This paper considers model predictive control (MPC) for linear systems under relaxed constraints. The main novelty of our proposal is the introduction, and an adequate use, of the terminal dynamics of the slack variable associated with relaxed constraints. The proposed MPC under relaxed constraints retains computational efficiency of the traditional MPC, while it guarantees positive invariance and exponential stability over an enlarged domain of attraction. The design method is also illustrated in a step-by-step manner by an academic example.
In this chapter, we discuss the sustainable ultra-dense heterogeneous networks (UDHN). Section 2.1 introduces the motivation of developing sustainable UDHN. Section 2.2 presents one potential network architecture for UDHN, and Sect. 2.3 investigates the random access problem in UDHN, where we focus on the machine-type communication (MTC) devices and develop a random access scheme for MTC devices to improve the network efficiency while reducing the signaling overhead. Section 2.4 analyzes the challenges of UDHN, and Sect. 2.5 concludes this chapter.
In this chapter, we investigate the compressive sensing (CS) based dynamic estimation algorithm in a unified laser telemetry, tracking, and command (TTC) system. Section 6.1 introduces the motivation of designing the CS-based dynamic estimation algorithm for the unified laser TTC system. Section 6.2 presents the system model. Section 6.3 details the CS-based dynamic estimation algorithm, and Sect. 6.4 analyses the performance and the complexity of developed algorithm. Section 6.5 presents the simulation results, and Sect. 6.6 concludes this chapter.
Underdeveloped infrastructure and inconvenient water and heating in winter are important factors restricting the improvement of living conditions and quality of life in cold rural areas in China. Developing energy-saving, sustainable, and autonomous communities for self-sufficiency in suitable areas is an effective way to overcome the above difficulties and improve the quality of life of farmers, which is significant to developing economy and saving land and energy. Based on the self-sufficiency technology, the paper puts forward the concept of Autonomous Community for Self-sufficiency and implementation strategy. Contraposing the regional climate feature, community environment and facility, utilization of energy and resources in Beijing countryside, it analyzes the technical feasibility and application of rural autonomous community for self-sufficiency from three aspects of neighborhood, cluster and community under co-construction and sharing. The energy-saving principle, structure and construction method, frontier development and application effectiveness of technologies of autonomous community are discussed afterwards. It gives the conclusion and suggestion on the technological choice and management mechanism at the end.
The distribution of lubricating oil in the bearing cavity is of great significance to bearing lubrication and cooling. A new idea is provided to further study the ball bearings lubrication, to achieve effective lubrication of bearings. The flow field of oil injection lubrication ball bearings is studied by the moving particle semi-implicit (MPS) method. The accuracy of the numerical calculation method is verified by experiments. The oil distribution of the bearing lubrication flow field and churning torque of the ball and cage at different speeds are analyzed. The research results show the maximum oil content in the bearing cavity is distributed in the range of about 90° to 120°. As the increase of rotating speed, the number of particles in the bearing cavity decreases. The churning torque decreases with the increase of rotating speed and increases with the increase of the oil viscosity. This study provides a new numerical calculation method for the lubrication flow field of ball bearings.
In this paper, the cooperative control of heterogeneous multi-agent systems (HMASs) subject to certain constraints are surveyed. First, HMASs are classified into two categories, namely, weak and strong HMASs, according to different cooperative behaviours. Then, control strategies are discussed for HMASs when facing different sorts of constraints imposed on the agent dynamics and on the communication networks. Subsequently, some latest results on the cooperative control subject to various kinds of constraints are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Sub-Saharan Africa (SSA) was colonised for about a century by the British, French and other European countries. Therefore, we examine these forms of colonisation on accounting development in Africa. We use a description-explanatory approach to show how three forms of colonisation have driven the development of accounting in Africa during and post-colonisation era. This paper defines driving forces during the colonisation period as ex-ante driving forces, and after independence, as ex-post driving forces. We identify among the ex-ante driving forces, governance, economic policy, education and language influenced accounting systems/practices, and they are still predominant. Regarding the ex-post, we found four ex-post driving forces that impact accounting in SSA, which supports the instrumental form of accounting colonisation. These four driving forces are foreign aid, foreign trade liberalisation, membership in international associations and prevalence of foreign ownership. This paper provides insights into how accounting practices have evolved in Africa and how colonisation has driven different accounting systems across the continent. Unlike prior studies, which are limited to pre or post-colonial eras, we provide an understanding of accounting development during the colonial and post-colonial era. Therefore, we demonstrate how colonisation still influences accounting development even after independence in many African countries.
A personal microclimate management system is designed to maintain thermal comfort which allows people to overcome a harsh environment. It consists of several micro-fans placed in the garment side seam to provide cooling air. The computational fluid dynamics method was used to simulate the three-dimensional model and analysis the influence of fan’s number and air gap distance. The obtained results depict that the introduced cool airflow will find its way along paths with flow resistance minimized and exhaust through several separated exit. The body heat flux is taken away at the same time. The convection effect is enhanced by the increase in the fans’ numbers, but the fans’ cooling effect varies a lot because of various air gap distances. When the air gap is small enough, the cooling air impact the body surface directly and causes fierce heat loss. While the air gap distance is large enough, the heat transfer along the skin surface could be enhanced by the eddy flow which is existed in the air gap between body and garment. These phenomena can maintain the body’s thermal comfort in a suitable range.
The Precise Point Positioning (PPP) service of BeiDou-3 Navigation Satellite System (BDS-3) is implemented on its Geostationary Earth Orbit (GEO) satellites. However, its signal design is limited by the actual power of satellite and other conditions. Furthermore, the design needs to fully consider the compatibility of different service phases. Starting from the actual state of the BDS-3 GEO satellite, this paper studies the multiplexing modulation of the BDS PPP service signal that is based on the Asymmetric Constant Envelope Binary Offset Carrier (ACE-BOC) technique and proposes several feasible schemes for this signal. Comparison and optimization of these techniques are made from the aspects of transmission efficiency, multiplexing efficiency, and service forward compatibility. Based on the Type-III ACE-BOC multiplexing modulation technique, phase rotation and intermodulation reconstruction techniques are proposed to suppress the intermodulation interference issue. Finally, a signal based on improved ACE-BOC multiplexing is designed. The quality of the proposed signal was continuously monitored and tested using large-diameter antennas. The evaluation results show that the power spectrum deviation of the signal is 0.228 dB, the correlation loss is 0.110 dB, the S-curve slope deviation is 1.558% on average, the average length difference between the positive/negative chip and the ideal chip is only 0.0006 ns, and the coherence between the carrier and the pseudo code is 0.082°. All quality indicators are satisfactory, indicating that the proposed signal multiplexing modulation technique is an ideal solution that meets all the requirements of the design constraints, and can achieve efficient information broadcasting and forward compatibility of the BDS PPP service.
Music is the language of emotions. In recent years, music emotion recognition has attracted widespread attention in the academic and industrial community since it can be widely used in fields like recommendation systems, automatic music composing, psychotherapy, music visualization, and so on. Especially with the rapid development of artificial intelligence, deep learning-based music emotion recognition is gradually becoming mainstream. This paper gives a detailed survey of music emotion recognition. Starting with some preliminary knowledge of music emotion recognition, this paper first introduces some commonly used evaluation metrics. Then a three-part research framework is put forward. Based on this three-part research framework, the knowledge and algorithms involved in each part are introduced with detailed analysis, including some commonly used datasets, emotion models, feature extraction, and emotion recognition algorithms. After that, the challenging problems and development trends of music emotion recognition technology are proposed, and finally, the whole paper is summarized.
TTPs (Tactics, Techniques, and Procedures), which represent an attacker’s goals and methods, are the long period and essential feature of the attacker. Defenders can use TTP intelligence to perform the penetration test and compensate for defense deficiency. However, most TTP intelligence is described in unstructured threat data, such as APT analysis reports. Manually converting natural language TTPs descriptions to standard TTP names, such as ATT&CK TTP names and IDs, is time-consuming and requires deep expertise. In this paper, we define the TTP classification task as a sentence classification task. We annotate a new sentence-level TTP dataset with 6 categories and 6061 TTP descriptions from 10761 security analysis reports. We construct a threat context-enhanced TTP intelligence mining (TIM) framework to mine TTP intelligence from unstructured threat data. The TIM framework uses TCENet (Threat Context Enhanced Network) to find and classify TTP descriptions, which we define as three continuous sentences, from textual data. Meanwhile, we use the element features of TTP in the descriptions to enhance the TTPs classification accuracy of TCENet. The evaluation result shows that the average classification accuracy of our proposed method on the 6 TTP categories reaches 0.941 . The evaluation results also show that adding TTP element features can improve our classification accuracy compared to using only text features. TCENet also achieved the best results compared to the previous document-level TTP classification works and other popular text classification methods, even in the case of few-shot training samples. Finally, the TIM framework organizes TTP descriptions and TTP elements into STIX 2.1 format as final TTP intelligence for sharing the long-period and essential attack behavior characteristics of attackers. In addition, we transform TTP intelligence into sigma detection rules for attack behavior detection. Such TTP intelligence and rules can help defenders deploy long-term effective threat detection and perform more realistic attack simulations to strengthen defense.
To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm, based on the driver-behavior-based transferable motion primitives (MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints, trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.
A piecewise acoustic metasurface is designed to suppress the first mode while marginally amplifying the Mack second mode in a Mach 4 flat-plate boundary layer (BL) flow. The results of linear stability theory (LST) and the e N method demonstrate the stabilization effect and transition delay performance, respectively. However, the direct numerical simulation (DNS) results indicate that the designed broadband acoustic metasurface actually weakly excites the first mode with a slightly larger fluctuating pressure amplitude at the surface, which is in contrast to the analysis of LST. The discrepancies are found to lie in the ‘roughness’ effect caused by the recirculation zones inside the microslits and the alternating expansion and compression waves induced at the slit edges, which significantly amplifies the first mode. For further clarification of the competitive mechanism between the acoustic stabilization and ‘roughness’ destabilization effects of metasurfaces on the first mode, a carefully designed metasurface is installed at the maximum growth rate region, which excites the first mode on the metasurface but inhibits its development downstream.
Spin light manipulation based on chiral metasurfaces is a striking hotspot that has intrigued huge attention. Circular dichroism, a unique phenomenon of chiral atoms/molecules, has been regarded as another auxiliary dimension for guiding electromagnetic waves, which has been explored in the field of artificial material sciences yet a challenging issue. Here, a generic strategy based on dynamic chiral meta-atom for revealing strong circular dichroism as well as applicable electromagnetic functionality is proposed in microwave regime. We demonstrate a dynamic metasurface that enables the fully independent holograms reconstruction for one circular polarization or the other at the active operating state. On the other hand, the electromagnetic scattering is realized for lowering observable backward reflection at the passive state. Numerical simulation and experimental verification are conducted to manifest the feasibility. It is expected that the proposed strategy can be applied to broaden the horizon for dynamic chiral meta-devices and may find applications in information encryption, anti-counterfeiting, and other dynamic systems.
Cavitation inside a torque converter induces noise, vibration and even failure, and these effects have been disregarded in previous torque converter design processes. However, modern torque converter applications require attention to this issue because of its high-speed and high-capacity requirements. Therefore, this study investigated the cavitation effect on a torque converter using both numerical and experimental methods with an emphasis on the influence of the charging oil feed location and charge pressure. Computational fluid dynamics (CFD) models were established to simulate the transient cavitation behaviour in the torque converter using different charging oil pressures and inlet arrangements and testing against a base case to validate the results. The CFD results suggested that cavitating bubbles mainly takes place in the stator of the torque converter. The transient cavitation CFD model yielded good agreement with the experimental data, with an error of 7.6% in the capacity constant and 7.4% in the torque ratio. Both the experimental and numerical studies showed that cavitation induced severe capacity degradation, and that the charge pressure and charging oil configuration significantly affects both the overall hydrodynamic performance and the fluid behaviour inside the torque converter because of cavitation. Increasing the charge pressure and charging the oil from the turbine-stator clearance were found to suppress cavitation development and reduce performance degradation, especially in terms of the capacity constant. This study revealed the fluid field mechanism behind the influence of charging oil conditions on torque converter cavitation behaviour, providing practical guidelines for suppressing cavitation in torque converter.
Thermometric detectors are crucial in evaluating the condition of target objects spanning from environments to the human body. Optical-based thermal sensing tools have received extensive attention, in which the photon upconversion process with low autofluorescence and high tissue penetration depth is considered as a competent method for temperature monitoring, particularly in biomedical fields. Here, we present an optoelectronic thermometer via infrared-to-visible upconversion, accomplished by integrated light receiving and emission devices. Fully fabricated thin-film, microscale devices present temperature-dependent light emission with an intensity change of 1.5% °C ⁻¹ and a spectral shift of 0.18 nm °C ⁻¹ . The sensing mechanism is systematically characterized and ascribed to temperature dependent optoelectronic properties of the semiconductor band structure and the circuit operation condition. Patterned device arrays showcase the capability for spatially resolved temperature mapping. Finally, in vitro and in vivo experiments implemented with integrated fiber-optic sensors demonstrate real-time thermal detection of dynamic human activity and in the deep brain of animals, respectively.
Carbon capture, utilization, and storage (CCUS), as a technology with large-scale emission reduction potential, has been widely developed all over the world. In China, CCUS development achieved fruitful outcomes. CCUS gained further broad attention from the announcement of the carbon neutrality target by 2060, as CCUS is an indispensable important technology to realize carbon neutrality. It helps not only to build zero-emission and more resilient energy and industry systems but also provides negative emission potential. This paper discusses the new demand for carbon capture, utilization, and storage development brought by the carbon neutrality target analyzes the development status. As there remain various challenges of CCUS development, this paper focuses on several key issues for CCUS development in China targeting carbon neutrality: 1) how to reposition the role of CCUS under the carbon neutral target? 2) how shall we understand the technology development status and the costs? 3) what role shall utilization and storage play in future? 4) potential strategy applied to solve challenges of source-sink mismatch and resources constraints; and 5) new business model that suits large scale deployment of CCUS. This paper puts forward several policy suggestions that should be focused on now in China, especially to raise awareness under the vision of carbon neutrality that the role and contribution of CCUS are different, to accelerate the establishment of a comprehensive and systematic enabling environment for CCUS.
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