State Estimation Research Articles

Dynamic Inverse Control of Uncertain Pure Feedback Systems Based on Extended State Observer

A novel, precise disturbance rejection dynamic inversion control algorithm has been proposed. In the high-order dynamic surface control system, an innovative approach utilizes a monotonically increasing inverse hyperbolic sine function to construct an extended state observer, which estimates the uncertain functions at each step. The monotonicity of the inverse hyperbolic sine function simplifies the system stability analysis. Additionally, being a smooth function, it avoids the disturbances caused by piecewise functions at their breakpoints in conventional observer construction, thereby enhancing system stability. The accurate prediction capability of the new observer improves the system’s disturbance rejection performance. To address the inherent differential explosion phenomenon in traditional dynamic inversion control schemes, this paper ingeniously employs a tracking signal observer as a substitute for traditional filters, thus avoiding the differential explosion that may occur with first-order filters. Finally, comparative simulations were conducted to validate the effectiveness of the proposed method. The results show that both the observer and the controller possess high-gain characteristics, and the closed-loop system exhibits a fast convergence rate.

A novel combination between finite-time extended state observer and proportional-integral-derivative nonsingular fast terminal sliding mode controller for an autonomous underwater vehicle

A novel combination between finite-time extended state observer and proportional-integral-derivative nonsingular fast terminal sliding mode controller for an autonomous underwater vehicle

Prescribed Performance-Based Formation Control for Multiple Autonomous Underwater Helicopters with Complex Dynamic Characteristics

This research addresses the challenge of formation control among multiple homogeneous autonomous underwater helicopters (AUHs) in the presence of external disturbances and complex dynamic characteristics. The study introduces a novel approach by integrating both disturbance and state observers within the control law framework to manage external disturbances and the immeasurability of velocity, respectively. Concurrently, localized radial basis function neural networks (RBFNNs) of identical configurations are incorporated into the formation control law to assimilate model uncertainties. Building upon this integration, an experience-based formation control strategy is developed, leveraging accumulated knowledge to diminish computational demands while maintaining stipulated performance criteria. Furthermore, the incorporation of a finite-time prescribed performance control (FTPPC) technique enhances the learning process’s efficiency by expediting convergence. Numerical simulations are presented to validate the efficacy of the proposed methodology.

The relationship between natural resource rents and gender discrimination laws: evidence from panel data analysis

PurposeThis study investigates the impact of hydrocarbon rents on gender discrimination laws and the extent to which democratic institutions and women’s political participation condition this relationship.Design/methodology/approachThis study uses static and dynamic panel estimation including pooled-ordinary least squares, fixed and random effects and system generalized method of moments.FindingsThe results show that countries with higher hydrocarbon rents have higher levels of gender discrimination laws. Furthermore, there is a significant link between hydrocarbon rents and gender discrimination laws regardless of the quality of democratic institutions or strength of women’s political empowerment.Research limitations/implicationsThe index of gender discrimination laws is limited to laws that impact a woman’s access to employment and entrepreneurial activity once a woman enters the labor force and does not take into account implementation of the laws.Practical implicationsPolicymakers should promote output and export diversification and adopt gender-inclusive policies to counter the adverse consequences of gender discrimination laws associated with hydrocarbon resource wealth.Originality/valueWomen’s empowerment is a major issue on the global development agenda, featuring most notably in the United Nations Sustainable Development Goal 5 on achieving women equality and empowerment of women and girls. There is scant evidence about how hydrocarbon rents impact gender discrimination laws, a pervasive obstacle to women’s economic and political empowerment. This paper fills this gap in the literature paper by examining the effect of hydrocarbon rents on gender discrimination laws.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0174

Decentralized Finite‐Time Adaptive Neural Output‐Feedback Quantized Control for Switched Nonlinear Large‐Scale Delayed Systems

ABSTRACTThis paper considers the problem of decentralized finite‐time adaptive neural output‐feedback quantized control for a class of switched nonlinear large‐scale delayed systems. A switched high‐gain quantized state observer is therefore constructed for each subsystem to estimate unavailable system states. Different from the traditional Lyapunov–Krasovskii functional method, multiple Lyapunov–Krasovskii functions are introduced to develop the decentralized adaptive output‐feedback control strategy with neural network approximation for the switched nonlinear large‐scale delayed systems. Under a category of switching signals with persistent dwell time, all signals in the closed‐loop switched system are semi‐globally uniformly ultimate bounded. Meanwhile, the tracking errors can remain in a small domain of origin in finite time. Case studies are finally used to illustrate the flexibility and effectiveness of the proposed control approach, including the switched two continuous stirred tank reactor delayed systems.

Output feedback control for non-strict feedback nonlinear systems: an adaptive fuzzy backstepping scheme

The adaptive fuzzy tracking control design issue is considered in this paper for a class of non-strict feedback nonlinear systems subject to external disturbances. A fuzzy high-gain state observer is constructed to reconstruct the unmeasurable states of the system by leveraging the universal approximation property of fuzzy logic systems for arbitrary unknown nonlinear functions. Within the framework of backstepping control design and in conjunction with adaptive techniques, an adaptive fuzzy control approach is presented. Subsequently, to work out the inherent ‘complexity explosion’ problem of the proposed control approach, dynamic surface control technique is introduced, leading to a simplified adaptive fuzzy output feedback control scheme. Stability analysis shows that the two proposed control schemes can ensure that all signals of the closed-loop system are semi-globally uniformly ultimately bounded, meanwhile the system tracking error can converge to a small neighborhood around the origin. Ultimately, a numerical simulation example is provided to validate the feasibility of the proposed control scheme.

Theory and experiment for autonomous quadrotor flight via bounded robust finite-time homogeneous sliding mode control: A roadmap to search and rescue

This paper introduces a new saturated robust control technique for quadrotor aircraft modeled by second-order Ordinary Differential Equations (ODEs), considering disturbances in the control channel (matched disturbances). The control design employs a Sliding Mode Control (SMC) approach, featuring in: (i) a novel saturated homogeneous sliding manifold, (ii) a novel tracking controller, namely, Bounded Robust Finite-Time Homogeneous Sliding Mode Control (BRFTHSMC). An Improved Fixed-time Convergent Extended State Observer (IFCESO) is incorporated into the control scheme to handle disturbances. Together the BRFTHSMC and the IFCESO establish a reliable Active Disturbance Rejection Control (ADRC) framework. The latter ensures finite-time convergence of the errors quantities to the origin along with effective disturbance rejection. Rigorous stability analysis is conducted based on Lyapunov theory. Beside control design, another distinguishing theoretical outcome of this paper in the form of Corollary is the extension of the present results to integrator-type systems (higher-order systems). The study is substantiated through MATLAB®/Simulink simulations and Robot Operating System (ROS)/Gazebo implementation, validating the theoretical foundation. Extensive experimental tests on real hardware, including attitude and Cartesian trajectory tracking under various disturbances, further affirm the theoretical findings. The synthesized control system surpasses alternative methods in terms of control signal’s boundedness, finite-time tracking stability, transient response performance, and steady-state precision. Notably, the control input circumvents singularity challenges observed in conventional SMC approaches. In addition to trajectory tracking experiments, the controller’s effectiveness is demonstrated in real-world search and rescue scenarios. Therefore, a Deep Neural Network (DNN) algorithm, based on a MS COCO-pretrained Single Shot Detector (SSD-Mobilenet-v2), is employed for a person detection mission in an unknown search area.

Robust Nonlinear Model Predictive Control for the Trajectory Tracking of Skid-Steer Mobile Manipulators with Wheel–Ground Interactions

This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the effects of disturbances caused by the slip phenomena through the wheel–terrain contact and bidirectional interactions propagated by mechanical coupling between the SSMM base and arm. These interactions are modelled using a coupled nonlinear dynamic framework that integrates bounded uncertainties for the mobile base and arm joints. The model is developed based on principles of full-body energy balance and link torques. Then, a centralized control architecture integrates a nominal NMPC (disturbance-free) and ancillary controller based on Active Disturbance-Rejection Control (ADRC) to strengthen control robustness, operating the full system dynamics as a single robotic body. While the NMPC strategy is responsible for the trajectory-tracking control task, the ADRC leverages an Extended State Observer (ESO) to quantify the impact of external disturbances. Then, the ADRC is devoted to compensating for external disturbances and uncertainties stemming from the model mismatch between the nominal representation and the actual system response. Simulation and field experiments conducted on an assembled Pioneer 3P-AT base and Katana 6M180 robotic arm under terrain constraints demonstrate the effectiveness of the proposed method. Compared to non-robust controllers, the R-NMPC approach significantly reduced trajectory-tracking errors by 79.5% for mobile bases and 42.3% for robot arms. These results highlight the potential to enhance robust performance and resource efficiency in complex navigation conditions.

Pitch control for floating offshore wind turbines via model-dependent extended state observer-based active disturbance rejection control

Various types of disturbances bring significant challenges to the stable operation of floating offshore wind turbines. This paper formulates the pitch control of floating offshore wind turbines using a novel model-dependent extended state observer-based active disturbance rejection control, which can effectively estimate and compensate for total disturbances. Firstly, a Markov model is proposed to describe wind and wave combined external disturbances and the aerodynamic characteristics of floating offshore wind turbines. Then, an active disturbance rejection control is developed based on the constructed model-dependent extended state observer. The approach provided in this paper can adjust the pitch angle to ensure that the generator speed output tracks the desired reference value. Based on this, the multi verse optimization algorithm is introduced to optimize the parameters of the controller. Finally, the superiorities of the results presented in this paper are illustrated by a 5 MW floating offshore wind turbine model. Simulation results demonstrate that the model-dependent extended state observer-based active disturbance rejection control strategy can significantly adjust the pitch angle to guarantee the stable operation of floating offshore wind turbines under wind and wave combined external disturbances.

Three-Dimensional Event-Triggered Predefined-Time Cooperative Guidance Law

To address the problem of multiple missiles attacking a maneuvering target simultaneously in three-dimensional space, we propose a new predefined-time cooperative guidance law based on an event-triggered mechanism. The settling time of the system states under this guidance law is independent of the initial states, and the upper bound of the settling time can be directly set by the explicit parameters in the guidance law. Firstly, the time-to-go estimate is taken as a consistency variable, and the communication failure and time-delay that are easily encountered during the communication process are taken into account; the event-triggered mechanism is introduced into the guidance law along the line of sight (LOS) direction, and the event-triggered threshold is given. Then, a predefined-time extended state observer is used to accurately estimate disturbances. In addition, the stability of the proposed guidance laws along and perpendicular to the LOS direction is proven by the Lyapunov theory. Finally, the superiority of the proposed guidance law introducing the event-triggered mechanism in reducing energy consumption and its effectiveness in encountering communication failure and time-delay are verified through simulations.

Adaptive Time-Varying Formation Maneuvering Control for Multi-Robot Systems in Complex Obstacle-Rich Environments

To tackle the challenge of time-varying formation control for underactuated robots under model parameter uncertainties and environmental disturbances, this study proposes an affine formation control approach enhanced by an Extended State Observer. Initially, using affine positioning theory and polynomial interpolation, guidelines for selecting leader vehicles and trajectory planning methods are established, whereby the trajectory of follower vehicles is uniquely determined through the stress matrix. To address the cumulative disturbances arising from model uncertainties and environmental factors impacting the formation, an Extended State Observer with optimized parameters is introduced. Furthermore, a distributed affine formation control method with disturbance rejection is designed specifically for underactuated robots with “nonlinear, strongly coupled” dynamics, ensuring that the formation system can track the target configuration within bounded error margins. Finally, theoretical analysis and simulation outcomes ultimately confirm the efficacy of the control approach in achieving resilient formation tracking.

The Response of Tropopause-Overshooting Convection over North America to Climate Change

Abstract Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo–global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-yr simulations consisting of 1) a retrospective period (2003–12) forced by ERA-Interim initial and boundary conditions (the control simulation) and 2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. In the PGW simulation, tropopause-overshooting convection is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (>4 km) is more frequent in a warmed climate scenario.

Discrete-time Luenberger observer design for Lithium-ion battery state-of-charge with stability guarantee

State-of-charge (SOC) estimation is particularly important as it provides information about the remaining energy capacity of the battery, allowing for better planning and utilization. Accurate SOC estimation is challenging because it cannot be directly measured from the battery. Instead, it is estimated by analyzing measurable variables such as current and voltage. To address this challenge, a discrete-time observer-based SOC estimation approach is proposed in this paper. This approach utilizes a second-order equivalent circuit model and a piecewise linear approximation to represent the relationship between SOC and open circuit voltage (OCV). The proposed observer-based approach utilizes these models to estimate the SOC with assured asymptotic stability under specific assumptions to simplify the design process. Simulations in Python are conducted to evaluate the performance of the designed observer. In the simulations, the SOC estimation under various conditions, such as model uncertainty, disturbances, and measurement noise, is also covered. In addition, three different observer gains are considered in the simulations. Lastly, simulation studies indicate that the estimated SOC values converge to the real SOC values, with some different behavior depending on the regarded situations.

Adaptive Robust Sensorless Control for PMSM Based on Improved Back EMF Observer and Extended State Observer

Adaptive Robust Sensorless Control for PMSM Based on Improved Back EMF Observer and Extended State Observer

Double-level prescribed performance control for rigid spacecraft attitude tracking under actuator faults

The problem of prescribed performance attitude tracking control for rigid spacecraft with external disturbance, inertia uncertainties and actuator faults on special orthogonal group SO(3) is investigated in this paper. With the aid of a novel Lyapunov function, a double-level prescribed performance controller is devised to ensure both attitude and angular velocity tracking errors converge within preset performance boundaries. By applying the suggested controller, the setting time, overshoot and steady-state error of both attitude and angular velocity tracking errors can be regulated by preset performance boundaries getting rid of the initial conditions of the control system. Distinguished from the exist prescribed performance controllers, a stricter performance boundary for angular velocity tracking error can be achieved. For the lumped disturbance which stems from the unknown external disturbance, inertia uncertainties and actuator faults, an extended state observer with linear feedback functions is initially designed to provide an estimation with simple structure. Rigorous proofs within a Lyapunov framework and comparison simulations are presented to demonstrate the effectiveness and superiority of the suggested control strategy.

Observer-based self-triggered adaptive decentralized control for uncertain interconnected nonlinear systems

In this paper, an observer-based self-triggered adaptive decentralized control method is presented for uncertain interconnected nonlinear systems (UINS) with unmeasured states. First, an adaptive state observer is constructed to estimate unmeasured system states. Then, the observer-based self-triggered controller is developed by applying the famous backstepping technique, in which the controller signal is updated based on the well-designed self-triggered protocol. Moreover, parameter adaptive laws are designed to address unknown parameters of UINS. Lyapunov theory is employed to prove that all signals of the UINS are semi-globally uniformly ultimately bounded (SGUUB) and the Zeno behavior will not appear. Simulation results manifest the efficacy of the derived self-triggered control solution.

A decoupling control of air supply for the PEM fuel cell with slide mode-active disturbance rejection controller

The air supply subsystem is crucial for optimizing proton exchange membrane fuel cells (PEMFCs). This study develops a transient model for the air subsystem and proposes a control strategy that decouples air pressure and flow using sliding mode-active disturbance rejection control (SM-ADRC). In this study, adjustments to the air compressor speed and the opening of the back-pressure valve are utilized to achieve this control strategy. The sliding mode-extended state observer (SM-ESO) is employed to estimate and compensate for uncertainties within the system, while the sliding mode-nonlinear state error feedback (SM-NLSEF) is used to simultaneously control air flow and pressure. The study evaluates the performance of the SM-ADRC controller across various scenarios and environmental pressures. Evaluations show that the SM-ADRC controller significantly outperforms traditional methods like Fuzzy-ADRC, ADRC, SMC, and PID, with overshoot reductions of 18.2%, 34.1%, 42.5%, and 63.7%, respectively, and adjustment time under 1 s. Additionally, SM-ADRC achieves a 4.1% and 1.8% improvement in efficiency compared to PID and ADRC.

On Active Disturbance Compression Control by Twice-Extended State Observer for Laser Pointing System

On Active Disturbance Compression Control by Twice-Extended State Observer for Laser Pointing System

Adaptive fuzzy optimal output-feedback fault-tolerant control for the USV system with intermittent actuator faults

This paper presents a novel fuzzy optimal output-feedback fault-tolerant control (FTC) method for uncertain nonlinear unmanned surface vehicle (USV) systems, which are subject to intermittent actuator failures and unmeasured states. The proposed optimal controller is composed of a fuzzy feedforward fault-tolerant output-feedback controller and a fuzzy error feedback optimal controller. The fuzzy feedforward fault-tolerant output-feedback controller is designed by using the fuzzy state observer and backstepping control design technique. The fuzzy optimal feedback controller is given by adopting adaptive dynamic programming (ADP) theory. It is proven that the presented fuzzy optimal FTC scheme is able to ensure that the USV system is uniformly ultimately bounded (UUB), and the optimal control performance is achieved. The validity is confirmed by computer simulation results.

Anti-Sway Adaptive Fast Terminal Sliding Mode Control Based on the Finite-Time State Observer for the Overhead Crane System

This work proposes an adaptive rapid terminal SMC (sliding mode control) approach based on the FFTSO (fast finite-time state observer) for overhead crane trajectory tracking and anti-swing control in the presence of external disturbances and parameter uncertainty. First, the system state observation under the constraint of unknown system parameters is accomplished by designing the FFTSO based on finite-time theory. Next, a parameter-adaptive fast terminal SMC is created for an overhead crane based on the model transformation. This technique can still monitor the intended trajectory and reduce payload swing even in cases when the payload mass and wire rope length are uncertain. Next, the Lyapunov theorem is used to demonstrate the stability of the overhead crane system’s positioning and anti-swing angle control mechanism. Lastly, the platform experiments confirm that the suggested closed-loop system control technique is successful.