State Estimation Research Articles

Output feedback control of stochastic nonlinear systems with external disturbances and inverse dynamics

SummaryThis work presents an approach to control a type of stochastic cascade nonlinear systems, which involve external disturbances and nonlinear terms. The external disturbances under the consideration are not measurable and regarded as extended states. The proposed method addresses the problem of unmeasured states and external disturbances by introducing an extended state observer (ESO). Based on the above work, a new stochastic nonlinear system including ESO is established. To ensure the stability and boundedness of the system, an adaptive output feedback controller is designed by using stochastic integrated input‐to‐state stability and backstepping design technique. This controller guarantees that all the states remain almost surely bounded and globally asymptotically stable in probability. Simulation experiments are conducted to validate the effectiveness of the proposed control scheme.

Finite-time error constraint control for multi-AUV systems with unknown uncertainties based on observer and tan-type barrier Lyapunov function

PurposeAutonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation, nonlinear model uncertainties and external ocean current disturbances. The containment errors can be limited to a small neighborhood of zero in finite time by employing control strategy. The control strategy can keep errors within a certain range between the trajectory followed by AUVs and their intended targets. This can mitigate the issues of collisions and disruptions in communication which may arise from AUVs being in close proximity or excessively distant from each other.Design/methodology/approachThe tracking errors are constrained. Based on the directed communication topology, a cooperative formation control algorithm for multi-AUV systems with constrained errors is designed. By using the saturation function, state observers are designed to estimate the AUV’s velocity in six degrees of freedom. A new virtual control algorithm is designed through combining backstepping technique and the tan-type barrier Lyapunov function. Neural networks are used to estimate and compensate for the nonlinear model uncertainties and external ocean current disturbances. A neural network adaptive law is designed.FindingsThe containment errors can be limited to a small neighborhood of zero in finite time so that follower AUVs can arrive at the convex hull consisting of leader AUVs within finite time. The validity of the results is indicated by simulations.Originality/valueThe state observers are designed to approximate the speed of the AUV and improve the accuracy of the control method. The anti-saturation function and neural network adaptive law are designed to deal with input saturation and general disturbances, respectively. It can ensure the safety and reliability of the multiple AUV systems.

Finite-time fuzzy adaptive consensus control for state-constrained MIMO nonlinear MASs with switched topologies

In this article, the adaptive fuzzy finite-time output feedback consensus control problem is investigated for multiple input and multiple output (MIMO) nonlinear multi-agent systems (MASs) with switched topologies and asymmetric state constraints. Fuzzy logic systems (FLSs) are utilised to approximate uncertain nonlinear dynamics, and a distributed observer and a state observer are established to estimate the unknown leader and system states, respectively. By constructing the barrier Lyapunov functions (BLFs), a finite-time output feedback consensus control scheme is presented via backstepping control technique. It is proved that the controlled MASs are stable, and the consensus errors converge in finite time. Moreover, the system states will not exceed the given bounds. Finally, the proposed finite-time consensus control approach is applied to control multiple unmanned surface vehicles (USVs), the simulation results check the feasibility of the developed finite-time consensus control methodology.

Accurate trajectory tracking control for AUV under state constraints with a rapid stability dimensionality‐augmented state observer

AbstractA rapid stability dimensionality‐augmented state observer (RSDASO) based event‐driven control strategy is presented for the autonomous underwater vehicle (AUV) trajectory tracking issue, addressing state constraints, model uncertainty, limited communication resources and unknown external time‐varying disturbances. The first step is to develop a fast stability extended state observer to estimate the lumped disturbances and unmeasurable states of the system and ensure the estimation error converges in fixed time. Secondly, a fixed‐time AUV trajectory tracking control method is proposed to ensure that the tracking error of the system converges within a fixed time, based on the mentioned observer. Simultaneously, to reduce the communication resource usage by the system, an event‐triggered mechanism (ETM) is included in the control law. Lastly, simulation experiments verify the effectiveness of the process.

Innovative design and construction of a closure joint for inland-river immersed tunnels via dry-land construction methods: A case study of the Yuliangzhou tunnel in China

Closure joints constructed to fill the spaces between immersed tunnel elements or between the tunnel elements and adjacent cut-and-cover tunnels are crucial for the longitudinal stability of immersed tunnels and affect the overall cost and duration of tunnel construction. To avoid the obstruction of navigation and reduce the difficulty of constructing closure joints, dry-land construction methods have been widely applied to construct closure joints for inland-river immersed tunnels, in particular using procedures involving axial dry docks. However, the traditional dry-land construction method has many inherent drawbacks. For example, the construction of underwater large-scale reinforced concrete antiretreat structures involves many underwater works, complicated construction processes, long operation time spans and high costs. Based on the Yuliangzhou immersed tunnel in China, a new dry-land construction method for closure joints of inland-river immersed tunnels based on tunnel–soil interface friction was developed to address the abovementioned problems. Considering the adverse influences of back-silting sediment on tunnel–soil interface friction, large-scale laboratory and onsite shear tests were carried out to derive the interface friction coefficients between the tunnel element base slabs and prelaid pebble foundation beds. A composite concrete steel sandwich (CCSS) water-retaining system was designed and assembled to separate the water in the dry dock from the river course. A simplified analysis method based on numerical simulations for the determination of the equivalent horizontal thrust P applied to element ES caused by the dewatering of the axial dry dock was proposed. Based on horizontal antisliding stability analyses of the tunnel elements during the axial dry dock dewatering stage, equations for the key design parameters of the new dry-land construction method were established. Through examination of the static equilibrium of the tunnel elements in the tunnel longitudinal direction, temporary longitudinal displacement constraint (LDC) structures at the immersion joints were designed. Furthermore, the following key construction techniques for the new dry-land construction method were systematically designed: installation of a CCSS water-retaining system at the entrance of the axial dry dock, water sealing at contact gaps, installation of finish-rolled screw-thread (FRST) steel bars as the LDC structures at the immersion joints, and construction of rigid connections between tunnel element ES and the cut-and-cover tunnel. Finally, onsite observation of the deformation states of Gina gaskets and monitoring of the tensile forces of FRST steel bars at the immersion joints verified the successful implementation of the new dry-land construction method, supporting the use of these techniques in closure joint design and construction for inland-river immersed tunnels.

Research on Vehicle Stability Control Based on a Union Disturbance Observer and Improved Adaptive Unscented Kalman Filter

This paper considers external disturbances imposed on vehicle systems. Based on a vehicle dynamics model of the vehicle with three degrees of freedom (3-DOFs), a union disturbance observer (UDO) composed of a nonlinear disturbance observer (NDO) and an extended state observer (ESO) was designed to obtain external disturbances and unmodeled items. Meanwhile, an improved adaptive unscented Kalman filter (iAUKF) with anti-disturbance and anti-noise properties is proposed, based on the UDO and the unscented Kalman filter (UKF) method, to evaluate the sideslip angle of vehicle systems. Finally, a vehicle yaw stability controller was designed based on UDO and the global fast terminal sliding mode control (GFTSMC) method. The results of co-simulation demonstrated that the proposed UDO was effectively able to observe external disturbances and unmodeled items. The proposed iAUKF, which considers external disturbances, not only achieves adaptive updating and adjustment of filtering parameters under different sensor noise intensities but can also resist external disturbances, improving the estimation accuracy and robustness of the UKF. In the anti-disturbance performance test, the maximum estimation error of the sideslip angle of the iAUKF under the three working conditions was less than 0.1°, 0.02°, and 0.5°, respectively. Based on the UDO and the GFTSMC, a vehicle yaw stability controller is described, which improves the accuracy of control and the robustness of the vehicle’s stability control system and greatly strengthens the driving safety of the vehicle.

Observation of Floquet states and their dephasing in colloidal nanoplatelets driven by visible pulses

Observation of Floquet states and their dephasing in colloidal nanoplatelets driven by visible pulses

Pipe roughness calibration approach for water distribution network models using a nonlinear state observer

This paper introduces an online approach based on a nonlinear state observer (NSO) to calibrate the roughness of each pipe within a water distribution network (WDN) or a sector thereof. The NSO is designed to obtain the estimations of pipes' friction factors, which are then used to estimate the roughness. The core of the NSO is a dynamic WDN model formulated through a structured set of ordinary differential equations derived from fundamental physical principles and taking advantage of both graph theory and rigid water column theory. By applying a coordinate transformation, the WDN model is represented as a fully connected network of damped nonlinear oscillators, with each oscillator formulated as a Liénard system. This representation allows for estimating the friction factors for each pipe using only flow rate information. The proposed approach facilitates a continuous calibration when hydrodynamic data are readily accessible, which is a capability that empowers engineers to enhance, concurrently or proactively, the day-to-day operations of water distribution networks, such as control or diagnose tasks, whenever data are available. The results of numerical simulations are presented to illustrate the practical utility of the proposed method.

Prescribed-Time Trajectory Tracking Control for Unmanned Surface Vessels with Prescribed Performance Considering Marine Environmental Interferences and Unmodeled Dynamics

This article investigates a prescribed-time trajectory tracking control strategy for USVs considering marine environmental interferences and unmodeled dynamics. Firstly, a fixed-time extended state observer is introduced to quickly and accurately observe the compound perturbations including ocean disturbances and unmodeled dynamics. Subsequently, a prescribed-time prescribed performance function is utilized to obtain guaranteed transient performance within a predefined time. Finally, combining the fixed-time extended state observer, dynamic surface control technique, and prescribed-time prescribed performance control, a prescribed-time prescribed performance control strategy is developed to guarantee that the tracking errors converge to a predefined performance constraint boundary within a prescribed time. The effectiveness and superiority of the presented control strategy is verified by the simulation results.

Quality of life in older adults with mood states associated with bipolar disorder: A secondary analysis of the English longitudinal study of ageing data.

To investigate: (i) whether mood states associated with bipolar disorder are associated with poorer quality of life in older adults, and (ii) what are some of the predictors of quality of life in older adults with mood states associated with bipolar disorder. The authors completed a cross-sectional multilevel analysis of panel data from seven waves of The English Longitudinal Study of Ageing dataset. The main analysis included 567 participants who reported experiencing mood states associated with bipolar disorder. Some participants reported this in more than one wave, resulting in 835 observations of mood states associated with bipolar disorder across the seven waves. Quality of life was assessed using the Control, Autonomy, Self-realization, and Pleasure-19 (CASP-19) measure. The presence of mood states associated with bipolar disorder was significantly associated with poorer quality of life, even after controlling for multiple covariates (age, sex, social isolation, loneliness, alcohol use, education level, and economic status). Loneliness significantly predicted poorer quality of life in older adults with mood states associated with bipolar disorder. In contrast, higher educational attainment and being female predicted better quality of life in this group. Older adults with mood states associated with bipolar disorder have potentially worse quality of life compared to the general population, which may be partly driven by loneliness. This has ramifications for the support offered to this population and suggests that treatments should focus on reducing loneliness to improve outcomes.

A novel joint estimation for core temperature and state of charge of lithium-ion battery based on classification approach and convolutional neural network

The core temperature (CT) of lithium-ion batteries (LIBs) is crucial for effective thermal management, and is significantly influenced by the state of charge (SOC) among other battery parameters. However, directly measuring CT and SOC poses challenges. This study introduces a novel joint estimation method for CT and SOC, in which classification approach is pioneeringly employed through a two-dimensional convolutional neural network (2D-CNN). SOC is initially estimated and subsequently utilized as an input to refine CT estimation. This process is facilitated by two 2D-CNNs that incorporate measured indices such as current, terminal voltage, surface temperature, and ambient temperature into their inputs. Techniques including data augmentation, sequential optimization, and Gaussian filtering are employed to enhance estimation effect. The methodology is validated using LIB charge/discharge data derived from experiments based on the urban dynamometer driving schedule (UDDS). Results demonstrate that the root-mean-square errors (RMSEs) for CT and SOC estimation are below 0.267 °C and 0.7 %, respectively, across a broad ambient temperature range of −15 °C–55 °C. Consequently, this study confirms the effectiveness of using classification for CT and SOC estimation, illustrating that the proposed method can precisely estimate CT and SOC of LIBs across a wide temperature spectrum. The effectiveness of the deep learning method based on classification in estimating CT and SOC has been validated. Furthermore, a comparative analysis reveals that incorporating SOC as an input for CT estimation notably reduces the training time required by the method.

Adaptive sliding mode control with disturbance estimation for hydraulic actuator systems and application to rock drilling jumbo

For achieving high-performance control of hydraulic actuator systems, an adaptive sliding mode control with disturbance estimation algorithm is proposed and successfully applied to the hydraulic actuator systems of rock drilling jumbo. A switching extended state observer for hydraulic actuator systems is proposed, which combines the advantages of the linear extended state observer and the nonlinear extended state observer to estimate system disturbances more efficiently. The designed parameter adaptive law provides adaptivity to the system parameters, while the disturbance estimation algorithm can online estimate the unknown disturbances, such integration can enhance the adaptability and robustness of the sliding mode control algorithm. Rigorous simulation tests and practical application experiments are conducted to evaluate the performance of the proposed controller. The reliability of the designed parameter adaptive law and switching extended state observer is validated in detail in simulation studies. In the application experiments of rock drill jumbo, the results indicate the proposed controller is superior to sliding mode control with disturbance estimation and PID control. The average error of the developed controller is reduced by 58 %, 54 %, and 56 % compared to the sliding mode control with disturbance estimation controller, and 82 %, 78 %, and 79 % compared to the PID controller in tracking the low-frequency, high-frequency, and superimposed sinusoidal signals, respectively. Moreover, both the convergence of the uncertain parameters and the estimation of the unknown disturbances in the experiments are satisfactory. These experimental results adequately demonstrate the practical application value of the proposed controller.

Motion/force coordinated trajectory tracking control of nonholonomic wheeled mobile robot via LMPC-AISMC strategy

Nonholonomic constrained wheeled mobile robot (WMR) trajectory tracking requires the enhancement of the ground adaptation capability of the WMR while ensuring its attitude tracking accuracy, a novel dual closed-loop control structure is developed to implement this motion/force coordinated control objective in this paper. Firstly, the outer-loop motion controller is presented using Laguerre functions modified model predictive control (LMPC). Optimised solution condition is introduced to reduce the number of LMPC solutions. Secondly, an inner-loop force controller based on adaptive integral sliding mode control (AISMC) is constructed to ensure the desired velocity tracking and output driving torques by combining second-order nonlinear extended state observer (ESO) with the estimation of dynamic uncertainties and external disturbances during WMR travelling process. Then, Lyapunov stability theory is utilised to guarantee the consistent final boundedness of the designed controller. Finally, the system is numerically simulated and practically verified. The results show that the double-closed-loop control strategy devised in this paper has better control performance in terms of complex trajectory tracking accuracy, system resistance to strong interference and computational timeliness, and is able to realise effective coordinated control of WMR motion/force.

Justifying and Implementing Concept of Object-Oriented Observers of Thermal State of Rolling Mill Motors

Implementing the IIoT concept in industry involves the development and implementation of online systems monitoring the technical state of electromechanical equipment. This is achieved through the use of digital twins and digital shadows (object state observers). The tasks of mastering new rolling profiles and optimizing plate mill rolling programs require improved methods for calculating equivalent motor currents and torques. Known methods are generally based on calculations using smoothed load diagrams, which are assumed to be identical for the upper and lower main drive (UMD and LMD) rolls. These methods do not consider the differences in actual loads (currents or torques) in steady rolling states. Experiments performed on the 5000 plate mill have shown that due to speed mismatches, the UMD and LMD torques differ three times or more. This causes overheating of the more heavily loaded motor, insulation life reduction, and premature failure. Therefore, the problem of developing and implementing techniques for monitoring the load and thermal regimes of motors using digital observers is relevant. The paper’s contribution is the first justification of the concept of object-oriented digital shadows. They are developed for specific classes of industrial units using open-source software. This research justifies a methodology for assessing motor load and temperature by processing arrays of motor currents or torques generated during rolling. An equivalent load observer and a temperature observer were proposed and implemented using Matlab-Simulink resources. The algorithm was implemented on the mill 5000 and tuned using an earlier-developed virtual commissioning methodology with digital twins. Thermal regimes were studied, proving that torque alignment ensures equal motor temperatures. The proposed considerations contribute to the development of the theory and practice for creating digital systems to monitor the technical condition of electromechanical and mechatronic systems and implementing the Industry 4.0 concept at industrial enterprises.

Backstepping control of hypersonic vehicles under input and output constraints with model uncertainties and disturbances

In this paper, considering the physical restriction of hypersonic vehicle systems in a practical flight environment, the altitude tracking problem is studied with input magnitude, input rate, output constraints, system parameter uncertainties and disturbances, which expands the traditional considerations of control methods in the hypersonic vehicle field. The hyperbolic tangent function is employed to address the system input constraints. Furthermore, the incorporation of barrier Lyapunov function serves to ensure that the system output is limited in the prescribed limitations. In particular, two extended state observers are integrated to eliminate errors from model uncertainties and disturbances. Based on the effective combination of these techniques and auxiliary variable designs, a novel backstepping controller is proposed to simultaneously handle problems of input and output constraints, model uncertainties and disturbances. The closed-loop system stability is demonstrated using the Lyapunov theory. Simulation results show the effectiveness and superiority of the proposed controller compared with the traditional backstepping controller.

Bosanac v Federal Commissioner of Taxation: The Future of the Presumptions of Resulting Trust and Advancement

This case note examines the decision of the High Court of Australia in Bosanac v Federal Commissioner of Taxation. Part II provides a case summary. Part III considers the future of the presumptions of resulting trust and advancement following Bosanac. Part IV discusses the judicial references in Bosanac to the presumptions being ‘weak’, and analyses whether these were an observation of the current state of the law or represent a change to it. Part V reviews the Court’s clarification of an earlier case concerning the application of the presumption of resulting trust to married couples, Trustees of the Property of Cummins (a bankrupt) v Cummins. The case note concludes that Bosanac is significant because it has paved the way for the future development of the presumptions, developed the law by weakening the presumptions of resulting trust and advancement, and helpfully clarified the effect of Cummins.

Servo Control of a Current-Controlled Attractive-Force-Type Magnetic Levitation System Using Fractional-Order LQR Control

Recent research on fractional-order control laws has introduced the fractional calculus concept into the field of control engineering. As described herein, we apply fractional-order linear quadratic regulator (LQR) control to a current-controlled attractive-force-type magnetic levitation system, which is a strongly nonlinear and unstable system, to investigate its control performance through experimentation. First, to design the controller, a current-controlled attractive-force-type magnetic levitation system expressed as an integer-order system is extended to a fractional-order system expressed using fractional-order derivatives. Then, target value tracking control of a levitated object is achieved by adding states, described by the integrals of the deviation between the output and the target value, to the extended system. Next, a fractional-order LQR controller is designed for the extended system. For state-feedback control, such as fractional-order servo LQR control, which requires the information of all states, a fractional-order state observer is configured to estimate fractional-order states. Simulation results demonstrate that fractional-order servo LQR control can achieve equilibrium point stabilization and enable target value tracking. Finally, to verify the fractional-order servo LQR control effectiveness, experiments using the designed fractional-order servo LQR control law are conducted with comparison to a conventional integer-order servo LQR control.

Robust anti-disturbance interval type-2 fuzzy control for interconnected nonlinear PDE systems via conjunct observer

This paper investigates a robust anti-disturbance interval type-2 (IT2) fuzzy control for interconnected nonlinear partial differential equation (PDE) systems subject to parameter uncertainties by the conjunct observer. First, an IT2 fuzzy model is adopted to remodel the target system. Second, a state observer with mismatched premise variables is constructed to solve the problem that the original system and the observer do not share a uniform premise variable. Moreover, a disturbance observer is designed to estimate the unknown external disturbances, which can be modeled by exogenous PDE systems. Then, utilizing the conjunct observation information, an anti-disturbance IT2 fuzzy control strategy is proposed to attenuate the effect of disturbances on the system performance while ensuring that the closed-loop system is stable. Finally, simulation results verify the effectiveness of the proposed method.

Fixed-time fault-tolerant attitude tracking control for UAV based on fixed-time extended state observer

PurposeTo improve the robustness of carrier-based unmanned aerial vehicle (UAV) with actuator faults attitude tracking control system, this paper aims to propose a fixed-time backstepping (FXTBSC) fault-tolerant control based on a fixed-time extended state observer.Design/methodology/approachA fixed-time extended state observer (FXTESO) is designed to estimate the total disturbance including nonlinear, coupling, actuator faults and external disturbances. The integration of backstepping control and fixed-time technology ensures fixed-time convergence.FindingsThe simulation results of tracking the desired attitude angle show that the anti-interference, fault tolerance and tracking accuracy of FXTBSC-FXTESO are better than the BSC-ESO control method.Originality/valueDifferent from the traditional BSC-ESO, the convergence speed and convergence accuracy of FXTBSC-FXTESO proposed in this paper are better than conventional extended state observer. And the fixed time controller has the advantages of high tracking accuracy, fault tolerance and anti-interference ability.

Prescribed-time and output feedback stabilization of heat equation with an intermediate-point heat source and boundary control

This paper addresses the problem of prescribed-time stabilization for the heat equation with an interior point heat source under output feedback. The study employs a two-step backstepping approach along with time-varying feedback techniques. A prescribed-time state observer and an observer-based boundary control law are developed. The proposed method extends the applicability of the prescribed time-stabilizing algorithm to heat equations with non-strict feedback terms. Numerical simulations validate its effectiveness.