State Estimation Research Articles

Adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems with unmeasurable states

This paper addresses the adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems, where the states and nonlinear functions are not feasible for the controller design. To address the issue of unmeasurable states, a state observer is developed, and fuzzy logic systems are utilized to approximate unknown nonlinear functions. Under the framework of fixed-time Lyapunov function theory and cooperative control, an adaptive fixed-time fuzzy containment control protocol is derived via the adaptive backstepping and adding one power integrator method. The derived fixed-time containment controller can confirm that the closed-loop systems are practical fixed-time stable, which implies that all signals in the systems are bounded and all follower agents can converge to the convex hull formed by the leader agents within fixed-time in the presence of unmeasurable states and unknown nonlinear functions . Simulation examples are conducted to test the validity of the present control algorithm.

ADRC‐based symmetric phase‐locked loop structure for improving low‐frequency stability of grid‐connected inverters

AbstractWith a small short‐circuit ratio (SCR), the grid‐connected inverter is prone to low‐frequency oscillation instability due to the dynamic interaction between the phase‐locked loop (PLL) and the weak grid. To this end, an active‐disturbance‐rejection‐controller‐based symmetric PLL (ADRC‐based SyPLL) is proposed in this article to simplify the system modelling and improve the low‐frequency stability of the inverter system. Specifically, the ADRC technique is applied to phase‐regulated feedback control of a PLL, where an extended state observer (ESO) is used to estimate the lumped disturbance of the controlled system. A control loop symmetric to the q‐axis is further designed on the d‐axis of the PLL, and the d‐axis information is then added at the reference generation side to eliminate the coupled frequency term in the small‐signal model. A simple and accurate single‐input single‐output (SISO) model is thus obtained. The impedance stability analysis for grid‐connected inverters shows that the proposed ADRC‐based SyPLL can significantly improve the low‐frequency stability margin of the system compared with the conventional PI‐regulated PLL. Finally, the experimental results validate the effectiveness and superiority of the proposed method.

Data‐driven nonlinear state observation for controlled systems: A kernel method and its analysis

AbstractThis work proposes a data‐driven state observation algorithm for nonlinear dynamical systems, when the true state trajectory is not measurable and hence the states information needs to be reconstructed from input and output measurements. Such a reduction is formed by kernel canonical correlation analysis (KCCA), which (i) implicitly maps the available input–output data into a higher‐dimensional feature space, namely the reproducing kernel Hilbert space (RKHS); (ii) finds a projection of the past input–output data and a projection of the future input–output data with maximal correlation; and (iii) identifies the projected inputs and outputs, namely the canonical variates, as the observed states. We adopt a least squares support vector machine (LS‐SVM) formulation for KCCA, which imposes regularization on the vectors that specify the projections and is amenable to convex optimization. We prove theoretically that, based on the statistical consistency of KCCA, the observed states determined by the proposed state observer has a guaranteed correlativity with the actual states (when properly transformed). Furthermore, such observed states, when supplemented with the information of succeeding inputs, can be used to predict the succeeding outputs with guaranteed upper bound on the prediction error. Case studies are performed on two numerical examples and an exothermic continuously stirred tank reactor (CSTR).

Influence of Magnetic Sublattice Ordering on Skyrmion Bubble Stability in 2D Magnet Fe5GeTe2.

The realization of above room-temperature ferromagnetism in the two-dimensional (2D) magnet Fe5GeTe2 represents a major advance for the use of van der Waals (vdW) materials in practical spintronic applications. In particular, observations of magnetic skyrmions and related states within exfoliated flakes of this material provide a pathway to the fine-tuning of topological spin textures via 2D material heterostructure engineering. However, there are conflicting reports as to the nature of the magnetic structures in Fe5GeTe2. The matter is further complicated by the study of two types of Fe5GeTe2 crystals with markedly different structural and magnetic properties, distinguished by their specific fabrication procedure: whether they are slowly cooled or rapidly quenched from the growth temperature. In this work, we combine X-ray and electron microscopy to observe the formation of magnetic stripe domains, skyrmion-like type-I, and topologically trivial type-II bubbles, within exfoliated flakes of Fe5GeTe2. The results reveal the influence of the magnetic ordering of the Fe1 sublattice below 150 K, which dramatically alters the magnetocrystalline anisotropy and leads to a complex magnetic phase diagram and a sudden change of the stability of the magnetic textures. In addition, we highlight the significant differences in the magnetic structures intrinsic to slow-cooled and quenched Fe5GeTe2 flakes.

Attitude Control of a Mass-Actuated Fixed-Wing UAV Based on Adaptive Global Fast Terminal Sliding Mode Control

Compared with traditional control methods, moving mass control (MMC) enhances the aerodynamic efficiency and stealth performance of fixed-wing unmanned aerial vehicles (FWUAVs), thereby facilitating their broader application in military and civilian fields. Nevertheless, this approach increases system complexity, nonlinearity, and coupling characteristics. To address these challenges, a novel attitude controller is proposed using adaptive global fast terminal sliding mode (GFTSM) control. Firstly, a dynamic model is established based on aerodynamics, flight dynamics, and moving mass dynamics. Secondly, to improve transient and steady-state responses, prescribed performance control (PPC) is adopted, which enhances the controller’s adaptability for mass-actuated aircraft. Thirdly, a fixed-time extended state observer (FTESO) is utilized to solve the inertial coupling issue caused by mass block movement. Additionally, the performance of the entire control system is rigorously proven through the Lyapunov function. Finally, numerical simulations of the proposed controller are compared with those of PID and linear ADRC in three different conditions: ideal conditions, fixed aerodynamic parameters, and nonlinear aerodynamic parameter changes. The results indicate that the controller effectively compensates for the system’s uncertainty and unknown disturbances, ensuring rapid and accurate tracking of the desired commands.

Observer‐based finite‐time time‐varying elliptical formation control of a group mobile mecanum‐wheeled omnidirectional vehicles for collaborative wildfire monitoring

AbstractThis article addresses the issue of collaborative wildfire monitoring using a group mobile mecanum‐wheeled omnidirectional vehicles (MWOVs) affected by nonlinear uncertainties and external disturbances. By integrating finite‐time extended state observers (FTESO) and backstepping nonsingular fast terminal sliding mode (BNFTSM) control method, an observer‐based finite‐time time‐varying elliptical formation control scheme is proposed for a group of MWOVs tasked with monitoring the propagation of wildfires in an elliptical pattern. First, the FTESO is employed to estimate the unavailable velocity system states and the lumped disturbances. Then, a novel nonsingular fast terminal sliding surface, enhanced with an exponential term, is introduced to improve the convergence rate. Through the Lyapunov theorem, the convergence of position and velocity cooperative tracking errors to zero in fast finite‐time is demonstrated. To showcase the effectiveness of the proposed control scheme, comparative simulation results are presented.

Non-singular terminal sliding mode control algorithm design based on extended state observer

Non-singular terminal sliding mode control algorithm design based on extended state observer

Extended State Observer Based Generalized Predictive Control for Aircraft at High Angle of Attack

Extended State Observer Based Generalized Predictive Control for Aircraft at High Angle of Attack

The effect of variations in experimental and computational fidelity on data assimilation approaches

AbstractWe conduct a comprehensive analysis of two data assimilation methods: the first utilizes the discrete adjoint approach with a correction applied to the production term of the turbulence transport equation, preserving the Boussinesq approximation. The second is a state observer method that implements a correction in the momentum equations alongside a turbulence model, both applied to fluid dynamics simulations. We investigate the impact of varying computational mesh resolutions and experimental data resolutions on the performance of these methods within the context of a periodic hill test case. Our findings reveal the distinct strengths and limitations of both methods, which successfully assimilate data to improve the accuracy of a RANS simulation. The performance of the variational model correction method is independent of input data and computational mesh resolutions. The state observer method, on the other hand, is sensitive to the resolution of the input data and CFD mesh.

Distributed event‐triggered fixed‐time formation tracking control for multi‐spacecraft systems based on adaptive immersion and invariance technique

AbstractIn this study, the problem of fixed‐time formation tracking for multi‐spacecraft systems without internal collisions was investigated. Aiming to ensure that the formation members can accurately realize and maintain the required configuration within the user‐given time, we designed a novel adaptive immersion and invariance (I&I)‐based control protocol. The novelty here lies in two aspects. First and foremost, this study was based on the adaptive I&I technique, combined with a new artificial potential function, to achieve the desired formation tracking without internal collision. Second, unlike the asymptotic convergence of the traditional I&I‐related works, to guarantee the fixed‐time stability, the proposed protocol introduced the prescribed performance control, which can also alleviate the possible system performance degradation caused by the non‐periodic control signal update of the event‐triggered mechanism. Further, the introduction of the event‐triggered mechanism can reduce the unnecessary information interaction. Lyapunov stability analysis shows that this proposed protocol can enable the defined implicit manifold to converge to the origin for the most initial conditions. Also, benefiting from the prescribed performance techniques, the convergence time can eliminate the dependence of the system on designed controller parameters or initial system conditions, relying only on the actual mission requirements. In addition, we adopted a linear extended state observer to deal with the parameter uncertainties and external disturbances, and used the I&I adaption to estimate the observer errors, thus further improving the system performance. Moreover, a new exponential‐type artificial potential function was designed to avoid close proximity between formation members and prevent internal collisions. Finally, numerical simulations were conducted to verify the theoretical results.

Improved model predictive control based on Luenberger state observer for LC‐coupling hybrid active power filter

AbstractAn improved model predictive control (MPC) with Luenberger state observer is proposed in this article for LC‐coupling hybrid active power filter (LC‐HAPF). Traditionally, the implementation of MPC for LC‐HAPF requires additional sensors to measure coupling capacitor voltage, thereby increases the system cost and reduces reliability. The existence of one‐step sampling delay in practice will also affect the final compensation performance. To relax these problems, both continuous and discrete models are deduced first. Then, the Luenberger observer is utilized based on the discrete model to mitigate the steady‐state error without additional sensors. In addition, the sampling delay compensation is provided by improving the prediction horizon. Finally, the effectiveness of the improved MPC for LC‐HAPF is verified by experiment results, indicating that the proposed method has fast dynamic response and low steady‐state error.

Adaptive fuzzy event-triggered control for a class of nonlinear time-delay multi-agent systems with dead zone and partial state constraints

This paper presents an adaptive fuzzy event-triggered control (ETC) method for a class of time-delay nonlinear multi-agent systems (MASs) with dead zone (DZ) and partial state constraints (PSCs). It should be pointed out that the states considered in this paper are unmeasurable and part of the system states are constrained by time-varying boundary. By utilizing fuzzy logic systems (FLSs) and backstepping design framework, a fuzzy state observer is constructed to estimate the unmeasured states, while the introduction of a time-varying barrier Lyapunov function (BLF) addresses the partial state constrained problem. Furthermore, during the design process of the state observer, compensation for the influence of the unknown DZ input on the system is achieved through utilization of known designed event-triggered input signal and adaptive parameter. Building upon this foundation, employing the Lyapunov stability theory and adaptive backstepping technique with ETC strategy, the developed distributed control mechanism demonstrates that all variables of the closed-loop system are bounded, the consensus error of the system can converge to a small region of origin and Zeno behavior can be ruled out. Finally, two simulation examples further illustrate the proposed control strategy and theorem.

Adaptive fuzzy controller design for an air handling unit

An adaptive control method based on a fuzzy state observer is designed for air handling unit (AHU) systems, where the intensity of humidity source and heat load are considered to be uncertain, and approximated by fuzzy logics. Besides, the supply air temperature is unmeasurable, which is observed by a state observer. To avoid the system equilibrium point offset, the prediction errors generated by the system and serial-parallel estimation models are introduced into the controller design based on backstepping. Finally, the superiority of proposed adaptive fuzzy controller is analyzed by simulation comparison with feedback linearization and PID controllers in two cases.

Pressure Space: The key subsurface commodity for CCS

Storage resource estimates are part of the foundation for CCS policy, project development and pipeline routing. Multiple generations of such estimates have found that hundreds and even thousands of gigatons of storage are available in basins around the world. However, these estimates have largely been based on basin-scale static capacity calculations that assume pore space is accessible to CO2, because basins have open boundaries that allow water to be displaced and avoid pressure build-up. However, as we now consider large-scale injection that stresses the system capacity, limitations to the flow of CO2 and displaced brine must be considered. These limits include pressure interactions among multiple projects, physical lateral discontinuities such as faults and facies changes, overpressure, juxtaposition with impermeable basement, and regulatory requirements that require protection of freshwater. We present here a simple algorithm to estimate the total pressure-limited storage resource. Applying it to the example of the Texas coastal Miocene results in a significantly lower storage resource over our previous static capacity estimates (assuming no water production). Based on this assessment, we find that CCS is still unlikely to be capacity-limited, but effective regulation, land valuation and project development will require recalibration and consideration of all projects in pressure communication. We conclude that depth-dependent and geomechanically-limited pressure space, not pore space, is the key subsurface commodity.

Neuroadaptive event-triggered tracking control for nonlinear systems with dynamic fault feedback and prescribed time convergence

This paper investigates the problem of event-triggered adaptive prescribed time tracking control for nonlinear systems with combining multiplicative and additive dynamic sensor fault. A simple state observer is designed by fusing fault output and reference signal to estimate unmeasurable states, where the unknown unmeasurable uncertain functions are approximated by neural network technology. Then, the prescribed time performance function is constructed based on the time scale function, and a suitable function transformation is introduced that the tracking error can reach the desired residual set in the prescribed time, where the initial value of the error can be arbitrarily selected regardless of the prescribed time performance function. Moreover, the desired accuracy and the prescribed time can be specified on request. The designed adaptive event-triggered controller can effectively compensate the sensor fault in the output feedback control and reduce the communication burden, and the feasibility of the proposed method is verified by the simulation result.

Robust internal model control based on a novel generalized extended state observer and its application on a two-inertia system

Disturbance observer (DOB) and extended state observer (ESO) are extensively utilized to handle external disturbances and model uncertainties in the control system. Nevertheless, the integration of these two methods to improve disturbance suppression remains an open question. In this research, the disturbance compensation mechanism of DOB is employed to compensate the disturbance estimation error of ESO, thereby achieving an effective integration of DOB and ESO. Additionally, a generalized ESO (GESO) is proposed to replace ESO. A robust internal mode control (RIMC) scheme is then developed by incorporating GESO into a two-degree-of-freedom internal mode control (TDF-IMC) framework. Moreover, the equivalence of RIMC and classical TDF-IMC is given by a rigorous derivation under the frequency domain description. Finally, the RIMC is applied to the control of a two-inertia system to verify its superiority in terms of robustness, disturbance rejection, and resonance suppression.

Fast Finite-Time Observer-Based Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems with Full-State Constraints

This article studies a class of uncertain nonlinear multiagent systems (MASs) with state restrictions. RBFNNs, or radial basis function neural networks, are utilized to estimate the uncertainty of the system. To approximate the unknown states and disturbances, the state observer and disturbance observer are proposed to resolve those issues. Moreover, a fast finite-time consensus control technique is suggested in order to accomplish fast finite-time stability without going against the full-state requirements. It is demonstrated that every signal could be stable and boundless, and an event-triggered controller is considered for the saving of resources. Ultimately, the simulated example demonstrates the validity of the developed approach.

Distributed coordinated speed control of flywheel energy storage matrix systems with model uncertainties and disturbances

SummaryThis paper studies a coordinated rotor speed control of flywheel energy storage matrix systems (FESMS) in the presence of model uncertainties and unknown disturbances. We consider the scenarios that the torque variation during the operation of flywheel energy storage system (FESS) cannot be accurately measured and the coordinated operation of FESMS is realized without the measurements of accurate rotor speeds. We design a distributed extended state observer (ESO) only using local rotor position measurements to estimate the rotor speeds and unknown disturbances. Based on the estimated states, a coordinated control strategy with the compensation of model uncertainties and unknown disturbances is proposed. The proposed control strategy has the advantage of speed‐free feature and active disturbance rejection. By using Lyapunov stability theory, sufficient conditions are given to ensure that the FESMS can achieve the reference tracking. The performance of the control strategy is verified by simulations.

Research on Control Strategy of PMSG-PWM Power Generation System with Tidal Energy

Aiming at the characteristics of machine-side output instability and the wide-range variation in the tidal energy PMSG-PWM power generation system, we propose a control scheme with a high anti-interference capability applied to the PWM rectifier. The outer voltage loop adopts sliding mode control (SMC) with the variable exponential convergence law based on expanded state observer (ESO). By compensating the perturbation observation value into the sliding mode controller in advance, it improves the robustness and response speed of the system and suppresses the direct current (DC)-side voltage jitter phenomenon. The current inner loop combines model prediction (MP) with direct power control (DPC). By introducing time-delay compensation, it improves the control accuracy, reduces the machine-side harmonic content, and enables the system to maintain unit power factor operation despite external disturbances. Simulation and experiment results show that, under the wide range of PMSG output, the PMSG-PWM power generation system adopting the “ESO_SMC+MDPDC” scheme has a fast dynamic regulation of DC output voltage, obvious vibration suppression effect, low harmonic content of the current on the PMSG side, and fast current tracking speed, which verify the feasibility of applying this system to the field of tidal energy generation.

Humidity and temperature nonlinear control based on almost disturbance decoupling and state observers for air-handling units

The almost disturbance decoupling problem for air-handling units (AHUs) containing unmeasurable states is addressed. Firstly, a state observer is introduced to estimate the supply air temperature, which is an unmeasurable state. Secondly, the almost disturbance decoupling technique is utilized to attenuate the influence of unknown disturbances including outdoor temperature, outdoor humidity ratio, heat load, and strength of the humidity source. Finally, compared with the linearization and PID control methods, simulation results verify the superiority and effectiveness of the proposed controller.