Strong Disturbances Research Articles

Robust Low-Rank Clustering Contrastive Learning Integrating Transformer for Noisy Industrial Soft Sensors

Strong process noise and disturbance caused by operating conditions and internal systems have brought a considerable challenge for soft sensor modeling in industrial processes. Existing modeling methods mainly focus on removing the noise from the process data, which do not improve the accuracy of the soft sensor model effectively for it is unrealistic to get completely noise-free data in actual industrial processes. Therefore, a novel robust Low-rank Clustering Contrastive Learning (LrCCL) integrating Transformer (LrCCL-T) is proposed in this paper. Based on the data augmentation technology, the LrCCL is designed to learn intrinsic and invariant feature representations from the process data by combining low-rank prior (Lr) and adaptive clustering contrastive learning (CCL). The CCL can bring closer the pairs from the same sample and cluster. Moreover, the Lr which assumes that samples in the same cluster should lie in a low-dimensional subspace is utilized to enhance the learned feature representations by adding a low-rank constraint. Then, the Transformer is used to build the soft sensor model, which can extract dynamic temporal relationship between the learned feature representations and outputs. Finally, to verify the effectiveness and robustness of the proposed method, a public industrial thermal power dataset and an actual industrial polypropylene dataset are utilized to build the steam volume (SV) and the melt index (MI) soft sensor model, respectively. The contrastive and ablation experiment results show that the proposed LrCCL-T can achieve comparable accuracy to other state-of-the-art soft sensor methods under strong noise industrial environment.

A Gain Scheduling Design Method of the Aero-Engine Fuel Servo Constant Pressure Valve with High Accuracy and Fast Response Ability

Constant pressure valve, which has an axially symmetric structure, is an essential component to supply the servo reference pressure for aero-engine hydraulic mechanical control systems, and its performance directly impacts the performance of the control system. This paper constructs a closed-loop disturbance rejection system of the constant pressure valve based on the linear incremental description method, in which the controlled object is the controlled pressure, and the stabilization controller is constructed by the closed-loop feedback motion valve. Meanwhile, the linear models of the closed-loop system are calculated. Subsequently, based on the bode frequency domain characteristic analysis, the accurate influences of the stabilization control gain on the dynamic performance and stability of the system are given. On this basis, a gain scheduling design method of the system is proposed, and the geometry design and implementation method of the inlet orifice is proposed to complete the design work. The simulation results show that under bad conditions, which include the 1 MPa strong step disturbance of the inlet pressure and the step disturbance of the variable outlet flow area, the steady-state working range of the controlled pressure is 1.5 ± 0.01 MPa, the steady-state error is not more than 0.7%, and the regulation time is not more than 0.006 s.

Statistical analysis of mechanical properties of biological soft tissue under quasi-static mechanical loading

The mechanical properties of biological soft tissues are inextricably linked to the field of health care, and their mechanical properties can be important indicators for diagnosing and detecting diseases; they can also be used to analyze the causes of organ diseases from a pathological point of view and thus guide the deployment of medical solutions. As an effective method to characterize the mechanical properties of materials, mechanical loading experiments have been successfully applied to the mechanical properties of materials, including tension, compression, pure shear, and so on. Under quasi-static loading, when the material is a biological soft tissue material between a solid and an ideal fluid, its viscoelastic properties strongly respond to the force stimulus, and the stress-strain-time in the elastic phase will have obvious disturbance characteristics. Therefore, the existing statistical methods are often difficult to quantitatively describe the mechanical properties of materials. Therefore, this study proposes an Interval Capture Point based on the principle of integration. The experimental data based on this method can characterize its nonlinear mechanical properties well, especially when the loading speed is extremely low and the soft materials show strong disturbance characteristics. The proposed method can still accurately characterize the hyperelastic and viscoelastic properties of the mechanical properties of biological soft tissues under quasi-static loading.

Assessment of permafrost disturbances caused by two parallel buried warm-oil pipelines: A case study at a high-latitude wetland site in Northeast China

Multiple studies demonstrate that narrow-linear strong disturbances triggered by pipeline engineering activities have resulted in rapid permafrost degradation. However, the extent, duration, and severity of permafrost disturbances induced by two parallel buried warm-oil pipelines remain unclear. Here, we examine the thermal disturbances of the China-Russia crude oil pipelines (CRCOPs I and II) on the surrounding permafrost. Ground temperature measurements on and off the right-of-way of the CRCOPs and an electrical resistivity tomography survey were conducted at a selected high-latitude wetland site in northeastern China. The observations showed that warm oil flow in pipelines dissipated heat to the surrounding soil, resulting in the thawing of underlying permafrost accompanied by the formation and development of thaw bulbs around the pipes. Currently, the thaw bulb of CRCOP-I was about four times as large as that of CRCOP-II, mainly due to the longer 7-year working duration of CRCOP-I. To quantify the permafrost disturbances around the pipeline, a conductive heat transfer model was established. A numerical simulation of the soil thermal regime around the pipeline suggested the initial growth of the thaw bulb was quite fast but gradually slowed with time, of which the shape was modified to ellipse from a semicircle. The existence of CRCOP-II would accelerate the warming of permafrost on the CRCOP-I right-of-way due to the small separation distance between them. We expect that the thaw bulbs of the two pipelines will expand larger than previously estimated due to the adverse effects of pipeline settlement and surface water flow, sparking a wider permafrost disturbance.

Automatic Current-Constrained Double Loop ADRC for Electro-Hydrostatic Actuator Based on Singular Perturbation Theory

For an electro-hydrostatic actuator (EHA), the position, speed, and current cascade three-loop control architecture are dominant in existing active disturbance rejection control (ADRC). However, this architecture suffers from many problems, such as severe noise sensitivity of the extended state observer (ESO), excessive complexity of control structure, and too many tuned parameters, which makes the controller not easy to implement in practice. Aiming at the above drawbacks, a novel cascade double-loop ADRC strategy that is automatic current-constrained is proposed, which makes the whole ADRC architecture simplified to the position and the integrated speed–current double-loop architecture. Firstly, for the position control loop, the singular perturbation theory is used to reasonably reduce the order of the model for the position subsystem of EHA. A reduced order ADRC controller (ROADRC) is synthesized, which not only effectively reduces the noise sensitivity of ESO, but also circumvents use of the actuation acceleration information in the controller design process. Secondly, the integrated speed–current ADRC controller is designed by taking the speed and current subsystems of EHA into synthesis, which avoids the problem of excessive current loop bandwidth in conventional three-loop control architecture, and the number of tuned parameters is significantly reduced. Additionally, an uncomplicated and effective automatic current-constrained ADRC controller (CACADRC) is designed to solve the problem in the integrated speed–current ADRC that the current cannot be automatically constrained. Finally, by comparing the three-loop PI controller with the traditional three-loop ADRC, a detailed simulation analysis is carried out to verify the effectiveness and merits of the proposed controller. The simulation results show that the proposed controller not only inherits the advantages of high precision and strong disturbance rejection performance of the conventional ADRC, but can also efficiently decrease the noise sensitivity of ESO and effectively achieve the current-constrained control.

Motion-inhibition control of a multi-robot mooring system using an actuating force fuzzy control method

The multi-robot mooring system (MRMS) composed of robots and a moored ship has characteristics of strong fluid-structure coupling, high nonlinear, complex disturbance, and difficulty in establishing models accurately. Thus, the conventional model-based control method is difficult to be implemented for motion-inhibition control. In the paper, the displacement gain coefficient and velocity gain coefficient of the local feedback PD control law are defined as the actuating restoring force (ARF) coefficient and the actuating damping force (ADF) coefficient, respectively, and a local feedback PD motion-inhibition control law is given. Then a mapping relationship from moored-ship motions to the ARF and ADF coefficients is developed using a maximum normalized deviation index and fuzzy reasoning logic, and an actuating force fuzzy control (AFFC) method is proposed. An optimization approach is proposed to solve the problem that too many fuzzy control parameters are not easy to adjust. An MRMS composed of a ship model (266000 m3 LNG ship of 1:60 scale) and a dual parallel elastic underactuated mooring robot is used to conduct experiments in terms of different motion-inhibition control methods. The results show that the proposed method can effectively inhibit the surge, sway, and yaw motions of the ship under different wave directions.

Influence of Pipeline Leakage on the Ground Settlement around the Tunnel during Shield Tunneling

Shield tunneling is widely used in urban subway tunnel construction. Old urban underground pipelines generally have small leakages that are difficult to find. The water leakage significantly reduces the stability of the stratum, posing a threat to the safety of tunnel shield construction. Therefore, this study established 2D and 3D calculation models for analyzing the law of the leakage diffusion in the ground under water pressure, and the influences of the pipeline leakage range and leakage length on the changes in ground settlement during shield tunneling. The 2D model calculation results show that seepage water mainly diffuses vertically under gravity. As the pipeline leakage gradually reaches a predetermined depth, the simulation results tend to be consistent with the test results. The 3D model is more accurate than the theoretical solution in predicting the ground settlement because it can consider the influences of repeated disturbances in twin tunnel shield construction. The maximum ground surface settlement increases with the extent of the leakage length and leakage range, and the range is the main factor determining the settlement. At the interior of the ground, the seepage water has a greater impact on areas with strong disturbances and large soil losses.

Detecting the January 15, 2022 Hunga Tonga-Hunga-Ha'apai volcanic eruption (SW Pacific) high up in the sky through “ionospheric resonance”

Summary We report a mode of ionospheric resonance induced by the January 15, 2022, Hunga Tonga-Hunga-Ha'apai volcanic eruption, captured globally through ground-based GNSS networks. In the near-field region, we observe a strong ionospheric disturbance in the total electron content, including contributions from acoustic waves and gravity waves. In contrast, propagation of gravity waves, seismic airwaves diffracted by topographic barriers, and/or atmospheric Lamb waves can be documented for far-field ionospheric disturbances. Specifically, the atmospheric wave propagation towards the Hawaii Islands involved three distinct modes of ionospheric perturbation through Rayleigh wave, gravity waves and atmospheric Lamb waves. Further, we also noticed that the peak-to-peak amplitude of the disturbance reached ∼ 8.7 per cent of the background electrons, which is significantly higher than the recent volcanic explosions in the Japanese Islands and the 2020 chemical explosion in Beirut. The ionospheric total electron content perturbations can provide important information about the volcanic source, hence they could be useful as a measure of eruption intensity and for real-time hazard monitoring.

Simulation of a Quadrotor under Linear Active Disturbance Rejection

The quadrotor aircraft has the characteristics of simple structure, high attitude maintenance performance and strong maneuverability, and is widely used in air surveillance, post−disaster search and rescue, target tracking and military industry. In this paper, a robust control scheme based on linear active disturbance rejection is proposed to solve the problem that the quadrotor is susceptible to various disturbances during the take−off process of non−horizontal planes and strong disturbances. Linear Active Disturbance Rejection Control (LADRC) is a product of a tracking differentiator (TD), a linear extended state observer (LESO) and an error feedback control law (PD) and is a control technique for estimating compensation for uncertainty. Radial Basis Function Neural Networks (RBFNN) is a well−performing forward network with best approximation, simple training, fast learning convergence and the ability to overcome local minima problems. Combined with the advantages and disadvantages of LADRC, Adaptive Control and Neural Network, the coupling force between each channel, gust crosswind disturbance and additional resistance of offshore platform jitter in the flight state of the quadrotor are optimized. In the control, the RBF neural network is designed, the nonlinear control signal is wirelessly approximated and the uncertain disturbance to the quadrotor is identified online. Finally, the real−time estimation and compensation are performed by LESO to realize the full−attitude take−off of the quadrotor. In addition, this paper uses adaptive control to optimize the parameters of LADRC to reduce the problem of many LADRC parameters and difficulty to integrate. Finally, the robust control system mentioned in this paper is simulated and verified, and the simulation results show that the control scheme has the advantages of simple parameter adjustment and stronger robustness.

A Scalable-Bandwidth Extended State Observer-Based Adaptive Sliding-Mode Control for the Dissolved Oxygen in a Wastewater Treatment Process

Strong nonlinearities, uncertainties, and disturbances present great challenges to the control of the dissolved oxygen (DO) in a wastewater treatment process (WWTP). To deal with those undesired issues, in this article, a scalable-bandwidth extended state observer (SESO) is proposed, and the SESO-based adaptive sliding-mode control (ASMC) is designed. By the SESO, the time-varying total disturbance can be estimated more accurately and compensated more effectively. For the disturbances that are not addressed completely, an ASMC is employed to suppress them. Due to the advantages of both SESO and ASMC, the DO can be regulated more desirably. The benchmark simulation model Number 1 is taken to verify the proposed SESO-based ASMC. Comparative simulation results highlight the advantages of the proposed approach.

Optimisation of Temperature Control Parameters Based on Plate Heat Exchanger

Plate heat exchanger temperature control has strong coupling and disturbance instability in the control process. To solve these problems, first, a decoupling controller based on state feedback was designed. The parameters are then optimised using a genetic algorithm to suppress external disturbances using an active disturbance rejection controller (ADRC). The trackability and system stability of the built extended state observer (ESO) are analysed. The stabilisation of the system under bounded input conditions is achieved by adjusting the non-linear state error feedback control law coefficients in the ADRC. The simulation results show that the genetic algorithm optimised parameter controller based on state feedback decoupling enables complete decoupling of the temperature control, and the ESO has good tracking performance with better immunity to disturbances.

Frequency Domain Design Method of the Aeroengine Fuel Servo Constant Pressure Difference Control System with High Performance

The constant pressure difference regulating mechanism is widely used in aeroengine fuel servo metering systems, and it almost decides the metering precision. However, the design theory and design method of the available constant pressure difference regulating mechanism are unclear, and it is difficult to follow the high stability, high accuracy, and high robustness requirements of the modern aeroengine fuel servo metering system. In this paper, the design theory of the constant pressure difference regulating mechanism is revealed, and it indicates that it consists of two basic control units: a state feedback stabilization controller to ensure the asymptotic stability and disturbance rejection performance; and a servo and feed-forward compensator to ensure the asymptotic tracking ability. In addition, based on the frequency domain analysis method, the decisive influences about the control gains of the two control units on the dynamic performance and stability are analyzed. On this basis, a frequency domain design method of the two core control gains is proposed to complete the design task of the closed-loop system. The simulation results show that, under the adverse conditions of 1 MPa strong step disturbance of the inlet pressure and 50 mm2 strong step disturbance of the variable inlet flow area, the steady-state working range of the controlled pressure difference meets 0.92 ± 0.01 MPa, the steady-state error is not more than 1%, the regulation time is not more than 0.01 s, the dynamic overshoot is not more than 10%, and the designed phase margin is more than 70°.

Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence

Quadrotor UAV is vulnerable to external interference, which affects search and rescue. In this paper, a fuzzy neural network dynamic inverse controller (FNN-DIC) is designed to eliminate the instability of the attitude angle caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the component model of atmospheric turbulence is obtained firstly based on the Dryden model, using Gaussian white noise as a random input signal and a designed shaping filter. Combined with the Newton-Euler equation, a nonlinear dynamic model for the quadrotor UAV with atmospheric disturbance is established. While the traditional nonlinear dynamic inverse cancels the nonlinearity of the controlled object, it relies on precise mathematical models. The fuzzy neural network can adaptively compensate for the inaccurate part of the model and the inverse error of the model caused by the external disturbance, and the stability of the control system is strictly proved by using the Lyapunov function. The experiments are carried out on the simulation platform, and the results show that the FNN method can ensure that the quadrotor UAV can still fly smoothly against strong disturbances, and that robustness of the system is significantly improved.

Wild goose chase: Geese flee high and far, and with aftereffects from New Year's fireworks

AbstractIn the present Anthropocene, wild animals are globally affected by human activity. Consumer fireworks during New Year (NY) are widely distributed in W‐Europe and cause strong disturbances that are known to incur stress responses in animals. We analyzed GPS tracks of 347 wild migratory geese of four species during eight NYs quantifying the effects of fireworks on individuals. We show that, in parallel with particulate matter increases, during the night of NY geese flew on average 5–16 km further and 40–150 m higher, and more often shifted to new roost sites than on previous nights. This was also true during the 2020–2021 fireworks ban, despite fireworks activity being reduced. Likely to compensate for extra flight costs, most geese moved less and increased their feeding activity in the following days. Our findings indicate negative effects of NY fireworks on wild birds beyond the previously demonstrated immediate response.

Rotating mirror servo system control based on modified sliding mode-active disturbance rejection controller

In order to improve the tracking accuracy and robustness of the rotating mirror servo system, a modified sliding mode-active disturbance rejection control (MSM-ADRC) strategy is proposed. Firstly, the structure and working principle of the rotating mirror servo system are analysed, and its mathematical model is established to prepare for the design of the controller. Then, a MSM-ADRC is proposed to reduce the influence of unknown disturbance and improve the tracking accuracy. Among them, the modified sliding mode extended state observation (MSM-ESO) is designed by replacing the traditional nonlinear function with the designed optimal control function, which enhances the observation accuracy of the system state quantity and total disturbance. Meanwhile, an improved approach law is proposed, and an improved sliding mode nonlinear error feedback control law (MSM-NLSEF) is designed based on this approach law, which improves the convergence speed and accuracy of the control law. In addition, the stability of the designed MSM-ESO and MSM-NLSEF is proved. Finally, the proposed control method is validated by simulation and experimental comparison with other state-of-the-art controllers. Results reveal that the proposed control method has satisfying tracking performance and strong disturbance rejection ability.

Simple method to modulate the scattered light field under strong disturbance.

In this Letter, we propose a simple and robust method that we have named an optimal accumulation algorithm (OAA) to modulate a scattered light field. Compared with the simulated annealing algorithm (SAA) and genetic algorithm (GA), the OAA is very robust, that is to say it has a strong anti-disturbance capability. In experiments, the scattered light field through ground glass and a polystyrene suspension was modulated, where the polystyrene suspension supported a dynamic random disturbance. It was found that, even if the suspension is too thick to see the ballistic light, the OAA can still modulate the scattered field effectively, while the SAA and GA completely failed. In addition, the OAA is so simple that only addition and comparison are needed, and it can achieve multi-target modulation.

Incremental control system design and flight tests of a micro-coaxial rotor UAV

This paper applies the incremental nonlinear dynamic inversion (INDI) method to the control system design of coaxial rotor UAVs. The aerodynamic uncertainties and anti-disturbances problems are solved in the control system design. The designed controller gives the UAV excellent flight performance and control robustness. The incremental gain method (IGM) is adopted for the delay problem of the state derivatives. This method has the advantages of less calculation load and simple parameter adjustment, which provides excellent convenience for applying INDI controllers to coaxial rotor UAVs. The principle of IGM is further investigated by the discrete-time stability analysis methods, and the parameter selection strategy of the IGM is provided. The advantages of the controller design method are verified by comparative flight tests. The experimental results show that the average trajectory tracking error of INDI is only 58.3% of that of NDI under the same wind speed. When the angular acceleration delay is less than 0.06 s, IGM can easily keep the system stable. In addition, INDI has better robustness under obvious model errors and strong input disturbances.

Experimental and theoretical investigation of roadway fracture induced by static-blast loading using acoustic emission

Underground metal mine is characterized by a large mining range involving complex spatial roadways layout and high mining intensity along with strong blast disturbances. Roadway destruction is easily triggered by blast-induced disturbances from different directions. In this study, the relationships between the fracture pattern of the roadway and static-blast loading were investigated by the means of theoretical analysis and experiment. The results showed that the macroscopic cracks around the roadway could be attributed to the combined action of the static loading and blast-induced disturbances. Under static loading, the stresses of the spandrel and wall corners were concentrated, as well as the AE events were clustered significantly. Blast-induced disturbances aggravated the damage to both the blast-facing side and high-stress areas, resulting in generations of large-scale AE events and deformation inside the rock. The differences in the spatial distribution of AE parameters indicated that the damage caused by static stress loading was stronger than that caused by blast-induced disturbances. To control the progressive fracture of rock surrounding the roadway caused by dynamic disturbances, it is essential to strengthen the support for the high-stress area and the blast-facing side respectively.

Design and full-link trajectory tracking control of underwater snake robot with vector thrusters under strong time-varying disturbances

In this paper, an underwater snake robot with vector thrusters and axis-intersect joints is designed. The dynamic model of the newly designed robot is established. A new decoupling control strategy is proposed for full-link trajectory tracking. The control strategy decouples the movements between the body and the links. The trajectory of the body (represented by the head link) is controlled by thrusters, and the rest links follow its trajectory by controlling the relative angles to the head link with servo motors on the joints. To eliminate the influence of strong time-varying external and internal disturbances, the control method based on sliding mode and a nonlinear disturbance observer with linear matrix inequality is proposed to realize the full-body trajectory tracking. The results show that the proposed method performs better than the reference under strong time-varying external and internal disturbances.

Collective dynamics and shattering of disturbed two-dimensional Lennard-Jones crystals.

Elucidating collective dynamics in crystalline systems is a common scientific question in multiple fields. In this work, by combination of high-precision numerical approach and analytical normal mode analysis, we systematically investigate the dynamical response of two-dimensional Lennard-Jones crystal as a purely classical mechanical system under random disturbance of varying strength, and reveal rich microscopic dynamics. Specifically, we observe highly symmetric velocity field composed of sharply divided coherent and disordered regions, and identify the order-disorder dynamical transition of the velocity field. Under stronger disturbance, we reveal the vacancy-driven shattering of the crystal. This featured disruption mode is fundamentally different from the dislocation-unbinding scenario in two-dimensional melting. We also examine the healing dynamics associated with vacancies of varying size. The results in this work advance our understanding about the formation of collective dynamics and crystal disruption, and may have implications in elucidating relevant non-equilibrium behaviors in a host of crystalline systems. Microscopic dynamics and underlying topological defects in the disruption of the Lennard-Jones lattice under random disturbance.