State Estimation Research Articles

Improved Deadbeat Predictive Current Control With Extended State Observer for Dual Three-Phase PMSMs

Improved Deadbeat Predictive Current Control With Extended State Observer for Dual Three-Phase PMSMs

Adaptive differential steering strategy for distributed driving unmanned ground vehicle with variable configurations based on modified localized modelling sliding mode control

When performing complex tasks such as position transfer and material transportation, the distributed driving unmanned platform with variable configurations needs to address the challenge of multi-wheel cooperative torque distribution control to achieve high-performance differential steering and enhance vehicle dynamics. The configuration change will impact the dynamic performance of the unmanned platform, posing a challenge to the performance of the existing control strategy based on mathematical model development. In order to address the aforementioned issues, this paper analyzes the impact of changes in vehicle configuration on steering gain and proposes a hierarchical adaptive differential steering strategy based on variable vehicle configurations. Firstly, the response characteristics of the yaw angle relative to the active yaw moment under the influence of changes in wheelbase and tread are analyzed. Based on this analysis, two structural modes, maneuverable and balanced, are selected. Secondly, a localized-modelling sliding mode control method with an extended state observer is proposed to estimate the desired yaw moment in the upper controller, considering the motor's execution delay. Then, the lower controller optimizes the torque of each wheel in real-time using the whale optimization algorithm. It aims to optimize tire energy dissipation and tire load rate while ensuring driving stability and achieving differential steering. Finally, through co-simulation and experiments on a scaled prototype, the reliability of the dynamics theory and the superiority of the control algorithm are validated. This optimization has led to significant improvements in the tire dissipation energy index and tire load rate index.

Output-feedback path-following control of underactuated AUVs via singular perturbation and interconnected-system technique

This paper focuses on the output-feedback control for path-following of underactuated autonomous underwater vehicles subject to multiple uncertainties and unmeasured velocities. First, a novel extended state observer is proposed to estimate the mismatched lumped disturbance and recover the unmeasured velocities. Based on this premise, to overcome the limitation of relying solely on the accurate kinematic model, a disturbance observer-based stabilizing controller is developed. The difference in bandwidths between the observer and the vehicle dynamics allows for a mathematical setup amenable to standard singular perturbation theory. In the fast mode, a kinematic observer is designed to reject system uncertainty caused by unknown attack angular velocity and prohibitive path-tangential angular velocity, using a novel physical perspective. In the slow mode, an interconnected-system control law is proposed by integrating the backstepping technique with the time scale decomposition method. Furthermore, the stability of the overall closed-loop system is established. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method for path-following of underactuated autonomous underwater vehicles in the vertical plane.

An online battery–state of charge estimation method using the varying forgetting factor recursive least square - unscented Kalman filter algorithm on electric vehicles

Accurate and fast estimation of the state of charge is important for the battery management system of electric vehicles. This paper proposes a method to estimate the state of charge of Lithium-ion batteries by the <span lang="EN-US">variable</span> forgetting factor recursive least square (VFFRLS) – unscented Kalman filter (UKF) algorithm in real-time without the off-line battery testing data. Since the state observation requires an accurate model, an equivalent circuit model was constructed. Then, the VFFRLS algorithm is used to identify online the battery model parameters based on voltage and current measurements. An advantage of this algorithm is that it requires less initial information and shorter identification time than offline parameter identification. After the model parameters are well identified, the unscented Kalman filter estimates the state of charge and minimizes noise characteristics and uncertainty in the parameter identification process. The VFFRLS algorithm applied in this paper has shown a good result with the model output error of less than 1%, and the identification achieves real-time response. The state of charge obtained by the UKF algorithm has shown satisfactory estimation results with fast convergence speed and small errors. The UKF filter provides the results with a 1.5% error from the reference and converges after 10 cycles.

Robust predictive torque control of switched reluctance motor based on linear extended state observer

Robust predictive torque control of switched reluctance motor based on linear extended state observer

GRU-ESO Strategy for a Distributed Coil Magnetically Levitated Planar Micromotor.

Traditional magnetic levitation planar micromotors suffer from poor controllability, short travel range, low interference resistance, and low precision. To address these issues, a distributed coil magnetically levitated planar micromotor with a gated recurrent unit (GRU)-extended state observer (ESO) control strategy is proposed in this paper. First, the structural design of the distributed coil magnetically levitated planar micromotor employs a separation of levitation and displacement, reducing system coupling and increasing controllability and displacement range. Then, theoretical analysis and model establishment of the system are conducted based on the designed distributed coil magnetically levitated planar micromotor and its working principles, followed by simulation verification. Finally, based on the established system model, a GRU-ESO controller is designed. An ESO feedback control term is introduced to enhance the system's anti-interference capability, and the GRU feedforward compensation control term is used to improve the system's tracking control accuracy. The experimental results demonstrate the reliability of the designed distributed coil magnetic levitation planar micromotor and the effectiveness of the controller.

Robust distributed fixed-time cooperative hunting control for multi-quadrotor with obstacles avoidance

This paper addressed the robust distributed fixed-time cooperative hunting problem of multiple quadrotors subject to disturbances in obstacles environment. To handle the underactuated issue inherent in quadrotor dynamics, an inner–outer (attitude-position) loop cascade control configuration is proposed to achieve the cooperative flight control of quadrotors. For position subsystem, as the information of target cannot be accessible to all quadrotors, a distributed fixed-time observer is devised to estimate the target’s information. To improve the system’s robustness, a fixed-time extended state observer is designed to reject disturbances actively. Based on two observers, the sliding mode position encirclement control protocol with repulsive force is presented to avoid obstacles and encircle the target within a fixed time. For attitude subsystem, a sliding mode attitude tracking control protocol is proposed such that tracking errors can converge to zero even under disturbances. The stability analysis is performed to show the stabilization of the whole closed-loop system with fixed-time convergence. Finally, two sets of comparison simulation are provided to show the superiority of the developed control strategy.

Correlations in the EPR State Observables.

The identification and physical interpretation of arbitrary quantum correlations are not always effortless. Two features that can significantly influence the dispersion of the joint observable outcomes in a quantum bipartite system composed of systems I and II are: (a) All possible pairs of observables describing the composite are equally probable upon measurement, and (b) The absence of concurrence (positive reinforcement) between any of the observables within a particular system; implying that their associated operators do not commute. The so-called EPR states are known to observe (a). Here, we demonstrate in very general (but straightforward) terms that they also satisfy condition (b), a relevant technical fact often overlooked. As an illustration, we work out in detail the three-level systems, i.e., qutrits. Furthermore, given the special characteristics of EPR states (such as maximal entanglement, among others), one might intuitively expect the CHSH correlation, computed exclusively for the observables of qubit EPR states, to yield values greater than two, thereby violating Bell's inequality. We show such a prediction does not hold true. In fact, the combined properties of (a) and (b) lead to a more limited range of values for the CHSH measure, not surpassing the nonlocality threshold of two. The present constitutes an instructive example of the subtleties of quantum correlations.

A contact binary satellite of the asteroid (152830) Dinkinesh

Asteroids with diameters less than about 5 km have complex histories because they are small enough for radiative torques (that is, YORP, short for the Yarkovsky–O’Keefe–Radzievskii–Paddack effect)1 to be a notable factor in their evolution2. (152830) Dinkinesh is a small asteroid orbiting the Sun near the inner edge of the main asteroid belt with a heliocentric semimajor axis of 2.19 au; its S-type spectrum3,4 is typical of bodies in this part of the main belt5. Here we report observations by the Lucy spacecraft6,7 as it passed within 431 km of Dinkinesh. Lucy revealed Dinkinesh, which has an effective diameter of only 720 m, to be unexpectedly complex. Of particular note is the presence of a prominent longitudinal trough overlain by a substantial equatorial ridge and the discovery of the first confirmed contact binary satellite, now named (152830) Dinkinesh I Selam. Selam consists of two near-equal-sized lobes with diameters of 210 m and 230 m. It orbits Dinkinesh at a distance of 3.1 km with an orbital period of about 52.7 h and is tidally locked. The dynamical state, angular momentum and geomorphologic observations of the system lead us to infer that the ridge and trough of Dinkinesh are probably the result of mass failure resulting from spin-up by YORP followed by the partial reaccretion of the shed material. Selam probably accreted from material shed by this event.

Model-free Predictive Trajectory Tracking Control and Obstacle Avoidance for Unmanned Surface Vehicle With Uncertainty and Unknown Disturbances via Model-free Extended State Observer

Model-free Predictive Trajectory Tracking Control and Obstacle Avoidance for Unmanned Surface Vehicle With Uncertainty and Unknown Disturbances via Model-free Extended State Observer

Adaptive RISE Control of Winding Tension with Active Disturbance Rejection

A winding system is a time-varying system that considers complex nonlinear characteristics, and how to control the stability of the winding tension during the winding process is the primary problem that has hindered development in this field in recent years. Many nonlinear factors affect the tension in the winding process, such as friction, structured uncertainties, unstructured uncertainties, and external interference. These terms severely restrict the tension tracking performance. Existing tension control strategies are mainly based on the composite control of the tension and speed loops, and previous studies involve complex decoupling operations. Owing to the large number of calculations required for this method, it is inconvenient for practical engineering applications. To simplify the tension generation mechanism and the influence of the nonlinear characteristics of the winding system, a simpler nonlinear dynamic model of the winding tension was established. An adaptive method was applied to update the feedback gain of the continuous robust integral of the sign of the error (RISE). Furthermore, an extended state observer was used to estimate modeling errors and external disturbances. The model disturbance term can be compensated for in the designed RISE controller. The asymptotic stability of the system was proven according to the Lyapunov stability theory. Finally, a comparative analysis of the proposed nonlinear controller and several other controllers was performed. The results indicated that the control of the winding tension was significantly enhanced.

Polarization-resolved near-field characterization of coupling between a bus waveguide and a ring resonator

Light propagation in Photonic integrated circuits (PICs), which can nowadays involve complex systems of light-guiding structures, is measured with different approaches(Nuzhdin et al., 2020, Lončar et al., 2002, Hopman et al., 2007, Morichetti et al., 2014, Sapienza et al., 2012, Vesseur et al., 2007). An interferometric polarization-sensitive measurement of the evanescent fields of these structures provides insight in the performance of the circuit detects possible malfunction with sub-wavelength precision(Engelen et al., 2007, Gersen et al., 2005, Barwick et al., 2009). We demonstrate a Near-field scanning optical microscopy (NSOM) measurement on coupled ring resonators that shows how the guided modes evolve as they propagate across the optical chip. Analysis of the measurements provides information about intensity distribution of the two polarization components (TE and TM) and their spatial confinement. The data validates our methodology and opens new possibilities for analysis of signal propagation in prototyping and optimization of integrated optical systems. Direct observation of polarization state of the guided modes allows for clear understanding of mode conversion in coupling systems.

Fabrication of a Cancer Cell Aggregate Culture Device That Facilitates Observations of Nutrient and Oxygen Gradients.

Three-dimensional cell culture spheroids are commonly used for drug evaluation studies because they can produce large quantities of homogeneous cell aggregates. As the spheroids grow, nutrients supplied from outer spheroid regions render the inner spheroid areas hypoxic and hyponutrient, which makes them unobservable through confocal microscopy. In this study, we fabricated a cancer cell aggregate culture device that facilitates the observation of nutrient and oxygen gradients. An alginate gel fiber was created in the cell culture chamber to ensure a flow path for supplying the culture medium. A gradient of nutrients and oxygen was generated by positioning the flow channel close to the edge of the chamber. We devised a fabrication method that uses calcium carbonate as a source of Ca2+ for the gelation of sodium alginate, which has a slow reaction rate. We then cultured a spheroid of HCT116 cells, which were derived from human colorectal carcinoma using a fluorescent ubiquitination-based cell cycle indicator. Fluorescence observation suggested the formation of a hypoxic and hyponutrient region within an area approximately 500 µm away from the alginate gel fiber. This indicates the development of a cancer cell aggregate culture device that enables the observation of different nutrition and oxygen states.

Hadronization of heavy quarks

Heavy-flavor hadrons produced in ultrarelativistic heavy-ion collisions are a sensitive probe for studying hadronization mechanisms of the quark-gluon-plasma. In this paper, we survey how different transport models for the simulation of heavy-quark diffusion through a quark-gluon plasma in heavy-ion collisions implement hadronization and how this affects final state observables. Utilizing the same input charm-quark distribution in all models at the hadronization transition, we find that the transverse-momentum dependence of the nuclear modification factor of various charm hadron species has significant sensitivity to the hadronization scheme. In addition, the charm-hadron elliptic flow exhibits a nontrivial dependence on the elliptic flow of the hadronizing partonic medium. Published by the American Physical Society 2024

Neural adaptive dynamic surface control for position tracking of electrohydraulic servo systems based on extended state observer

High-performance motion tracking of electro-hydraulic servo systems plays an important role in developing industrial technology. However, the system itself has parameter uncertainty, uncertain nonlinearity, and measurement noise, significantly decreasing the performance of conventional controllers designed based on nominal models. To improve the tracking performance of electro-hydraulic servo systems, an adaptive dynamic surface control method combining extended state observer and radial basis function neural network is proposed. Firstly, an extended state observer combining neural network output and parameter adaptation technology is designed without the need for speed and pressure feedback to observe the system’s unknown state variables and nonlinear matched disturbance. The design of neural networks is used to approximate mismatched disturbance with significant nonlinearity online. Then, the proposed extended state observer is introduced into the neural adaptive backstepping design, effectively compensating for simultaneous matched and mismatched disturbances, thereby suppressing most of the uncertain nonlinearity of the system. Meanwhile, online update of uncertain parameters further improves the tracking performance of the controller. In addition, the introduction of dynamic surface overcomes the “explosion of complexity” issue in backstepping design. The rigorous stability of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness of the proposed controller is validated through comparative experiments on valve-controlled hydraulic cylinder.

Systematic Control Design for Adaptive Rejection of Narrow-Band Disturbances Based on a Novel Resonant Generalized Extended State Observer

In this paper, the adaptive rejection of multiple narrow-band disturbances with time-varying frequencies is investigated. A systematic control approach based on a resonant generalized extended state observer (RGESO) is proposed. The frequency response of the RGESO is shaped into a desired form to reject the total disturbance, including the wide-band uncertainties and the narrow-band disturbances. The state-space realization of the RGESO is also provided to estimate both the states and the total disturbance. To handle the time-varying frequencies of the narrow-band disturbances, a direct frequency estimation approach based on the Levenberg–Marquardt method and an online supervision strategy is presented to improve convergence and reliability, and the estimations are then used to adapt the RGESO parameters. Parameter tuning and stability robustness analysis methods are also developed for the proposed scheme to facilitate its application. Finally, extensive simulations are conducted to demonstrate the effectiveness of our method.

Asymptotic adaptive output-feedback stabilisation of nonlinear systems with unknown growth rate and sensor uncertainty

For a class of nonlinear systems with sensor uncertainty, the problem of adaptive output feedback stabilisation is investigated in this paper. It is assumed that only the output is available for feedback control, which suffers from sensor uncertainty. At the same time, the nonlinear function in the system model has an unknown growth rate. To solve this problem, a set of state observers is designed to estimate the unknown system states based on the uncertain output, and an adaptive output-feedback control is designed based on this. By using the corollary of Barbalet's Lemma, it is shown that the equilibrium of the closed-loop system is asymptotically stable. Finally, simulation results verify the effectiveness of the control scheme

GESO based RISE Controller for Active Flutter Suppression for Aeroelastic System

Abstract The paper presents a Robust Integral of Signum of Error (RISE) controller for active suppression of flutter of a two dimensional aerofoil and it is integrated with a General Extended State Observer (GESO). Towards this, aerofoil model in state space is first changed into a canonical form. Then, the controller is designed using RISE control technique. As equations of system dynamics are not into integral chain form, a GESO is formulated to observe system states and disturbances. The controller is implemented using estimated states and it is robustified using estimated disturbance. Stability of the proposed GESO-RISE controller is established using the Lyapunov theory. Simulations are performed to check the proposed controller's performance against variations in airspeed, uncertainties in model parameters, external disturbances, time delay and unmodeled dynamics. Comparison of the proposed GESO-RISE controller is carried out with existing controllers using two performance criteria i.e. Control Efforts and Integral of Absolute Error (IAE). It is discovered from simulations that the proposed GESO-RISE controller significantly reduces IAE and control efforts. Additionally, Monte Carlo method is utilized to check robustness of the proposed GESO-RISE controller. The proposed GESO-RISE controller significantly enhances flutter boundary of aerofoil and is completely implementable.

Data-driven estimation of the algebraic Riccati equation for the discrete-time inverse linear quadratic regulator problem

In this paper, we propose a method for estimating the algebraic Riccati equation (ARE) with respect to an unknown discrete-time system from the system state and input observation. The inverse optimal control (IOC) problem asks, “What objective function is optimized by a given control system?” The inverse linear quadratic regulator (ILQR) problem is an IOC problem that assumes a linear system and quadratic objective function. The ILQR problem can be solved by solving a linear matrix inequality that contains the ARE. However, the system model is required to obtain the ARE, and it is often unknown in fields in which the IOC problem occurs, for example, biological system analysis. Our method directly estimates the ARE from the observation data without identifying the system. This feature enables us to economize the observation data using prior information about the objective function. We provide a data condition that is sufficient for our method to estimate the ARE. We conducted a numerical experiment to demonstrate that our method can estimate the ARE with less data than system identification if the prior information is sufficient.

Distributed finite-time adaptive consensus output-feedback control of multi-agent systems under switching topologies

The paper investigates the finite-time adaptive consensus control of nonlinear multi-agent systems (MASs) by output-feedback. During the process of control design, the fuzzy logic system (FLS) is employed to approximate nonlinear function, as well as constructing a fuzzy state observer to estimate unmeasured states. Combining the dynamic surface control (DSC) with adaptive backstepping method conquers the complexity explosion issue. Then, semi-global practical finite-time stability (SGPFS) for closed-loop system is obtained under arbitrary switching communication topologies. All the signals of the overall system are uniformly ultimately bounded (UUB). Finally, the availability of developed control approach will be demonstrated through a simulation.