of-sight (BLOS) in IEGC system to fit a circular FOV. Then, the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters. The generalized extended state observer (GESO) is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy. Furthermore, the command filters are used to solve the ''differential expansion'' problem during the backstepping design. The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system. Finally, the simulation results validate the integrated system's effectiveness, achieving high accuracy strikes against maneuvering targets.

When the phased array radar-guided missile intercepts a high speed target with large maneuvering, the aerodynamic parameters of the missile body vary dramatically and become nonlinear, which affects the response of the control system to the large angle-of-attack, the robust autopilot control law should be designed considering the tracking error constraint of the angle-of-attack command. A robust nonlinear autopilot control law is designed based on the double power reaching law and logarithmic barrier Lyapunov function can make the tracking error of the angle-of-attack command converge to the constraint range rapidly. The aerodynamic parameter uncertainty and external disturbance of the system are estimated and compensated online by using the reduced order extended state observer. Stability analysis and numerical simulation show the angle-of-attack can reach a steady state within 1 second and the steady-state error of the angle-of-attack response

Abstract The shaking table test has been widely recognized as one of the most reliable methods for assessing the dynamic response of structures and systems when exposed to a range of vibrations. Replicating these vibrations, recorded as acceleration signals, necessitates precise controller designs. However, traditional controller designs primarily rely on linear system assumptions, leading to complications in incorporating parametric uncertainty and uncertain non‐linearity. This paper presents a novel approach to the acceleration trajectory control problem of single‐axis hydraulic shaking table systems from a non‐linear perspective. This strategy employs a controller combined with an extended state observer (ESO) and adaptive control, offering a design that more closely reflects real‐world scenarios and requires less parameter adjustment. The ESO estimates the uncertain non‐linearity using the displacement signal, while the parametric uncertainty is tackled through adaptive control. The proposed controller's effectiveness is validated through theoretical proof using Lyapunov analysis. The analysis demonstrates that asymptotic tracking performance is guaranteed when the uncertain non‐linearity is time‐invariant. Moreover, with time‐variant uncertain non‐linearity, the controller can also ensure both prescribed transient tracking performance and final tracking accuracy. Comparative experiment results underscore the superior performance of the proposed controller.

In this paper, an integrated guidance and control method based on an adaptive path-following controller is proposed to control a spin-stabilized projectile with only translational motion information under the constraint of an actuator, uncertainties in aerodynamic parameters and measurements, and control system complexity. Owing to the fairly high rotation speed, the dynamic model of this missile is strongly nonlinear, uncertain and coupled in pitch, yaw and roll channels.A theoretical equivalent resultant force and uncertainty compensation method are comprehensively used to realize decoupling of pitch and yaw. In response to the strong nonlinear and time-varying characteristics of the dynamic system, the quasi-linear model whose parameters are obtained by interpolation of points selected as the segmentation points in the trajectory envelope, is used for calculation in each step. To cope with the system uncertainty caused by model approximation, parameter uncertainty and ballistic interference, an extended state estimator is used to compensate the output feedback according to the test ballistic angle. In order to improve the tracking efficiency and ensure the tracking error convergence with only translational motion information, the virtual guide point, whose derivative is deduced according to the Lyapunov principle, is calculated in real time according to the projection relationship between the real-time position and the reference trajectory, and a virtual line-of-sight angle and the backstepping method are used for the design of the guidance and control system. In order to avoid the influence of control input saturation on the guidance and control performance due to the actuator limitation and improve the robustness of the system, an anti-saturation compensator is designed according to the two-step method.The feasibility and effectiveness of the path-following controller is verified through closed-loop flight simulations with measurement, control, and condition uncertainties. The results indicate that the designed controller can converge to the reference path and evidently decrease the distance between the impact point and target under different uncertainties.

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.

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.

The liquid cooling system (LCS) of the proton exchange membrane (PEM) fuel cell suffers from large time delay, coupling, uncertainties, and various disturbances, making it susceptible to temperature regulation overshoot and control oscillation. This article focuses on a composite control scheme for the LCS that has effectively addressed the aforementioned issues. We first propose a two-layer control approach for the pump to minimize coupling, and an average delay model (ADM) for radiator whose parameter uncertainties are removed by equilibrium optimizer (EO). To overcome disturbances, an adaptive sliding mode control (ASMC) based on extended state observer (ESO) is presented, and its finite-time convergence is demonstrated. Additionally, the indirect regulation for the stack temperature is designed to considerably reduce the time delay in the fan control loop. Co-simulation results indicate that the proposed ASMC significantly suppresses the chattering phenomenon compared with regular sliding mode control (SMC). In contrast to incremental fuzzy control, the proposed scheme possesses superiorities in response speed, tracking accuracy, anti-disturbance, as well as suppression of overshoot and oscillation. • A two-layer control approach is developed for the coolant pump. • An average delay model is presented for the radiator. • An adaptive sliding mode control is proposed for the cooling fan. • An indirect regulation method significantly reduces the time delay in the fan control loop. [ABSTRACT FROM AUTHOR]

Summary: The existing active disturbance rejection control (ADRC) method may not provide sufficient disturbance rejection to multiple mismatched disturbances for the fractional order systems. In this paper, a composite disturbance rejection approach is developed for a class of fractional order uncertain systems, by synthesizing the fractional order ADRC (FOADRC) approach and a disturbance observer (DO)‐based compensation scheme. Taking advantage of more disturbance information and a filter structure, an improved DO is developed to achieve precise estimation of disturbances in the presence of sensor noises. In addition, a state transformation is developed to convert the system into a simple integral chain model with only matched disturbances. Then a composite control law is designed to compensate the disturbances and provide satisfying dynamic performance. The efficiency of the proposed method is demonstrated by a numerical simulation and an actual servo control simulation, as well as the comparison with two kinds of the existing ADRC methods and the commonly used integral sliding mode control (I‐SMC) method. [ABSTRACT FROM AUTHOR]

This paper addresses the trajectory tracking problem with prescribed performance for a multi-link robotic manipulator subject to unknown dynamics and external disturbances. A predefined performance function is adopted to describe tracking errors' desired transient and steady-state performance. Then, the output error dynamics with performance constraints are transformed into an equivalent unconstrained system, whose stabilization is sufficient to guarantee the prescribed performance of the original system. An extended state observer with a friction model is designed to approximate unknown dynamics together with the unmeasurable velocity state, which extends the applicability of the proposed controller to manipulators with only position signals available. The friction model is lumped into it to improve the precision and velocity of estimation. It is proved via Lyapunov analysis that the proposed controller can theoretically guarantee the satisfaction of prescribed performance in the presence of uncertainties. The simulation results verify the reliability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a robust tracking control method for wheeled mobile robot (WMR) against uncertainties, including wind disturbances and slipping. Through the application of the differential flatness methodology, the under-actuated WMR model is transformed into a linear canonical form, simplifying the design of a stabilizing feedback controller. To handle uncertainties from wheel slip and wind disturbances, the proposed feedback controller uses sliding mode control (SMC). However, increased uncertainties lead to chattering in the SMC approach due to higher control inputs. To mitigate this, a boundary layer around the switching surface is introduced, implementing a continuous control law to reduce chattering. Although increasing the boundary layer thickness reduces chattering, it may compromise the robustness achieved by SMC. To address this challenge, an active disturbance rejection control (ADRC) is integrated with boundary layer sliding mode control. ADRC estimates lumped uncertainties via an extended state observer and eliminates them within the feedback loop. This combined feedback control method aims to achieve practical control and robust tracking performance. Stability properties of the closed-loop system are established using the Lyapunov theory. Finally, simulations and experimental results are conducted to compare and evaluate the efficiency of the proposed robust tracking controller against other existing control methods. [ABSTRACT FROM AUTHOR]

Microgrids can operate stably in both islanded and grid-connected modes, and the transition between these modes enhances system reliability and flexibility, enabling microgrids to adapt to diverse operational requirements and environmental conditions. The switching process, however, may introduce transient voltage and frequency fluctuations, causing voltage and current shocks to the grid and potentially damaging devices and systems connected to the microgrid. To address this issue, this study introduces a novel approach based on the Extended State Observer (ESO) and the Super-Twisting Algorithm (STA). Power conversion systems use Virtual Synchronous Generator (VSG) control and Power-Quality (PQ) control when they are connected to the grid or when the microgrid is not connected to the grid. VSG and PQ share a current loop. Transitioning the reference current generated by the outer loop achieves the switching of control strategies. A real-time observer is designed to estimate and compensate for current fluctuations, disturbances, and variations in id, iq, and system parameters during the switching process to facilitate a smooth transition of control strategies. Furthermore, to enhance the dynamic response and robustness of the system, the Proportional–Integral (PI) controller in the ESO is replaced with a novel super-twisting sliding mode controller based on a boundary layer. The Lyapunov stability principle is applied to ensure asymptotic stability under disturbances. The proposed control strategy is validated through simulation using a seamless switching model of the power conversion system developed on the Matlab/Simulink (R2021b) platform. Simulation results demonstrate that the optimized control strategy enables smooth microgrid transitions, thereby improving the overall reliability of grid operations. [ABSTRACT FROM AUTHOR]

A sliding mode control (SMC) method is designed to attenuate the disturbances in the DC–DC buck converter system based on the estimated values of extended state observer (ESO). A conventional ESO is unable to accurately estimate system states and disturbances in finite time limited by its linear nature. This weakness cannot ensure that the system reaches the nominal sliding mode surface within finite time, thus the sliding mode trajectory will be affected. Therefore, a novel finite-time extended state observer (FTESO) is presented, utilizing a homogeneous theorem for finite-time convergence. Subsequently, a FTESO-based nonsingular terminal sliding mode control (NTSMC) method is devised for achieving globally finite-time stable of the closed-loop system. The Lyapunov stability theorem and homogeneous theorem are used to prove the finite-time stability, and the upper bound of settling time is estimated explicitly. Finally, both numerical simulations and experiments demonstrate the superiority of the designed control scheme with modeling errors and load disturbances. [ABSTRACT FROM AUTHOR]

This study investigates an event-triggered disturbance estimation approach for the inner-formation system. An extended state observer is designed using an event-based sampling scheme, which offers advantages over traditional estimation methods by reducing information transmission and unnecessary output information exchange while ensuring accurate system estimation performance. Additionally, a method for designing output-feedback control is proposed. The separation of feedback control and event-based observation in the design of output feedback allows us to apply existing optimal control algorithms to the targeted plant without compromising our established event-triggered sampling methods. A numerical simulation is presented, and we demonstrate the effectiveness of our proposed approach for the inner-formation system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University 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.)

To address the robust speed control problem of the surface‐mounted permanent‐magnet synchronous motor (SPMSM) drive, a novel composite speed controller (CSC) is proposed, which consists of the modified super‐twisting sliding‐mode SC (STSM‐SC) and the extended state observer (ESO). Regarding the motion dynamics of the SPMSM drive, the unmodeled dynamics, endogenous, and exogenous disturbances are lumped together as the total disturbance. The ESO‐based feedforward compensation mechanism is used to deal with the total disturbance for the robustness improvement of the speed control achieved by the modified STSM‐SC‐based feedback regulation mechanism. On the basis of the field‐oriented control strategy, performance comparisons of the standard STSM‐SC, the ESO‐based standard STSM‐SC, the modified STSM‐SC, and the proposed CSC are carried out on a suitably developed experimental setup. The experimental results are presented to validate the superiority of the proposed CSC. [ABSTRACT FROM AUTHOR]

The control of Proton Exchange Membrane Fuel Cell (PEMFC) is exceptionally challenging due to its complex nonlinearity, slow dynamics and load disturbance. In this paper, an Adaptive Model Free Control (AMFC) approach is introduced for regulating the PEMFC output voltage under load perturbation and measurement noise conditions. The proposed method consists of four sub-elements. Firstly, an Extended State Observer (ESO) based on a Single-Input Interval Type-2 Fuzzy intelligent PI (SI-IT-2-FLC-iPI) scheme is designed to enhance the performance of PEMFC. Secondly, a Nonlinear Sliding Mode Control-based Super Twisting Algorithm (NSMC-STA) is used as an auxiliary control approach to reduce the estimation error and ameliorate the system robustness. Thirdly, a Forgotten Recursive Least Square Error (FRLSE) is applied for adjusting the physical parameter of MFC and further ameliorating the control response. Finally, all these elements are merged together within what it is called Ultra Local Model (ULM). Through extensive simulation, the efficacy of the proposed regulator in accurately tracking the output signal is showcased, outperforming conventional controllers with remarkable improvements. The system achieves 0.001 steady-state error, 0% overshoot and settling time of approximately 8.9 s, which is good enough in the context of standalone fuel cell applications. • An intelligent Model Free Control structure is developed for tracking the output voltage of PEMFC. • Integrating FLC type-2 PI, NSMC-STA, ESO and online tuner based FRLSE within ULM. • The finite stability is fully demonstrated using Lyapunov theorems. • The proposed control enhances the performance of PEMFC under various operating conditions. [ABSTRACT FROM AUTHOR]

The emerging trans-media vehicle is significant due to its amphibious ability. A finite-time output feedback trans-media tracking control scheme is proposed for a slender body trans-media vehicle with unknown time-varying hydrodynamics and external disturbances. First, a novel neural network extended state observer is developed to observe the vehicle's velocities and handle the time-varying hydrodynamics and total disturbances simultaneously. Then, combined with the proposed observer, the finite-time command filtered backstepping technique is carefully constructed to yield the finite-time output feedback tracking control. The strength of the proposed approach to the existing methods is that it ensures the trans-media tracking errors converge to the small region of origin within a finite time, even in the absence of velocity measurements. The simulations are given to illustrate the superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

With rising demands on system performance and reliability in engineering practice, researchers are increasingly interested in disturbance rejection control, of which state and disturbance observation is the essential element. The extended state observer (ESO, or extended high‐gain observer) is extensively utilized to compensate disturbance, nevertheless, the neglect of lumped disturbance's first derivative and peak phenomenon in classical ESO design impose obstacles to further promotion. In this article, nested ESO (NestedESO) is proposed to estimate states and disturbance simultaneously for general uncertain nonlinear systems under time‐varying disturbance. In NestedESO framework, low‐gain generalized ESO is implemented to obtain a rough estimation of lumped disturbance in the first stage. Then, a novel proportion‐filter‐derivative disturbance estimation refinement mechanism is introduced to provide accurate disturbance estimation. With refined disturbance estimation, modified Luenburger observer is put forward to reconstruct state. Besides, extension to sampled‐data systems is investigated to adapt the networked signal transmission scenario. Numerical examples are given to illustrate the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The DC–DC dual active bridge (DAB) converter has become one of the essential units for bidirectional energy distribution and connecting various renewable energy sources. When it comes to regulating the converter's output voltage, integrating an extended state observer (ESO) offers the advantage of eliminating the need for a current sensor, thereby reducing system costs. The ESO with a high observer bandwidth tends to acquire a faster system convergence and greater tracking accuracy. However, its disturbance suppression performance will become poor compared to the ESO with a low observer bandwidth. Based on this, the adaptive ESO (AESO) is proposed in this study to make a compromise between tracking performance and disturbance suppression. When the system is subjected to a high voltage error, the observer bandwidth will increase to improve the tracking performance and decrease to enhance the disturbance suppression. In order to demonstrate that the proposed method is effective, it is compared to the ESO with a fixed observer bandwidth and the improved model-based phase-shift control (MPSC). These comparisons are made through simulation and experimental results in various operation scenarios. [ABSTRACT FROM AUTHOR]

In this paper, a trajectory tracking control strategy for low-speed car-like mobile robots (CLMRs) based on an extended state observer (ESO) and backstepping control is proposed to address the issue of trajectory tracking accuracy degradation caused by modeling errors and external disturbances. First, modeling errors and external disturbances are introduced into an ideal kinematic model of a CLMR, and a set of output equations is utilized to split the coupled, underdriven disturbance kinematic model into two mutually independent subsystems. Next, disturbances in the subsystems are estimated based on a linear ESO, and the convergence of the proposed observer is proved by the Lyapunov method. Finally, a controller with disturbance compensation is designed using backstepping control to complete the trajectory tracking task of CLMRs. Simulation and experimental results show the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper is focused on asymptotic tracking control of electro-hydraulic actuator (EHA) systems subject to matched and mismatched time-varying disturbances. To counteract the matched disturbance, a novel extended state observer (ESO) is proposed to achieve asymptotic convergence of the estimation error, by incorporating the strictly positive real (SPR) Lyapunov design method and a Nussbaum function. To further suppress the mismatched disturbance, an adaptive robust integral of the sign of the error (RISE) controller is formulated in the backstepping framework based on the proposed ESO. Asymptotic tracking performance is theoretically achieved via closed-loop system stability analysis. The efficacy of the proposed control scheme is verified through comparative experiments executed on an EHA test rig. In this study, a priori bounds of the disturbances and their higher-order derivatives are no longer needed, and only one auxiliary error signal is introduced. This approach loosens the restrictions on the disturbances and reduces the design conservativeness, thus making it promising in practice. [ABSTRACT FROM AUTHOR]

This paper investigates the coordination control of large-scale systems (LSSs) with unknown external disturbances. The disturbances exist in the channels from the controllers to the actuators. To compensate the impact of disturbances, an extended observer using the output states is constructed, and an observer-based event-triggered controller is designed to save communication resources. Moreover, based on the event-triggering strategy, a controller using dynamic information estimation is designed, and Zeno behavior is further excluded. Finally, a DC micro-grid model is used for simulations to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper presents a practical and straightforward control strategy for robotic manipulators with unknown dynamics to achieve prescribed tracking performance, which has implementation advantages compared with previous work. In particular, an improved extended state observer (ESO) synthesized with a continuously differentiable friction model and time-varying gains is presented to estimate system states and unknown dynamics. This ESO outperforms the conventional ones in dealing with friction mutations while avoiding peaking estimation values in the initial stage. By combining the prescribed performance function and the proposed ESO, an independent joint control scheme is proposed for a robotic manipulator to keep the tracking error within a predefined performance bound based only on position measurements. The effectiveness of the proposed control scheme is verified by comparative simulation and experimental results on a six-degrees-of-freedom robotic manipulator with active disturbance rejection controller and PID methods. [ABSTRACT FROM AUTHOR]

Copyright of Aero Weaponry is the property of Aero Weaponry Editorial Office 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 considers the output tracking problem for uncertain nonaffine systems. A robust output tracking controller for a class of uncertain nonaffine strict-feedback systems with guaranteed tracking error bounds is proposed. First, a diffeomorphism is employed to convert the strict-feedback nonaffine system with mismatched uncertainties into a feedback linearization nonaffine system (FLNS). Second, for the transformed FLNS, an error transformation and sliding surface technique are combined to transform the constrained tracking problem of a high-order system into an unconstrained stabilization problem of a first-order system when visualizing the guaranteed tracking error bound as a tracking error constraint. Then, a saturated approximate dynamic inversion scheme and an extended state observer are combined to achieve the stabilization of the transformed first-order nonaffine system. The stability of the closed-loop system is analyzed rigorously and it is sufficient to guarantee that the tracking error constraint can be achieved and all system states are semi-globally uniformly bounded for the original system. Simulation results clarify and verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & 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.)

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China 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 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.)

This article addresses the problem of distributed average tracking for second‐order multi‐agent systems with disturbances. The unknown disturbances inject into the velocity dynamics, resulting in the degradation of system stability. An extended state observer is designed to estimate the velocities and disturbances. Then, an observer‐based average tracking protocol is proposed, which does not require velocity measurements, and the unknown disturbances are compensated by the estimations. The protocol is implemented in a distributed fashion, without requiring any global information, and is robust to initialization errors. Through Lyapunov analysis, it is verified that the second‐order multi‐agent system can achieve distributed average tracking under the proposed protocol. Finally, the effectiveness of the control method is demonstrated by simulations. [ABSTRACT FROM AUTHOR]

This paper proposes a data‐driven bipartite leader‐following consensus strategy for a class of nonlinear multi‐agent systems (MASs) under external disturbances and hybrid attacks, which are composed of denial‐of‐service attacks and false data injection attacks. This data‐driven algorithm incorporates no system dynamics and only utilizes the input and output data generated by the controlled plant. First, the nonlinear MAS with external disturbances can be transformed into an equivalent linear data model by applying a revised dynamic linearization method. Second, a hybrid‐attack compensation mechanism is proposed to alleviate the adverse impact of data dropout caused by hybrid attacks. Then, based on the compensation mechanism, an extended state observer is designed that can mitigate the negative influence induced by external disturbances and improve the control performance even though the MAS is threatened by hybrid attacks. The systems under hybrid attacks and external disturbances can still remain stable with the proposed data‐driven strategy. Finally, simulation examples demonstrate the validity of the data‐driven strategy, and the bipartite consensus error can be reduced to a small range. [ABSTRACT FROM AUTHOR]

The shaking table test has been widely recognized as one of the most reliable methods for assessing the dynamic response of structures and systems when exposed to a range of vibrations. Replicating these vibrations, recorded as acceleration signals, necessitates precise controller designs. However, traditional controller designs primarily rely on linear system assumptions, leading to complications in incorporating parametric uncertainty and uncertain non‐linearity. This paper presents a novel approach to the acceleration trajectory control problem of single‐axis hydraulic shaking table systems from a non‐linear perspective. This strategy employs a controller combined with an extended state observer (ESO) and adaptive control, offering a design that more closely reflects real‐world scenarios and requires less parameter adjustment. The ESO estimates the uncertain non‐linearity using the displacement signal, while the parametric uncertainty is tackled through adaptive control. The proposed controller's effectiveness is validated through theoretical proof using Lyapunov analysis. The analysis demonstrates that asymptotic tracking performance is guaranteed when the uncertain non‐linearity is time‐invariant. Moreover, with time‐variant uncertain non‐linearity, the controller can also ensure both prescribed transient tracking performance and final tracking accuracy. Comparative experiment results underscore the superior performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Multilayer neural networks can approximate endogenous disturbances with relatively high accuracy. However, for multilayer‐neural‐network‐based control methods of high‐order uncertain nonlinear systems, hard to handle large exogenous disturbances especially for mismatched types, complex controller scheme and so on, make them difficult to be practical. Therefore, a novel high‐performance multilayer neurocontroller which can simultaneously reject matched and mismatched disturbances will be proposed in this paper. Specially, strong endogenous and exogenous disturbances will be feedforwardly compensated. Additionally, the proposed controller not only protects from "explosion of complexity," but also owns a simple scheme. [ABSTRACT FROM AUTHOR]

In this paper, an optimal extended state observer (ESO) is designed for nonlinear integral chain system. For the first time, in this paper, proportional–integral (PI) extremum seeking control (ESC; PIESC) approach is applied to design a perturbation observer by minimizing the estimation error. The PI type structure of the ESC provides fast transient response for the closed-loop system to attain optimum equilibrium point. A mathematical proof is presented to show that the average error dynamic asymptotically converges to zero while the estimation error is minimized. The simulation results verify that the estimation error achieved by the proposed PIESC-based ESO (PIESC-ESO) is found significantly less than that achieved by the classic ESO and PSO-based ESO. Moreover, if slow changes occur within the system or external to it, the PIESC-ESO is still able to modify the observer gains such that the estimation error is minimized again. Therefore, this may help PIESC-ESO to be used in practical applications. [ABSTRACT FROM AUTHOR]

Effective vibration control of flexible cables is increasingly demanded for space flexible structure. For the low frequency dynamics of flexible cables, a novel vibration control strategy based on sliding mode control is proposed in this paper. First, the complex dynamical behavior of flexible cables is modeled using D'Alembert's principle. Second, an improved dual power reaching law is put forward to better address the chattering problem of the sliding mode controller. Then, an extended state observer (ESO) with the radial basis function (RBF) neural network is designed to compensate for internal uncertainties and external disturbances as well as further improve the control accuracy. Lyapunov function is employed to analyze the stability of the system. Finally, considering the large number of parameters of the proposed controller, an improved particle swarm optimization (PSO) algorithm is designed to automatically adjust these parameters. The effectiveness of the proposed method is demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

This article explores the use of an active disturbance rejection predictive control strategy for local trajectory planning of unmanned ground vehicles (UGVs). The strategy incorporates an extended state observer and a nonlinear feedback control law to handle internal error and environment disturbance. Nonlinear model predictive control is used to address motion planning and nonholonomic constraints. The proposed algorithm improves the accuracy and efficiency of UGV trajectory planning and control. Simulation and experimental results demonstrate the effectiveness of the strategy, and future research will focus on further improvements and practical implementation. [Extracted from the article]

This paper proposes an extended state observer (ESO) based data-driven set-point learning control (DDSPLC) scheme for a class of nonlinear batch processes with a priori P-type feedback control structure subject to nonrepetitive uncertainties, by only using the process input and output data available in practice. Firstly, the unknown process dynamics is equivalently transformed into an iterative dynamic linearization data model (IDLDM) with a residual term. A radial basis function neural network is adopted to estimate the pseudo partial derivative information related to IDLDM, and meanwhile, a data-driven iterative ESO is constructed to estimate the unknown residual term along the batch direction. Then, an adaptive set-point learning control law is designed to merely regulate the set-point command of the closed-loop control structure for realizing batch optimization. Robust convergence of the output tracking error along the batch direction is rigorously analyzed by using the contraction mapping approach and mathematical induction. Finally, two illustrative examples from the literature are used to validate the effectiveness and advantage of the proposed design. • Novel extended state observer (ESO) based data-driven set-point learning control (DDSPLC). • Iterative dynamic linearized data model (IDLDM) for nonlinear batch processes. • Use the radial basis function neural network (RBFNN) to approximate pseudo partial derivative. • Set-point learning law with an adaptive learning gain for a priori P-type feedback structure. • Robust convergence of the resulting ILC system along the batch direction is rigorously analyzed. [ABSTRACT FROM AUTHOR]

In this paper, an integrated guidance and control method based on an adaptive path-following controller is proposed to control a spin-stabilized projectile with only translational motion information under the constraint of an actuator, uncertainties in aerodynamic parameters and measurements, and control system complexity. Owing to the fairly high rotation speed, the dynamic model of this missile is strongly nonlinear, uncertain and coupled in pitch, yaw and roll channels. A theoretical equivalent resultant force and uncertainty compensation method are comprehensively used to realize decoupling of pitch and yaw. In response to the strong nonlinear and time-varying characteristics of the dynamic system, the quasi-linear model whose parameters are obtained by interpolation of points selected as the segmentation points in the trajectory envelope, is used for calculation in each step. To cope with the system uncertainty caused by model approximation, parameter uncertainty and ballistic interference, an extended state estimator is used to compensate the output feedback according to the test ballistic angle. In order to improve the tracking efficiency and ensure the tracking error convergence with only translational motion information, the virtual guide point, whose derivative is deduced according to the Lyapunov principle, is calculated in real time according to the projection relationship between the real-time position and the reference trajectory, and a virtual line-ofsight angle and the backstepping method are used for the design of the guidance and control system. In order to avoid the influence of control input saturation on the guidance and control performance due to the actuator limitation and improve the robustness of the system, an anti-saturation compensator is designed according to the two-step method. The feasibility and effectiveness of the path-following controller is verified through closed-loop flight simulations with measurement, control, and condition uncertainties. The results indicate that the designed controller can converge to the reference path and evidently decrease the distance between the impact point and target under different uncertainties. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) 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.)

In order to stabilize underactuated robotic systems with external disturbances, an adaptive hierarchical sliding mode control strategy based on extended state observer is proposed. The extended state observer is designed to estimate the joint states and lumped disturbance composed of matched and unmatched disturbances. The underactuated robotic system is divided into two subsystems. For each subsystem, a sub-sliding mode surface is constructed to obtain the first layer sliding mode surface and the second layer sliding mode surface is derived from the first layer sliding mode surface. Then the hierarchical sliding mode controller is designed with the estimated state obtained from the observer to compensate the lumped disturbance and an adaptive law is designed to adjust the switching gain. The stability of the system is proved by Lyapunov theory and the effectiveness of the proposed control strategy is verified by comparative simulations. With the proposed control, the tracking performance of the underactuated robotic system is effectively improved and the convergence time of the system is reduced. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University 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.)

A multi-channel phase-compensated active disturbance rejection control (MPADRC) incorporating an improved backstepping strategy is proposed in this paper to handle the phase lag in the extended state observer (ESO) and the residual uncertainty in the system. Firstly, a multi-channel phase-compensated ESO (MPESO) is constructed by adding phase-advanced networks to all output channels of the ESO, which allows disturbances and system states to be compensated and feedback in a more timely manner, respectively. Then, to estimate and offset the residual uncertainty in the system, an improved backstepping control method is employed and a Lyapunov function is designed to verify the convergence of the error between the estimated and actual values of the residual uncertainty. After that, the improved backstepping control is combined with MPADRC, and comparisons with the conventional linear active disturbance rejection control (LADRC) are conducted for a range of cases. Finally, on an inertial stabilization platform in the electro-optical tracking system (ETS), simulation and experimental results verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Distributed energy resources (DER) are integrated into a microgrid through dc-dc power electronic converters. The bidirectional dc-dc converter regulates charging and discharging operations of ESS. Model predictive control (MPC), is a high-performance control technique for these converters, but it is limited in robustness to parameter mismatch, model uncertainties and sensor measurement noise. Therefore, in this paper, an improved hybrid cascade-parallel extended state observer (CP-ESO) is proposed, for model-free predictive control, to guarantee both robustness to parameter/model uncertainties and measurement noise suppression. A novel structurally-adaptive ESO scheme is also proposed to improve the disturbance rejection of CP-ESO during transient response. These results are supported by analysis and design guidelines for the selection of optimal sub-frequencies. Experimental results, for a bidirectional dc-dc boost converter, validate the effectiveness of the proposed methods against model uncertainties, external disturbances from variable input voltage and load, as well as measurement noise.

This paper addresses the challenging control problem of stabilizing an inverted pendulum on a cart. The inherent nonlinearity, instability, and under actuation of the system pose significant difficulties in achieving simultaneous pendulum stabilization and cart movement. To overcome these challenges, we propose an integrated approach that combines Linear Quadratic Regulator (LQR) and fuzzy logic control methods. This integrated control strategy effectively stabilizes the pendulum and controls the cart’s position. Notably, the integrated control outperforms the LQR control in terms of convergence speed. Furthermore, we explore the use of observers for state estimation, specifically the high-order integral-chain differentiator and the extended state observer, to accurately estimate pendulum angular velocity. Simulation results, along with detailed discussions, are presented to validate the accuracy and effectiveness of the proposed control methods and observers.

ObjectiveThis paper develops a heading tracking design strategy for unmanned ships with state quantization and input quantization in order to address the problem of limited communication at sea for unmanned ships on the water surface.Methods First, a control law is designed on the basis of backstepping and combined with dynamic surface control to reduce the computational complexity of the virtual control law. An extended state observer is also designed to estimate uncertainties and unknown disturbances. Second, all state variables and control variables in the control system are assumed to be quantized by the uniform quantizer, and the quantized state feedback information is only available for the tracking control design. A controller of unmanned ships based on the extended state observer and using quantized states is recursively designed to ensure the tracking of the desired heading. The boundedness of the quantization errors between quantized variables and non-quantized variables in the closed-loop system is analyzed by presenting several theoretical lemmas.ResultsBased on the Lyapunov stability theory, the stability of the designed unmanned ship heading tracking control system with state quantization and input quantization is demonstrated, and the simulation results verify the effectiveness of the resulting tracking scheme. Conclusion The results of this study can provide references for the heading tracking of unmanned ships.