Dynamic Disturbances Research Articles

A new design of predictive plus PID control for second order plus time delay systems

AbstractThis paper proposes two novel predictive proportional‐integral‐derivative (PID) controllers for second‐order non‐self‐balance systems and self‐balance systems with time delays. For second‐order non‐self‐balance systems with time delays, traditional predictive PID controllers suffer from the drawback of failing to return to the setpoint after disturbances. Therefore, this paper introduces a novel double predictive PID controller, termed PPI‐PPD controller, which consists of an inner‐loop predictive PD controller and an outer‐loop predictive PI controller. In second‐order self‐balance systems encountered in practical chemical processes, time delays can lead to longer adjustment times, increased overshoot, and divergence issues. In order to solve these problems, an improved predictive PID (PPID) controller is proposed in this paper, which introduces a compensation link and an anti‐interference link in the traditional predictive PID controller. This enhancement improves the dynamic response and disturbance resistance of the control system. Simulation results demonstrate that both novel predictive PID controllers exhibit excellent control performance and robustness.

Optimizing energy efficiency, thermal comfort, and indoor air quality in HVAC systems using a robust DRL algorithm

This study presents a novel deep reinforcement learning (DRL) framework designed to optimize energy efficiency, thermal comfort, and indoor air quality, particularly focusing on CO2 levels, in Heating, Ventilation, and Air Conditioning (HVAC) systems. Existing DRL methods often face challenges in maintaining control effectiveness under environmental disturbances, leading to higher energy consumption and reduced system performance. To address these limitations, we propose the Decoupled Adversarial Long Short-Term Memory and Proximal Policy Optimization (DAL-PPO) algorithm, which integrates a Decoupled Adversarial Strategy (DAP) with Long Short-Term Memory networks (LSTM) to better handle temporal dynamics and disturbances. Using the EnergyPlus simulation tool and PyTorch, DAL-PPO was evaluated in a disturbed experimental setting, achieving a 15 % reduction in PMV and CO2 levels and an 8 % decrease in energy consumption compared to traditional reinforcement learning algorithms. These results highlight DAL-PPO's ability to maintain system stability and efficiency even under dynamic disturbances, offering a significant improvement in HVAC system control and contributing to the development of more energy-efficient and resilient buildings.

Experimental demonstration of the “unipolar cell” dynamics in a large laboratory magnetoplasma

The nonambipolar or “unipolar” particle transport accompanied by excitation of a system of eddy (short-circuit) currents can ensure the fast dynamics of small-scale magnetoplasma disturbances arising under pulsed localized rf heating, and evolving in electron magnetohydrodynamics regime of parameters. In this regime, redistribution of plasma density is possible, which is an order of magnitude faster than the classical mechanism of the ambipolar transport with the joint movement of electron-ion pairs. During the evolution of thermal plasma irregularity in the unipolar transport regime, magnetized electrons leave the heated plasma area along the magnetic field, while nonmagnetized ions drift predominantly across the field. The electric current arising in this case can be closed through the background plasma surrounding the irregularity. This regime can determine the times of development and decay of narrow field-aligned plasma density irregularities that arise, e.g., in the pulsed ionospheric heating experiments. The refined laboratory experiments with specially selected parameters, which were carried out in a large-scale Krot plasma device with localized (pointlike) short-pulse rf heating of electrons, demonstrated clearly the unipolar-cell dynamics. The “unipolar cell” is understood as a self-consistent, freely relaxing plasma-field structure, which is formed by the initial field-aligned plasma density depletion in a heated flux tube, the peripheral background plasma density enhancements and depletions, and a quadrupole system of electric eddy currents.

Fatigue fracture behaviors and damage evolution of coal samples treated with drying–wetting cycles investigated by acoustic emission and nuclear magnetic resonance

Constructing pumped-storage power stations using underground reservoirs in mines offers a promising method for large-scale energy storage. Watertight coal pillars have the potential to destabilize under the mine-shock cyclic dynamic loading and the drying–wetting cycles (DWCs). Understanding the fatigue damage mechanism and failure precursors in watertight coal pillars under cyclic dynamic loading disturbances in overburdened rock strata has become challenging. This study investigated the fatigue fracture behavior and precursor information of coal samples under acoustic emission (AE) monitoring over 1–7 DWC times. We analyzed the effects of DWC and fatigue cycles on the dynamic parameters and AE response, investigated crack spatial extension behaviors and the tensile-shear cracking evolution law, and analyzed the fatigue damage evolution law and failure precursor with energy and b-value. The results demonstrated that fatigue loading produced a strengthening effect on the DWC coal samples, and DWC promoted plastic softening damage to the specimens and increased the percentage of the elastic phase. The average dynamic fatigue strength and life of the specimens decreased exponentially under 7 DWC times. The average dynamic axial stiffness decreased by 15.67 %, the axial deformation increased by 6.1 × 10−4 in a single cycle, and the dynamic elasticity modulus of the fatigue damage instant decreased by 8.86 %. The greater the number of DWC, the smaller the b-value and the larger the fluctuation amplitude at fatigue failure of the specimen. A large short-term increase or decrease in the b-value can be regarded as a precursor to fatigue failure. This study provides a reference for the stability monitoring and forewarning of underground pumped-storage facilities.

Deformation failure mechanism and stability-control technology of deep layered clastic-rock roadway under dynamic disturbance

The deep layered clastic-rock roadways (LCRRs) of the gold mines in southwestern Guizhou, China, are adversely affected by dynamic disturbances such as blasting and mechanical operations, yielding poor roadway stability and unsatisfactory control effectiveness. This study investigates the deformation failure mechanism of a deep LCRR under dynamic disturbance and proposes and validates an optimised roadway stability-control scheme. Through on-site investigation and theoretical analysis, the main roadway stability-control factors are determined; that is, the mudstone-layer thickness, roadway buried depth, and dynamic-load amplitude. Similar simulation experiments reveal the deformation failure characteristics and strain-field evolution laws of similar models. Numerical analysis shows that increasing buried depth most severely affects the two sides of the roadway, whereas the dynamic-load amplitude determines the disturbance duration. Moreover, with increasing mudstone-layer thickness, the overall impact of the dynamic disturbance on the surrounding rock first intensifies and then diminishes. The results of the similar simulation experiment and numerical analyses are highly consistent, indicating a danger zone on the roadway roof. The roadway deformation and failure mechanisms are revealed, and a more rational technical solution for roadway stability control is proposed and implemented on-site. Analysis and monitoring results reveal a relative reduction in roadway surface displacement exceeding 30 %, and improvement of the overall roadway stability. The findings constitute a valuable reference and guide for roadway stability control under such geological conditions.

Characteristic stress response law and fracture precursor of granite under different dynamic disturbance damage conditions

Characteristic stress response law and fracture precursor of granite under different dynamic disturbance damage conditions

Finite-Time Control for Automatic Berthing of Pod-Driven Unmanned Surface Vessel with an Event-Triggering Mechanism

Coastal water accidents have occurred frequently in recent years, and human factors are still the main cause of these accidents. The purpose of this study is to provide a better and safer solution for the symmetry problem of unmanned surface vessels during automatic berthing in coastal waters. In automatic berthing, the symmetry problem refers to whether the USVs can maintain a stable state during motion and positioning, including dynamic symmetry and environmental symmetry. A finite-time controller based on a global nonsingular terminal sliding mode is designed to improve response speed and state consistency. Dynamic uncertainty and disturbance are considered in the design process, which can optimize the control law and effectively ensure the symmetry of the vessel in different states. Then, an event-triggering mechanism based on a dynamic threshold is adopted. In practice, there is excessive operation of the actuator. This mechanism ensures that the actuator is triggered only when the threshold is reached. USVs can adaptively adjust control strategies based on the real-time status, thereby improving symmetry during berthing. In simulation analysis, a pod-driven unmanned surface vessel with good maneuverability is taken as the research object. The results indicate that this control strategy can ensure rapid and consistent response of the vessel when subjected to external disturbances, which helps to maintain the symmetry of the automatic berthing motion under different conditions.

Vegetation disturbance and regrowth dynamics in shifting cultivation landscapes

Shifting cultivation, an age-old agricultural practice, is a major factor in forest cover change across Southeast Asia, where repeated cycles of vegetation disturbance and regrowth lead to far-reaching environmental and socio-economic impacts. The present study aims to assess the spatio-temporal patterns of vegetation disturbance and regrowth caused by shifting cultivation in Tripura state of India, over the past three decades, utilizing temporal segmentation of time-series Landsat data. The study analyzed vegetation disturbance and regrowth patterns in a shifting cultivation landscape from 1991 to 2020 using normalized burn ratio trends through LandTrendr, validated by the TimeSync tool. Six land use and land cover classes, viz., forests and trees outside forests, rubber plantation, shifting cultivation, water bodies, agriculture, and settlements, were mapped with an accuracy of 83.08% using a random forest classifier. This classification enabled the identification of the effective study area, which included forest areas with shifting cultivation patches. The analysis revealed that 2533.96 km2 of the study area remained undisturbed, 568.43 km2 experienced low-magnitude disturbance, 1501.11 km2 were moderately disturbed, and 184.82 km2 were highly disturbed. The shifting cultivation cycles in the study area show considerable variation. Low-magnitude disturbance indicates a single slash-and-burn event in the past three decades, moderate-magnitude disturbance involves fallow periods of over 10 years, and high-magnitude disturbance occurs with fallow periods of less than 8 years. The study revealed a shift from traditional shifting cultivation to more permanent agricultural practices in parts of Tripura. In response to incentives for commercial crops, cultivators are increasingly adopting long-term cultivation, including the growing of pineapple, areca nut, and rubber, as well as intercropping with papaya, banana, lemon, tapioca, pepper, and ginger. These plots are, however, abandoned if the yields become economically unviable. The expansion of monoculture cultivation significantly reduces the available area for shifting cultivation, thereby compelling jhum cultivators to revisit their jhum patches more frequently. This study is a first-of-its-kind attempt in the Indian context and sheds light on changing patterns in an age-old agricultural practice.

Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627

Abstract. New (a)biotic conditions resulting from climate change are expected to change disturbance dynamics, such as windthrow, forest fires, droughts, and insect outbreaks, and their interactions. These unprecedented natural disturbance dynamics might alter the capability of forest ecosystems to buffer atmospheric CO2 increases, potentially leading forests to transform from sinks into sources of CO2. This study aims to enhance the ORCHIDEE land surface model to study the impacts of climate change on the dynamics of the bark beetle, Ips typographus, and subsequent effects on forest functioning. The Ips typographus outbreak model is inspired by previous work from Temperli et al. (2013) for the LandClim landscape model. The new implementation of this model in ORCHIDEE r8627 accounts for key differences between ORCHIDEE and LandClim: (1) the coarser spatial resolution of ORCHIDEE; (2) the higher temporal resolution of ORCHIDEE; and (3) the pre-existing process representation of windthrow, drought, and forest structure in ORCHIDEE. Simulation experiments demonstrated the capability of ORCHIDEE to simulate a variety of post-disturbance forest dynamics observed in empirical studies. Through an array of simulation experiments across various climatic conditions and windthrow intensities, the model was tested for its sensitivity to climate, initial disturbance, and selected parameter values. The results of these tests indicated that with a single set of parameters, ORCHIDEE outputs spanned the range of observed dynamics. Additional tests highlighted the substantial impact of incorporating Ips typographus outbreaks on carbon dynamics. Notably, the study revealed that modeling abrupt mortality events as opposed to a continuous mortality framework provides new insights into the short-term carbon sequestration potential of forests under disturbance regimes by showing that the continuous mortality framework tends to overestimate the carbon sink capacity of forests in the 20- to 50-year range in ecosystems under high disturbance pressure compared to scenarios with abrupt mortality events. This model enhancement underscores the critical need to include disturbance dynamics in land surface models to refine predictions of forest carbon dynamics in a changing climate.

A Finite-Time Disturbance Observer for Tracking Control of Nonlinear Systems Subject to Model Uncertainties and Disturbances

In this study, a finite-time disturbance observer (FTDOB) with a new structure is originally put forward for the motion tracking problem of a class of nonlinear systems subject to model uncertainties and exogenous disturbances. Compared to existing disturbance estimator designs in the literature, in which the estimation error only converges to the origin asymptotically under assumptions that the first and/or second derivatives are vanishing, the suggested DOB is able to estimate the disturbance exactly in finite time. Firstly, uncertainties (parametric and unstructured uncertainties), unknown dynamics, and external disturbances in system dynamics are lumped into a generalized disturbance term that is subsequently estimated by the proposed DOB. Based on this, a DOB-based backstepping controller is synthesized to ensure high-accuracy tracking performance under various working conditions. The stability analysis of not only the DOB but also the overall closed-loop system is theoretically confirmed by the Lyapunov stability theory. Finally, the advantages of the proposed FTDOB and the FTDOB-based controller over other DOBs and existing DOB-based controllers are explicitly simultaneously demonstrated by a series of numerical simulations on a second-order mechanical system and comparative experiments on an actual DC motor system.

Enhancement of AVR system performance by using hybrid harmony search and dwarf mongoose optimization algorithms

Innovations in control algorithms, integration of smart grid technologies, and advancements in materials and manufacturing techniques all push the boundaries of AVR performance. As the demand for power systems progresses with the complexity and variety of loads, conventional AVR designs may struggle to handle these ever-changing circumstances efficiently. Therefore, the need for new optimization methods is crucial to bolstering the efficiency, reliability, and adaptability of AVRs. Thus, this work aims to improve the performance of the AVR system controller by using a novel hybrid technique between the Harmony Search (HS) and Dwarf Mongoose Optimization (DMO) algorithms to tune the proportional-integral-derivative (PID) and proportional-integral-derivative acceleration (PIDA) parameters. The suggested hybrid approach ensures an accurate solution with balanced exploration and exploitation rates. The reliability of the proposed HS-DMOA is verified through comparison with different optimization techniques carried out on time and frequency performance indicators, disturbances in the form of changes to time constants, and dynamic input signals. The proposed hybrid HS-DMOA PID-based has better overshoot than PID-based HS, LUS, TLBO, SMA, RSA, and L-RSAM by 20.37%, 18.5%, 18.5%, 2.77%, 5.55%, and 2.77%, respectively. Regarding the phase margin, the proposed hybrid HS-DMOA PID-based is better than PID-based HS, LUS, and TLBO by 39%, 37%, and 38%, respectively. While the proposed hybrid HS-DMOA PIDA-based has a better overshoot than PIDA-based HS, LUS, and PID HS-DMOA-based by 14%, 17%, and 20%, respectively. Moreover, the robustness under dynamic disturbance proved the reliability of the proposed HS-DMOA PID and PIDA based through enhancement of overshoot around 0.3%~20% for different cases. Finally, the main contribution of the paper is to propose a relatively new hybrid optimization method to enhance the AVR PID and PIDA-based performance with detailed analysis in time and frequency domains under normal and dynamic disturbances.

Ground motion characteristics induced by high-magnitude events with different source mechanisms of longwall mining

Rockbursts have become one of the most serious hazards in underground mines worldwide. While the characteristics of ground motions before rockbursts (or high-magnitude events (HMEs)) have not been studied. In this study, the peak ground velocity (PGV) and cumulative absolute displacement (CAD) before HMEs were examined based on seismic monitoring in a coal mine. It’s found that the source mechanisms vary significantly across different zones of the longwall, attributed to the low correlation between rock fracture types, stress levels, and seismic intensity. This correlation is mainly related to the distribution of primary fractures within the rock mass. The non-overlap of CAD peak with HME and the induction of delayed rockbursts are mainly caused by the unavoidable creep and additional energy input into the coal mass under disturbances before instability. The energy conversion process of the entire system is determined to be controlled by the stiffness ratio between the roof-floor system and the loaded coal, in accordance with the concept of dynamic and static load superposition. A high static load, strong dynamic disturbances, and a low rigidity ratio between surrounding rock and coal are identified as the most hazardous factors.

Adaptive Sliding Mode Control for AUV based on Backstepping and Neural Networks

Abstract Automatic Underwater Vehicle (AUV) inevitably suffers from various interference issues in the marine environment. Due to the limitations of underwater measurement methods and tools, as well as the complexity of AUV's control parameters in the underwater environment, dynamic measurement errors are easily cascaded and amplified, leading to the failure of the control system. In response to this phenomenon, this paper focuses on overcoming the influence of internal and external unknown factors in the tracking and control process of AUV trajectories. The internal factors are mainly the uncertainties generated by the model mismatch problem, and the external factors are mainly from the dynamic ocean currents. The AUV disturbances mainly affect the kinematics and dynamics levels directly or indirectly. In order to achieve the control of internal and external dynamic disturbances, we have designed a control system that employs backstepping (BS) and a sliding mode controller (SMC) with RBF neural networks to achieve the cascaded control of kinematics and dynamics. Comparison of multiple sets of simulations shows that our proposed algorithm has excellent anti-disturbance performance for dynamic conditions with low measurement accuracy.

Analysis of shear creep damage model of slope rock mass under the influence of coupled damage effects (DBSM)

Abstract This article reveals the evolution law of shear creep damage of carbonaceous shale (weak interlayer of slope) under dynamic load from a mechanical perspective by combining indoor experiments and theoretical research. Firstly, a coupled damage variable D BSM was established for the initial damage D 0 and dynamic disturbance shear creep damage D BS of rock mass based on the theory of damage mechanics. Secondly, according to the fractional calculus operator theory and considering the influence of coupled damage variable D BSM on the viscosity coefficient of rock mass in the viscoelasticity and viscoplasticity creep stages, a shear creep damage model of rock mass was established. At the same time, combined with the shear creep test data under the influence of dynamic loads, the damage evolution law of shear creep in carbonaceous shale (weak interlayer of slope) was revealed, and the accuracy of the established shear creep damage model was verified. Finally, the damage evolution law of carbonaceous shale was quantitatively analyzed. Results show that: The shear creep damage model established in this article has unique advantages. The greater the initial damage, the more likely shear creep failure is to occur under the influence of dynamic disturbance and shear creep loads. Dynamic disturbance accelerates the damage of weak interlayers of slope. The cumulative coupling damage of carbonaceous shale (D ma ≤0.18) under dynamic disturbance and multi-stage shear creep loads exhibits an S-like evolution pattern. The shear creep damage mechanism of carbonaceous shale is characterized by obvious initial damage effect, dynamic disturbance damage effect, and stress response characteristics.

Regulatory roles of histamine receptor in astrocytic glutamate clearance under conditions of increased glucose variability

In diabetic patients, repeated episodes of hypoglycemia can increase glucose variability (GV), which may lead to glutamate neurotoxicity in the brain and consequently affect cognitive functions. Astrocytes play a crucial role in regulating the balance of glutamate within the brain, and their function is influenced by the histamine receptor (HR) signaling pathway. However, the specific role of this mechanism under conditions of high GV is not yet clear. The results showed that increased GV resulted in decreased expression of HRs in mice hippocampus and astrocytes cultured in vitro. Additionally, a decrease in the expression of proteins related to glutamate metabolic clearance was observed, accompanied by a reduction in glutamate reuptake capacity. Notably, the intervention with histidine/histamine was able to reverse the above changes. Further mechanistic studies showed that inhibition of HRs that increased GV led to significant disturbances in astrocytic mitochondrial function. These abnormalities encompassed increased fragmentation morphology and the accumulation of reactive oxygen species, accompanied by decreased mitochondrial respiratory capacity and dysregulation of dynamics. Distinct HR subtypes exhibited variations in the modulation of mitochondrial function, with H3R demonstrating the most pronounced impact. The overexpression of H3R could enhance glutamate metabolic by reversing disturbances in mitochondrial dynamics. Therefore, this study suggests that H3R is able to maintain glutamate metabolic clearance capacity and exert neuroprotective effects in astrocytes that increased GV by regulating mitochondrial dynamic balance. This provides an important basis for potential therapeutic targets for diabetes-related cognitive dysfunction.

Development of a dynamic cumulative damage model and its application to underground hydropower caverns under multiple blasting

Underground infrastructures are crucial for resource extraction, energy storage, and space utilisation. The geomaterials that make up these structures, such as rock and concrete, are subjected to multiaxial stress conditions and are frequently exposed to dynamic and extreme loadings caused by both natural disasters and human activities. These stresses are particularly significant during the construction phase, which involves operations such as drilling and blasting excavation, as well as during the operational phase, which may include events like explosions. For instance, while drilling and blasting induce rock breakage within the excavated profile as designed, they inevitably lead to the formation of a damage zone in the surrounding rock mass. Moreover, the cumulative effects of sequential excavations and multiple blasts can cause significantly greater damage, thereby threatening the stability of tunnel structures during the operation phase. This paper highlights the importance of thoroughly analysing these phenomena during both static and dynamic loadings to ensure the stability of underground infrastructures. To address these challenges, a rate-dependent damage constitutive model is proposed for geomaterials to assess the impacts of blasting loads and the cumulative damage resulting from repeated blasts. The model is conceptualised using the strength envelope of loading-unloading curves to represent the progressive accumulation of damage under repeated impacts. Through theoretical derivation, a dynamic cumulative damage model is developed, based on a modified Mohr-Coulomb strain-softening model incorporating rate-dependent parameters, and is validated against dynamic experimental data. The model captures the transition between static strain-softening and dynamic cumulative damage, triggered by a critical strain-rate threshold. The applicability of the model is demonstrated through simulations of tunnel excavation, emphasising the impact of blasting loads and the accumulation of damage zones. To assess its practical feasibility, the developed model is applied to simulate different excavation scenarios for an underground hydropower cavern. Damage in the surrounding rock mainly results from static unloading and/or dynamic disturbances. Blasting construction, in particular, causes significant damage in tunnel intersection zones and the connecting areas of two benches, leading to increased displacement and higher damage levels compared to static excavation. To mitigate excessive damage while maintaining the construction timeframe, it is recommended to consider alternating cycles of dynamic loading and static excavation unloading continuously, which helps understand damage formation in critical zones without significantly delaying project completion.

Dynamic Integrated Scheduling of Production Equipment and Automated Guided Vehicles in a Flexible Job Shop Based on Deep Reinforcement Learning

The high-quality development of the manufacturing industry necessitates accelerating its transformation towards high-end, intelligent, and green development. Considering logistics resource constraints, the impact of dynamic disturbance events on production, and the need for energy-efficient production, the integrated scheduling of production equipment and automated guided vehicles (AGVs) in a flexible job shop environment is investigated in this study. Firstly, a static model for the integrated scheduling of production equipment and AGVs (ISPEA) is developed based on mixed-integer programming, which aims to optimize the maximum completion time and total production energy consumption (EC). In recent years, reinforcement learning, including deep reinforcement learning (DRL), has demonstrated significant advantages in handling workshop scheduling issues with sequential decision-making characteristics, which can fully utilize the vast quantity of historical data accumulated in the workshop and adjust production plans in a timely manner based on changes in production conditions and demand. Accordingly, a DRL-based approach is introduced to address the common production disturbances in emergency order insertions. Combined with the characteristics of the ISPEA problem and an event-driven strategy for handling dynamic events, four types of agents, namely workpiece selection, machine selection, AGV selection, and target selection agents, are set up, which refine workshop production status characteristics as observation inputs and generate rules for selecting workpieces, machines, AGVs, and targets. These agents are trained offline using the QMIX multi-agent reinforcement learning framework, and the trained agents are utilized to solve the dynamic ISPEA problem. Finally, the effectiveness of the proposed model and method is validated through a comparison of the solution performance with other typical optimization algorithms for various cases.

Analysis of the dynamic response and damage characteristic for the tunnel under near-field blasts and far-field earthquakes

The dynamic response and failure characteristics of tunnels vary significantly under various dynamic disturbances. These characteristics are crucial for assessing structural stability and designing effective support for surrounding rock. In this study, the theoretical solution for the dynamic stress concentration factor (DSCF) of a circular tunnel subjected to cylindrical and plane P-waves was derived using the wave function expansion method. The existing equivalent blast stress wave was optimized and the Ricker wavelet was introduced to represent the seismic stress waves. By combining Fourier transform and Duhamel’s integral, the transient response of the underground tunnel under near-field blasts and far-field earthquakes was determined in both the frequency and time domains. The theoretical results were validated by comparing them with those obtained from numerical simulations using ANSYS LS-DYNA software. Numerical simulations were conducted to further investigate the damage characteristics of the underground tunnel and evaluate the effect of initial stress on structural failure under both types of disturbances. The theoretical and numerical simulation results indicated that the differences in the dynamic response and damage characteristics of the underground tunnel were primarily due to the curvature of the stress waves and transient load waveform. The locations of the maximum DSCF values differed between near-field blasts and far-field earthquakes, whereas the minimum DSCF values occurred at the same positions. Without initial stress, the blast stress waves caused spalling damage to the rock mass on the wave-facing side. Shear failure occurred near the areas with maximum DSCF values, and tensile failure occurred near the areas with minimum DSCF values. In contrast, damage occurred only near the areas with maximum DSCF values under seismic stress waves. Furthermore, the initial stress exacerbated spalling and shear damage while suppressing tensile failure. Hence, the blast stress waves no longer induced tensile failure on the tunnel sidewalls under initial stress.

Composite Anti-Disturbance Control for Nonlinear Hidden Markov Jump Systems Under Replay Attacks: A Dynamic Output-Feedback Method.

This article is dedicated to researching the problem of composite anti-disturbance control for nonlinear hidden Markov jump systems, described by the interval type-2 Takagi-Sugeno fuzzy method, under replay attacks in the continuous-time domain. Based on dynamic output feedback control and disturbance observer, a fuzzy composite controller, following the core idea of nonparallel distribution compensation, is designed to compensate for the impact of multiple disturbances. For replay attacks, a multisensor scheme with the detection mechanism is introduced, enabling the studied systems to remain stable even under attacks. Afterward, with the aid of the Lyapunov stability theory, sufficient conditions for ensuring the stability of the resulting systems are deduced, and then the gains of the desired controller and disturbance observer are obtained. Finally, the rationality and effectiveness of the established method are demonstrated through simulation, as well as its superiority over the traditional Hinfty control method.

Mechanism and prevention of coal bursts in gob-side roadway floor under thick and hard roof in the deep mining area of Ordos

The complex stress environment in deep roadways, often exacerbated by thick and hard strata, frequently precipitates coal bursts, posing significant safety hazards. This paper investigates the mechanisms and preventive methods for coal bursts in the gob-side roadway floor (GSRF) under thick and hard roof in the Ordos region, China. First, the stress-distributing characters of GSRF were analyzed then a stress calculation formula was derived. A mechanical model was developed to determine the critical stress for buckling failure of the roadway floor strata. Criteria for the bursting instability of GSRF were then established. The lateral static load from the adjacent gob, the advancing static load from the working face, and the disturbance load from overlying thick and hard roof fractures combine to transmit high loads and energy to the roadway floor via the “roof → rib → floor” pathway, causing increased stress concentration and energy accumulation. When the conditions satisfy the criteria for bursting instability, coal bursts can occur on the roadway floor. To mitigate dynamic load disturbances, the paper proposes roof regional fracturing and abrasive water jet axial roof cutting. Hydraulic reaming of gutters in the roadway ribs and deep hole blasting at the roadway bottom corners are offered to alleviate the static loads on the surrounding rock. The implementation of targeted prevention measures for dynamic and static loads effectively reduces coal bursts in GSRF. These findings offer an example of preventing and controlling coal bursts in other mines of the Ordos region with comparable geological conditions.