State Estimation Research Articles

Super-twisting ADRC for maximum power point tracking control of photovoltaic power generation system based on non-linear extended state observer

This paper proposed a new method for maximum power point tracking in photovoltaic power generation systems by combining super-twisting sliding mode control and active disturbance rejection method. An incremental guidance method is used to find the point of maximum power. The non-linear extended state observer is applied to estimate the unmodeled dynamics and external disturbance. The ADRC based on a super-twisting sliding mode is designed to bring the state variables to the desired state. In the next step, the stability of NESO and ADRC are theoretically proved. Finally, the simulation results have been compared with the results of the PI controller, classical sliding mode control, and terminal sliding mode control (TSMC) presented in other articles. The results show the effectiveness and superiority of the proposed method.Also, to check the performance of the proposal method in real-time, real-time results have been compared with non-real-time results. The results obtained from the real-time and non-real-time simulations exhibited a minimal difference. This fact indicates the high accuracy of the modeling and simulations performed. Indeed, the mathematical models and non-real-time simulations have been able to accurately mimic the actual behavior of the photovoltaic system under various operating conditions.

Active disturbance rejection control of a bearingless permanent magnet slice motor

Abstract Bearingless permanent magnet slice motor has the advantages of easy stator-rotor isolation, no contact, simple structure, and high integration, which is a significant feature in the ultra-pure field of biology, chemistry, medical treatment, semiconductor manufacturing, aerospace, and other applications, as well as high-speed drive field. To realize the control of a bearingless permanent magnet slice motor, the mechanism of torque control, as well as suspension control, is systematically analyzed. On this basis, a simplified control parameter design method for decoupling torque and suspension is proposed, and the parameter tuning rules are given. For the problem of insufficient anti-disturbance performance of the suspension control under the traditional linear active disturbances rejection controller (LADRC), an improved LADRC strategy based on known disturbances is proposed, and an expansion state observer (ESO) with partially known disturbances is designed. The suspension accuracy and robustness of the system are verified by simulating the motor control with a Matlab/Simulink module. Finally, the improved LADRC control is used in a BPMSM prototype. The simulation and experimental results show that the improved LADRC control with the addition of known perturbations effectively improves the suspension control stability and accuracy compared to the traditional LADRC control.

Output feedback active disturbance rejection control of an electro-hydraulic servo system based on command filter

The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper. First, a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated. Due to the fact that only position information can be measured, a linear Extended State Observer (ESO) is introduced to estimate unknown states and matched disturbances, while a dedicated disturbance observer is constructed to estimate mismatched disturbances. Different from the traditional observer results, the design of the disturbance observer used in this study is carried out under the constraint of output feedback. Furthermore, an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking. To mitigate the inherent differential explosion problem of the traditional backstepping framework, a finite-time stable command filter is incorporated. Simultaneously, considering transient filtering errors, a set of error compensation signals are designed to counter their negative impact effectively. Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system. Additionally, under the specific condition of only time-invariant disturbances in the system, the conclusion of asymptotic stability is established. Finally, the algorithm’s efficacy is validated through comparative experiments.

Survival Probability, Particle Imbalance, and Their Relationship in Quadratic Models.

We argue that the dynamics of particle imbalance in quadratic fermionic models is, for the majority of initial many-body product states in the site occupation basis, virtually indistinguishable from the dynamics of survival probabilities of single-particle states. We then generalize our statement to a similar relationship between the non-equal time and space density correlation functions in many-body states, and the transition probabilities of single-particle states at nonzero distances. Finally, we study the equal-time connected density-density correlation functions in many-body states, which exhibit certain qualitative analogies with the survival and transition probabilities of single-particle states. Our results are numerically tested for two paradigmatic models of single-particle localization: the 3D Anderson model and the 1D Aubry-André model. This work gives an affirmative answer to the question of whether it is possible to measure features of single-particle survival and transition probabilities by the dynamics of observables in many-body states.

Path following of underactuated surface vessels based active disturbance rejection control considering lateral drift

To address the challenges posed by unmodeled dynamics, lateral drift, external disturbances, and the difficulty in measuring velocities in underactuated surface vessels (USVs) motion systems, an active disturbance rejection control (ADRC) with two linear extended state observers (LESO) is proposed for USV path following. Firstly, we employ the Backstepping technique to create a virtual heading angle while estimating lateral drift and unmodeled dynamics using LESO. Subsequently, the ADRC algorithm is employed to control the heading angle. Since measuring the velocities of USV is challenging, velocity observers are introduce to estimate surge and sway velocities. Finally, we utilize the MMG model with high precision to track straight-line and curved paths, respectively. Simulation results validate that our developed controller accurately follows the reference path even in the presence of disturbances, affirming the effectiveness of our proposed control strategy.

Unmanned Floating Object Transportation Applying Multiple Dynamic Positioning Tugboats: A Novel Cooperative Control Algorithm

Abstract To promote the automation and intelligence of marine floating object transportation, this paper proposes a cooperative consensus control algorithm for multiple unmanned dynamic positioning (DP) tugboats to transport an unactuated floating structure object using cables. The major concept of present algorithm is to implement a leader-follower formation strategy among distributed tugboats, with the aim of effectively maneuvering the object by adjusting the relative position between the virtual leader and the object in a reasonable manner. A cooperative consensus controller is integrated into the feedback controller of each tugboat local DP system in order to facilitate cooperative coordination among tugboats in a formation. A customized DP system, which incorporates the radial basis function neural network supervisor control into the DP controller design and introduces nonlinear disturbance observer into the low-frequency motion state observer design, is proposed to address cable tension disturbances, and thus, the tracking performance of the DP tugboat is improved. Full-scale nonlinear time domain simulations are performed under variable environmental conditions, verifying the effectiveness of the proposed automatic towing control scheme.

Addressing Launch and Deployment Uncertainties in UAVs with ESO-Based Attitude Control

This paper describes the design and implementation of a novel three-axis attitude control autopilot scheme for tube-launched, air-deployed UAVs. In early flight tests, various factors, such as model uncertainties during launch, aerodynamic uncertainties, geometric parameter changes during deployment, and significant uncertainties in booster rocket installation, exceeded the control capabilities of the attitude autopilot, causing flight instability. In order to address these issues, a numerical simulation model of the full launch process considering deviations was established based on early flight tests. A cascade attitude controller was then designed using an extended state observer (ESO), and the boundedness of control errors under unknown bounded disturbances was theoretically proven, providing requirements for the parameter tuning of the cascade controller. Comparative experiments and a second flight test both demonstrate that the ESO-based cascade attitude controller exhibits strong feedforward disturbance compensation under high-uncertainty conditions, effectively achieving stable control within the flight envelope.

Safe MPC-based disturbance rejection control for uncertain nonlinear systems with state constraints

This paper studies a safe model predictive control (MPC)-based disturbance rejection control for a broad range of uncertain nonlinear systems subject to complex state safety constraints. The system under study is composed of a nominal model and an uncertain term that encapsulates modeling uncertainty, control mismatch, and external disturbances. In order to estimate the system state and total uncertainty, an extended state observer (ESO) is first designed. Utilizing the output of the ESO, the control compensates for the total uncertainty in real time and concurrently implements a control barrier function (CBF)-based MPC for the compensated system. The proposed control framework guarantees both safety and disturbance rejection. Compared to the baseline algorithm CBF-MPC, the proposed method significantly enhances system stability with a smaller root mean square (RMS) error of the system state from the equilibrium point. Rigorous theoretical analysis and simulation experiments are provided to validate the effectiveness of the proposed scheme.

Composite sliding mode control for cyber‐physical systems with multi‐source disturbances and false data injection attack

AbstractThis paper investigates the sliding mode control problem for cyber‐physical systems subject to multi‐source disturbances and actuator false data injection attacks simultaneously. Firstly, a series of extended state observers are designed to estimate the unknown multi‐source disturbances. For the actuator false data injection attacks, a sliding mode observer is designed to online estimate the values of attacks. Then, by introducing the disturbance and attack estimations, a dynamic sliding manifold and a composite sliding mode controller are constructed. Under the proposed approach, the unknown disturbances and false data injection attacks can be timely estimated and compensated, which can improve the disturbance rejection ability and guarantee security of the cyber‐physical system. Lyapunov theory is utilized to prove the stability of the closed‐loop system. Finally, simulations of both the numerical example and application to a power converter system demonstrate the effectiveness and superiority of the proposed composite sliding mode control approach.

Observer-based guaranteed-cost bipartite time-varying formation tracking control for multiagent systems subject to communication delays

The paper centers on the guaranteed-cost bipartite time-varying formation tracking control for multiagent systems with nonuniform time-varying communication delays under the framework of a distributed observer. An integral quadratic cost function is presented, founded on formation tracking and observation error. Firstly, distributed state observers, using the relative measurement output between neighbors, are established so that the leader and follower can accurately estimate each agent's unmeasurable state. Subsequently, a bipartite formation tracking protocol is proposed, incorporating estimation information and nonuniform time-varying communication delays. This protocol aims to achieve bipartite time-varying formation tracking for multiagent systems. Next, a new augmented Lyapunov-Krasovskii functional with delay-product and triple integral terms is constructed. By integrating the second-order Bessel-Legendre inequality technique, the delay-dependent reciprocally convex combination inequality method, and the free weight matrix technique, a new guaranteed-cost bipartite time-varying formation tracking criterion is developed, offering less conservatism. Compared to certain existing delay conditions, the stability conditions assure a greater allowable upper bound of delay. Finally, a numerical example is conducted to confirm the validity and superiority of the theoretical findings.

A Novel Repeat PI Decoupling Control Strategy with Linear Active Disturbance Rejection for a Three-Level Neutral-Point-Clamped Active Power Filter with an LCL Filter

The three-level neutral-point-clamped (NPC) active power filter (APF) is suitable for harmonic compensation in high voltage and large capacity applications. And, the harmonic compensation effect of APF depends on its dynamic performance and control. This paper propose a repeat proportional integral (PI) decoupling control strategy with linear active disturbance rejection (LADRC) to address the issues of detection in complex harmonic current and power supply current distortion when the nonlinear load varies. To simplify the design of LADRC, this paper adopts inverter current feedback control. Firstly, repeat control is introduced to optimize the traditional PI controller, which improves the compensation accuracy while ensuring the dynamic response capability of the control system. Then, to address the serious coupling of the system model in the d-q coordinate system, a reduced order linear active disturbance rejection (LADRC) control is introduced. The PI and linear extended state observer (LESO) control method is adopted in the outer voltage loop to maintain stable DC voltage and improve the ability to suppress voltage overshoot during grid connection. The effectiveness of this control method has been verified through MATLAB/Simlink. The results show that, compared with the repeat PI method, the control method based on repeat PI–LADRC can achieve better decoupling control, improve robustness and anti-interference ability, enhance the performance of the original system, and can significantly improve the harmonic suppression capability of the APF.

Robust adaptive attitude control for agile maneuver of quadrotors based on finite-time geometric extended state observer

Robust adaptive attitude control for agile maneuver of quadrotors based on finite-time geometric extended state observer

Distributed control for DC microgrids with cyber attacks and constraints: A fault-tolerant model predictive controller

Communication security issues pose severe challenges to stability of microgrid system. This paper designs a cooperative control method based on fault-tolerant distributed model predictive control (DMPC) for DC microgrid against possible false information injection (FDI) attacks and communication constraints problems. First, a state variable is defined based on the voltage and current information, thereby deriving a system model of the microgrid under the cyber-physical framework. Then, since a combined uncertainty term consisting of attacks and disturbances exists in the constructed system model, an expanded state observer (ESO) is proposed to observe the uncertainty term. Further, based on the constructed system model and the designed ESO, a fault-tolerant distributed model predictive controller is designed. In the controller, DMPC is utilized to constrain the communication information and ensure the boundedness of the communication state and physical state. Simulation results indicate that the proposed DMPC-based distributed control method can achieve stable voltage regulation and accurate current sharing, and maintain smooth operation even under FDI attack, which verifies the feasibility for the proposed method.

Dynamic surface control for satellite attitude of the chained three-body tethered system during deployment

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.

Cascaded safety trajectory tracking control for a hovercraft with double-loop prescribed performance and state constraints

ABSTRACT This paper presents a cascaded safety trajectory tracking control scheme for hovercraft, addressing dump disturbances with a novel double-loop strategy that enforces prescribed performance and state constraints. Initially, an Adaptive Prescribed-Time Extended State Observer (APESO) is meticulously crafted to estimate lumped disturbances accurately. Subsequent to this, virtual velocity control laws are established through Double Power Appointed-Time Performance Function (DPATPF) combined with an Asymmetric Barrier Lyapunov Function (ABLF), streamlining the position error into a more manageable, equivalent unconstrained control system format. To effectively manage velocity safety constraints, a Unified Barrier Function (UBF) is introduced, ensuring that hovercraft velocities adhere to asymmetric safety boundary. The entire system state is rigorously ultimately uniformly bounded, in strict compliance with cascade control theories and Lyapunov stability criteria. Through simulation, we demonstrate the superior performance and effectiveness of the proposed control strategy, showcasing its potential for enhancing hovercraft navigational safety and reliability.

Observer-based adaptive fuzzy control of stabilized platform in rotary steerable system with input saturation and output constraint

This paper explores the control strategy for toolface tracking in the stabilized platform of a rotary steerable system, considering both input saturation and output constraint. To mitigate the impact of unknown friction torque and modeling error on the stabilized platform, we propose an adaptive fuzzy backstepping control approach. A fuzzy state observer is specifically devised to handle the uncertain state arising from unknown friction torque and modeling errors. Introducing an auxiliary system effectively compensates for input saturation, and the resolution of the output error constraint is achieved through the construction of a barrier Lyapunov function. Furthermore, employing the Lyapunov method establishes that all signals in the entire closed-loop control system are semi-globally uniformly ultimately bounded. Simulation results confirm the efficacy of the proposed control methodology.

ОБЗОР СЕЛЕВОЙ ОПАСНОСТИ ДОЖДЕВОГО ГЕНЕЗИСА ПО ГОРНОЙ ТЕРРИТОРИИ РЕСПУБЛИКИ КАЗАХСТАН ЗА 2023 ГОД

The review was prepared based on the results of monitoring the debris-flow hazard caused by rainfall in the mountainous territory of the Republic of Kazakhstan for 2023. Monitoring was carried out for debris-flow hazard areas of Almaty, Zhetysu, Zhambyl, Turkestan, Mangistau, Abay and East Kazakhstan regions. The Ile, Kungey, Teriskey, Zhetysu, Kyrgyz and Talas Alatau, Ugam, Mangystau, Saur, Tarbagatai and Kazakhstan Altai mountains ridges are debris-flow hazard areas. The Review contains a map of debris-flow hazard on the territory of the Republic of Kazakhstan, information on the hydrometeorological situation and debris f low occurrences during the 2023 debris-flow-hazardous period. In the monitoring process information from the state observation network of the RSE «Kazhydromet» in operational mode, synoptic and numerical weather forecasts of the RSE «Kazhydromet» was used, etc.

QCD equation of state and thermodynamic observables from computationally minimal Dyson-Schwinger equations

We study the QCD equation of state and other thermodynamic observables including the isentropic trajectories and the speed of sound. These observables are of eminent importance for the understanding of experimental results in heavy ion collisions and also provide a QCD input for studies of the timeline of heavy-ion-collisions with hydrodynamical simulations. They can be derived from the quark propagator whose gap equation is solved within a minimal approximation to the Dyson-Schwinger equations (DSEs) of QCD at finite temperature and density. This minimal approximation aims at a combination of computational efficiency and simplification of the truncation scheme while maintaining quantitative precision. This minimal DSE scheme is confronted and benchmarked with results for correlation functions and observables from lattice QCD at vanishing density and quantitative functional approaches at finite density. Published by the American Physical Society 2024

Stable convergence of conditional least squares estimators for supercritical continuous state and continuous time branching processes with immigration

We prove stable convergence of conditional least squares estimators of drift parameters for supercritical continuous state and continuous time branching processes with immigration based on discrete time observations.

Tax evasion, education and shadow economy

The aim of the paper is to evaluate the influence of education on tax evasion. This study proposes a theoretical model, in which an agent can choose to allocate his labor effort between two production technologies. Higher levels of education lead to more skilled and specialized workers, and the tax authority can observe the use of advanced tools and equipment. The main result is that an increase in the general level of education leads to a labor effort substitution effect, showing that higher education can reduce tax evasion and the size of the shadow economy. Both static and dynamic estimation techniques are employed to test the theoretical findings, using a sample of 133 countries, over the period 2001–2020. The empirical analysis confirms the significant negative association between education and shadow economy.