Integral Mode Research Articles

Discrete‐Time Integral Fast Terminal Sliding Mode Predictive Control for Dynamic Positioning Ships With Lumped Uncertainties and Input Constraints

ABSTRACTThis paper proposes a robust discrete‐time integral fast terminal sliding mode predictive control (DIFTSMPC) scheme for DP ship trajectory tracking under the consideration of unmodeled dynamics, environmental disturbance, and input constraints. An improved single closed‐loop control strategy is designed by adopting the earth‐fixed reference velocity as the virtual velocity. The improved nonlinear PID discrete‐time integral fast terminal sliding mode is designed to achieve faster convergence. The unknown nonlinear dynamics and the environmental disturbance are combined as a lumped uncertainty term and estimated using the one‐step delay observation method. Then the corrected sliding model state is optimized to track the reference sliding reaching law in the prediction horizon. The lumped uncertainty estimation is integrated into the sliding mode prediction to guarantee the robustness of the control scheme. The stability of the proposed scheme has been verified. Comparison results demonstrate the effectiveness and superiority in chattering suppressing and constraint handling of the proposed scheme.

Analysis on Teaching Reform under the Mode of Integration of Curriculum and Certificate

Analysis on Teaching Reform under the Mode of Integration of Curriculum and Certificate

Study on the Innovative Development Path of Rural Characteristic Sports Events in Ganzi Prefecture under the Background of Culture and Tourism Integration

Under the background of cultural and tourism integration, the development of rural characteristic sports events in Ganzi Prefecture faces new opportunities and challenges. By analyzing the rich culture, natural resources and the current situation of characteristic sports events in Ganzi Prefecture, this paper discusses how to innovate the development of these events in order to realize the deep integration of cultural tourism and rural sports and promote the development of local economy and society. The study finds that Ganzi Prefecture has a broad space for innovation in terms of event branding, integration of events and tourism projects, technological empowerment and community participation. To this end, this paper proposes an innovative path based on the excavation of local cultural resources, branding, digital promotion and industry linkage development, specifically including event branding, exploration of the integration mode of culture and tourism, the application of scientific and technological means, and the improvement of the community participation mechanism.

Robust Bumpless Transfer Control for Switched Systems with Unmatched Uncertainties Based on the Common Robust Integral Sliding Mode Under Arbitrary Switching Rules

In this paper, a robust bumpless transfer control scheme for tracking control is proposed to avoid large jumps in the control signals for a switched system (SS) with unmatched uncertainty and disturbance. The robust bumpless controller comprises a robust linear feedback control (RLFC) and a continuous sliding mode control (CSMC) based on the given robust integral sliding mode (RISM). The RLFC meets the requirement of bumpless indices, and the CSMC suppresses the unmatched uncertainty and disturbance. First, the RLFC design is proposed, and the linear feedback coefficients satisfy the bumpless indices, despite the uncertainty and disturbance. Then, a RISM surface design is proposed, in which the uncertain SS satisfies the given H-infinity robust performance index, and can resist the unmatched uncertainty. Consequently, the CSMC ensures that the RISM surface can be reached in finite time from the initial time instant. By composing the CSMC with the RLFC, the control scheme achieves the robust trajectory tracking and the suppression of the control signal bumps during switching. Finally, the proposed robust bumpless transfer control scheme was applied to the different examples, and the simulation results verified its effectiveness.

Stochastic neuropeptide signals compete to calibrate the rate of satiation.

Neuropeptides have important roles in neural plasticity, spiking and behaviour1. Yet, many fundamental questions remain regarding their spatiotemporal transmission, integration and functions in the awake brain. Here we examined how MC4R-expressing neurons in the paraventricular nucleus of the hypothalamus (PVHMC4R) integrate neuropeptide signals to modulate feeding-related fast synaptic transmission and titrate the transition to satiety2-6. We show that hunger-promoting AgRP axons release the neuropeptide NPY to decrease the second messenger cAMP in PVHMC4R neurons, while satiety-promoting POMC axons release the neuropeptide αMSH to increase cAMP. Each release event is all-or-none, stochastic and can impact multiple neurons within an approximately 100-µm-diameter region. After release, NPY and αMSH peptides compete to control cAMP-the amplitude and persistence of NPY signalling is blunted by high αMSH in the fed state, while αMSH signalling is blunted by high NPY in the fasted state. Feeding resolves this competition by simultaneously elevating αMSH release and suppressing NPY release7,8, thereby sustaining elevated cAMP in PVHMC4R neurons throughout a meal. In turn, elevated cAMP facilitates potentiation of feeding-related excitatory inputs with each bite to gradually promote satiation across many minutes. Our findings highlight biochemical modes of peptide signal integration and information accumulation to guide behavioural state transitions.

Adaptive Integral Sliding Mode Control with Chattering Elimination Considering the Actuator Faults and External Disturbances for Trajectory Tracking of 4Y Octocopter Aircraft

This paper presents a control strategy for a 4Y octocopter aircraft that is influenced by multiple actuator faults and external disturbances. The approach relies on a disturbance observer, adaptive type-2 fuzzy sliding mode control scheme, and type-1 fuzzy inference system. The proposed control approach is distinct from other tactics for controlling unmanned aerial vehicles because it can simultaneously compensate for actuator faults and external disturbances. The suggested control technique incorporates adaptive control parameters in both continuous and discontinuous control components. This enables the production of appropriate control signals to manage actuator faults and parametric uncertainties without relying only on the robust discontinuous control approach of sliding mode control. Additionally, a type-1 fuzzy logic system is used to build a fuzzy hitting control law to eliminate the occurrence of chattering phenomena on the integral sliding mode control. In addition, in order to keep the discontinuous control gain in sliding mode control at a small value, a nonlinear disturbance observer is constructed and integrated to mitigate the influence of external disturbances. Moreover, stability analysis of the proposed control method using Lyapunov theory showcases its potential to uphold system tracking performance and minimize tracking errors under specified conditions. The simulation results demonstrate that the proposed control strategy can significantly reduce the chattering effect and provide accurate trajectory tracking in the presence of actuator faults. Furthermore, the efficacy of the recommended control strategy is shown by comparative simulation results of 4Y octocopter under different failing and uncertain settings.

Distributed Adaptive Integral Sliding Mode Affine Formation Maneuver Control for Multiple AUVs With Event-Triggered Chattering- Reduction Mechanism

Distributed Adaptive Integral Sliding Mode Affine Formation Maneuver Control for Multiple AUVs With Event-Triggered Chattering- Reduction Mechanism

Novel Surface Integral Equation-Based Sub-Structure Characteristic Mode Formulations for Lossy Composite Objects

Novel Surface Integral Equation-Based Sub-Structure Characteristic Mode Formulations for Lossy Composite Objects

A collaborative planning of PCCs siting and transmission network expansion for super large‐scale offshore wind clusters

AbstractThe integration of super large‐scale offshore wind clusters into the onshore power grid brings challenges for the flexibility of the transmission network. Therefore, this paper proposes a two‐stage collaborative planning of points of common coupling siting and transmission network expansion for super large‐scale offshore wind clusters, based on a multi‐voltage‐level stratified integration mode which enables offshore wind power to transmit to larger regions for accommodation. At first, the transmission network flexibility indexes are established. Then, a two‐stage collaborative planning model for points of common couplings siting and transmission network expansion is proposed, which comprises a collaborative planning model and an optimal power flow operation model. The proposed model reduces wind curtailment and load shedding by optimizing the annual total cost and flexibility transmission capability of the network. Finally, the effectiveness of the proposed method is verified using a modified IEEE 30‐bus system and a 65‐bus system.

A socio-cognitive perspective of knowledge integration in digital innovation networks

Digital innovation is a complex process in which actors seek to create new value pathways by combining digital resources in a layered modular architecture. While IS scholarship has a rich tradition of research on developing and implementing digital artefacts within intra-organisational contexts, our understanding of knowledge integration across distributed innovation networks is nascent and under-theorised. This is an important area of research given the rising importance of digital innovation networks and the challenges faced in integrating specialised knowledge, especially given the greater diversity, speed, reach, and scope made possible by digital technologies. Drawing on in-depth case study findings from a health IoT project involving multiple organisations and disciplines, we explore how knowledge is integrated across boundaries during the initiation stage of a digital innovation network. Our findings point to boundaries related to the digital platform’s organising vision, resource allocation, delivery roadmap, technical architecture, and intellectual property, to name but a few challenges. We then reveal five socio-cognitive modes of knowledge integration which actors strategically enact to cross syntactic, semantic, and pragmatic boundaries: Signalling, Assembling, Contesting, Discounting, and Finalising. The choice of mode depends on the perceived knowledge status (‘what they know’) and social status (‘who they are’) of network actors, which highlight the salience of both social and cognitive dependencies for knowledge integration. We further discuss the contribution of design objects for overcoming differences and distinctions between specialist actors in a digital innovation network.

Application Research of Power Measurement Data Exchange Based on Uninterruptible Power Supply

With the maturity of the smart meter embedded system integration mode, the power consumption information can be fed back to the management center by the intelligent terminal through the power Internet of Things. The smart terminal adopts the narrowband data communication mode. However, the narrowband channel interval is hindered by interference signals, resulting in serious data packet loss. Therefore, a stable and efficient acquisition scheme is needed to ensure its smooth interaction. Based on the application of smart meter data communication, we analyze the power consumption optimization and carrier transmission optimization of the power Internet of Things and propose a data analysis method based on self-learning and external characteristics, which is used to calculate the offline execution strategy of smart meters when they encounter factors such as power outage or intrusion. A production task-driving rule is designed. The external characteristics of deep learning data of the power Internet of Things are collected. The accuracy of data classification is judged according to the parallel Internet of Things of a convolutional neural network and a long-term and short-term memory deep neural network. When dealing with high-dimensional original data, the data network is graded to reduce the work of feature selection and the difficulty of training. Moreover, we improve the autonomous execution ability of an embedded terminal device in an offline state. We also strengthen the ability of abnormal data detection and judgment learning to meet the requirements of efficient and stable operation of the power grid. Simulation results verify that compared with the current mainstream schemes, the performance of the proposed scheme is improved by more than 17%. Besides, the fault tolerance rate is enhanced by 29%, and the power consumption after optimization is reduced by 26.3% and 42.8%. These effects highlight the role of data processing in embedded systems. It solves the problem of abnormal data and energy loss affecting the accuracy of error estimation of electric energy meters, opens up a new way for data acquisition and processing of large-scale smart meters, and further improves the service level of information management of power systems.

A dendritic substrate for temporal diversity of cortical inhibition.

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Research on the Optimization of Practical Teaching System under the Mode of Integration of Production and Teaching in Institute of Navigation Technology and Industry

Under the background of global economic integration and the rapid development of shipping industry, navigation technology education is facing challenges such as the disconnection between theory and practice and limited practical opportunities. In order to meet these challenges, this paper deeply analyzes the implementation status of the integration mode of production and teaching in Maritime Technology Industry College, and discusses its advantages and disadvantages in personnel training, curriculum system construction, teacher team development, training base construction and teaching quality monitoring. Through the strategies of modular curriculum design, virtual simulation training, enterprise internship opportunities, double-qualified teachers training and diversified evaluation system, this paper puts forward a set of plans to comprehensively optimize the practice teaching system. The program aims to enhance students' practical ability, innovation ability and professional accomplishment, make them better adapt to the needs of the industry, and provide high-quality talent guarantee for the sustainable development of the navigation technology industry. At the same time, this paper also emphasizes the importance of school-enterprise cooperation, and realizes the deep integration and sharing of educational resources and industrial resources through co-construction of curriculum system, teaching staff and training base. Finally, this paper looks forward to the potential contribution of the optimized practical teaching system in improving teaching quality, promoting industrial upgrading and technological innovation.

Control Design of the Quadrotor Aircraft based on the Integral Adaptive Improved Integral Backstepping Sliding Mode Scheme

Control Design of the Quadrotor Aircraft based on the Integral Adaptive Improved Integral Backstepping Sliding Mode Scheme

‘Pooling and Sharing’ and ‘Permanent Structured Cooperation’ as the Current EU’s Defense and Security Integration Modes

ABSTRACT When an urgent response in international relations is needed, the EU institutions and Member States’ governments face a deficiency of effective and practical mechanisms in security cooperation. Developing autonomous programs and concepts that address this dilemma, preventing duplication of endeavors and investments, and maximizing cost-effectiveness by broadening military-political consultations on all issues of common concern is challenging. This article analyses the path and logic of EU security integration in the recent decade. In this context, the origins and goals of the pooling and sharing concept are essential to analyze the continuity of security integration, where the Council’s introduction of Permanent Structured Cooperation in defense and security is an important step forward. Therefore, this article will investigate whether and how P&S and PESCO have been related and complemented, even though both differ in the prism of aims, logic, decision-making processes, and funding. Due to budgetary throwbacks in recent decades and the war in Ukraine intensified after February 2022, EU Member States’ governments might evaluate their approach to the level of engagement in common security programs.

Direct Power Control of BDFRG Based on Novel Integral Sliding Mode Control

Direct Power Control of BDFRG Based on Novel Integral Sliding Mode Control

Tracking performance and power quality enhancement of DFIG based wind turbine using robust integral terminal sliding mode control

The aim of this work is to develop a robust Integral Terminal Sliding Mode Control (ITSMC) strategy for a Doubly Fed Induction Generator (DFIG) wind turbine (WT) operating in challenging conditions. This controller is designed to manage the system's rotor side converter (RSC) and grid side converter (GSC), ensuring maximum power production, improved power quality, and accurate tracking of system state variables, even in the face of fluctuating wind conditions, parameter uncertainties, and external disturbances. The stability of the proposed controller is assured using the Lyapunov theory. The performance of ITSMC is compared with that of the conventional sliding mode controller (SMC) and backstepping controller through simulation tests, using the integral absolute error (IAE) as a performance metric. The results highlight the superiority of ITSMC, demonstrating its ability to precisely track reference values, eliminate static errors, and minimize chattering. ITSMC consistently achieves the lowest IAE for all tracked state variables and across all test scenarios. A comparative study analyzing the Total Harmonic Distortion (THD) of the proposed controller versus SMC, the backstepping controller, and other similar works in the literature shows a marked improvement in the THD of stator and filter currents by at least 24.53 % and 7.96 %, respectively. These findings underscore the controller's capability to enhance the power quality delivered to the grid.

Robust fractional-order load frequency control for hybrid power system concerning high wind penetration

Hybrid power systems concerning wind farms have witnessed significant dynamic characteristic changes due to unpredicted generation output and integration mode conversion between frequency-sensitive wind plants and non-scheduled ones. This work presents a robust fractional-order load frequency control (LFC) method for a multi-area hybrid power system in the presence of wind penetration uncertainties. To characterize the injection effect of wind farms, the power system is described by a model with an uncertain wind penetration factor in a pre-estimated range. Then, an enhancement of Levy’s identification method is developed to convert this model into a fractional-order reduced structure to design the load frequency controller, which is in a form of fractional-order PID with a filter for ease of engineering implementation. The closed-loop stability is analyzed by the stability boundary locus (SBL) method under different wind penetration levels. It is shown that superior frequency response performance and system robustness can be obtained if the controller is designed in terms of the model with the worse-case wind penetration. Illustrative examples including a three-area hybrid power system under a variety of wind penetration variations are given to show the effectiveness of the proposed method.

High Voltage Monolithic Active Pixel Sensors for the MOLLER experiment

The MOLLER experiment [1] aims to measure the parity-violating asymmetry (APV) in electron–electron scattering at 11 GeV, and thus determine the weak charge of the electron to a high precision (2.4%). Two of the key sub-systems in the experimental apparatus are the main detector array, consisting of 224 fused silica detector modules and an electron beam Compton polarimeter. The main detector array can be operated in either pulsed mode for particle tracking, or integration mode for the asymmetry measurement at high rate detection. A subset of these detector modules will be equipped with an array of High Voltage Monolithic Active Pixel Sensors (HVMAPS), to be used in particle tracking and allowing for real-time monitoring of the event profile in the main Møller region. HVMAPS are also used for the Compton polarimeter, consisting of four-plane planes of HVMAPS chips, housed in a vacuum chamber upstream of the interaction point. An overview of the implementation of the HVMAPS for the main detectors and Compton polarimeter is provided.