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In this paper, we present a framework for studying folding problems from a motion-planning perspective. The version of the motion-planning problem we consider is that of determining a sequence of motions to transform some configuration of a foldable object (the start) into another configuration (the goal). Modeling foldable objects as tree-like multilink objects allows us to apply motion-planning techniques for articulated objects with many degrees of freedom (many links) to folding problems. An important feature of this approach is that it not only allows us to study foldability questions, such as, can one object be folded (or unfolded) into another object, but it also provides us with another tool for investigating the dynamic folding process itself. The frame-work proposed here has application to traditional motion-planning areas such as automation and animation, to paper-folding problems studied in computational geometry, and to computational biology problems such as protein folding. Preliminary experimental results with paper folding and the folding of small proteins (approximately 60 residues) are quite encouraging. [ABSTRACT FROM AUTHOR]

With the introduction of automated driving, new requirements for the design and control of a vehicle powernet and powertrain arise, since the increasing level of driving automation shifts the responsibility for passengers’ safety from a driver towards automation system. Therefore, the functionality of the subsystems required for the automated transition to a standstill in case of a failure must be guaranteed. The work presented in this paper proposes a novel and generic system architecture for the energy management of a fail-operational powernet and powertrain in fault-free and failure case operation. The underlying control strategy is based on a concept enabling safety based range extension with the main goal to complete a driving mission at the safest possible location for the passengers. The proposed Energy Management System (EMS) approximates a driving trajectory to the destination based on route preview, which is then used for the dynamic optimization of the torque split in a powertrain with multiple motors. In this way, the total energy required for propulsion, which is also used as an input for the energy distribution, can be accurately predicted. The optimal distribution of the energy for the supply of safety-critical subsystems and powernet auxiliaries is then estimated by solving a mixed-integer optimization problem. If the desired driving mission cannot be completed, a three-level-degradation concept adapting the driving mission is applied. The individual modules of the EMS are presented in this paper and a system architecture enabling model predictive and adaptive energy distribution in a vehicle powertrain and powernet with automated fault reactions is proposed and exemplified with simulation results. [ABSTRACT FROM AUTHOR]

User interfaces to control networked household appliances are often inadequate. Either they are too simplistic or they are too complex and complicated relying on a PC-based interface. Therefore, a user interface that supports complex functionalities and is easy to use is required. In this article digital pen and paper are presented as a suitable interface. Digital pens are only marginally larger than their traditional counterparts, and digital paper is ordinary paper with an almost invisible unique pattern printed on it. Pen and paper are well known to users and thus an important barrier to the acceptance of networked appliances is removed. The approach is integrated with an Open Services Gateway Initiative (OSGi) gateway, thus allowing for flexibility with respect to the protocol used to communicate with the appliance. It is also shown how the approach can be applied to other appliances in and beyond the home. [ABSTRACT FROM AUTHOR]

Provides information on the publication `Fault and Disturbance Data Requirements for Automated Computer Analysis,' which describes the analysis objectives and the data necessary to facilitate automated analysis. Information on the application areas included in the publication; Listing of the types of conditions to be captured; Types of data required for analysis.

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. Results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration. [ABSTRACT FROM AUTHOR]

The lack of information regarding the systemic behavior of new software and hardware before introducing them for controlling and operating power networks consists of a major challenge for power distribution utilities towards a smart grid implementation. In this context, this paper describes an innovative and cost-effective test platform for advanced distribution automation (ADA) functionalities. The platform integrates a steady-state power system simulator, intelligent electronic devices, smart meters, communication infrastructure, and typical operation systems, using a cyber-physical system approach. The development of such platform originated a novel smart grid emulator, aiming at the execution of systemic tests and validation of ADA functionalities in a controlled environment, allowing systemic analysis rarely found in hardware-in-the-loop (HIL) testbeds. Through such an approach, it is possible to predict and solve typical issues that would be typically noticed only in field implementation. The study case presents tests of a specific algorithm for downed conductor location, considering the environment that the power distribution utility would have through the deployment of a smart grid infrastructure. The paper also discusses the robustness of the event-driven synchronization as an interface technique for HIL and software-in-the-loop environment, which is responsible for integrating operation systems, field equipment, and the power system simulator. [ABSTRACT FROM AUTHOR]

Although every educational institution has a code of academic honesty, they still encounter incidents of plagiarism. These are difficult and time-consuming to detect and deal with. This paper explores the use of personalized assessments with the goal of reducing incidents of plagiarism, proposing a personalized assessment software framework through which each student receives a unique problem set. The framework not only auto-generates the problem set but also auto-marks the solutions when submitted. The experience of using this framework is discussed, from the perspective of both students and staff, particularly with respect to its ability to mitigate plagiarism. A comparison of personalized and traditional assignments in the same class confirms that the former had far fewer observed plagiarism incidents. Although personalized assessment may not be cost-effective in all courses (such as language courses), it still can be effective in areas such as mathematics, engineering, science, and computing. This paper concludes that personalized assessment is a promising approach to counter plagiarism. [ABSTRACT FROM PUBLISHER]

Learning a good graph similarity matrix in data clustering is very crucial. The goal of clustering is to construct a good graph similarity matrix such that the similarity of points between the same classes is largest, and the similarity of points between different classes is smallest. In this paper, a more efficient subspace segmentation approach to learn a similarity matrix with large spectral gap is proposed. In our model, a robust self-representation coefficient matrix is learned by utilizing the Schatten- ${p}$ norm instead of the conventional rank function. Besides, the fast block-diagonal structure of the coefficient representation matrix is enhanced by learning and optimizing the co-association matrix with the soft label of clustering results simultaneously in a unified framework. The affinity graphs constructed in this paper can clearly reveal the intrinsic structures of the data sets. Extensive experiments on the real data sets demonstrate that our proposed method can perform better than the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The cover page of the journal "IEEE Transactions on Robotics" is presented.

The ten papers in this special section are enhanced versions of some of the best papers from the 2012 SEMI Advanced Semiconductor Manufacturing Conference. [ABSTRACT FROM AUTHOR]

There are many organizations and standard bodies that recommend segmenting the enterprise zone from the industrial zone by utilizing an industrial demilitarized zone (IDMZ). This paper will discuss the basic principles and purpose behind an IDMZ. Additionally, this paper will discuss various strategies and design considerations to help users understand their application requirements for the development and deployment of an IDMZ. [ABSTRACT FROM AUTHOR]

This paper is concerned with the moving horizon (MH) estimation issue for a type of networked nonlinear systems (NNSs) with the so-called random access (RA) protocol scheduling effects. To handle the signal transmissions between sensor nodes and the MH estimator, a constrained communication channel is employed whose channel constraints implies that at each time instant, only one sensor node is permitted to access the communication channel and then send its measurement data. The RA protocol, whose scheduling behavior is characterized by a discrete-time Markov chain (DTMC), is utilized to orchestrate the access sequence of sensor nodes. By extending the robust MH estimation method, a novel nonlinear MH estimation scheme and the corresponding approximate MH estimation scheme are developed to cope with the state estimation task. Subsequently, some sufficient conditions are established to guarantee that the estimation error is exponentially ultimately bounded in mean square. Based on that the main results are further specialized to linear systems with the RA protocol scheduling. Finally, two numerical examples and the corresponding figures are provided to verify the effectiveness/correctness of the developed MH estimation scheme and approximate MH estimation scheme. [ABSTRACT FROM AUTHOR]

A method for remote wattmeter (RW) adjustment is introduced in this paper. The estimated adjustment gain is intended for corrections of wattmeter’s indications. Currently, legal metrology regulations do not allow such type of adjustment of certified instruments in the field. However, the proposed adjustment could be applicable in the areas of private or industrial subaccounting, home automation, and so on. If the achievable uncertainty could be specified, the method might be suggested for the wattmeter’s calibration or verification. The implementation of remote adjustment becomes possible if both remote and reference wattmeters are connected to the same electrical grid and are equipped with a data communication channel. The main idea of the method is based on a temporary injection of the additional load at the location of remote device and acquisition of synchronized power readings by both reference and remote devices. The acquired readings are then processed to derive an adjustment gain of the RW. The proposed method aims to cancel an influence of the measurement unit propagating medium between the reference and remote devices. It is assumed that the characteristics of the medium are constant during the short period that is necessary to acquire readings. It is demonstrated that using the simulation of the proposed setup in the case of typical power losses in distribution lines, the adjustment gain can be estimated precisely. It is shown that in the case of remote measurement, the injected load power uncertainty can be reduced by averaging the acquired power samples. [ABSTRACT FROM AUTHOR]

This paper is focused on the issue of scheduling stabilization of Takagi–Sugeno fuzzy control systems by the aid of digging down much deeper of implicit information in the underlying systems. An event-triggered real-time scheduler that decides which control mode should be executed at any given instant is constructed by periodically evaluating the joint-distribution-type of multi-instant normalized fuzzy weighting functions at every sampled instant. Profiting from the proposed event-triggered scheduling policy, the proper control mode for the current instant is updated in order to adapt time-varying situations once if the underlying joint-distribution-type changes, and thus previous implementations of control tasks with an unchanged control mode can be further relaxed in this paper. The effectiveness of our approach is verified by several simulation examples in the end. [ABSTRACT FROM AUTHOR]

These instructions give guidelines [ABSTRACT FROM PUBLISHER]

This paper presents an improved equivalent input disturbance (EID) approach to deal with exogenous disturbances and system nonlinearities. The disturbances and nonlinearities are regarded as a lumped disturbance on the control input channel. The EID approach, which has a state observer and an EID estimator, is used to estimate the lumped disturbance. There is a constraint between the observer and the estimator on the design of the control system for the conventional EID approach. A stable zero was added to the estimator to remove the constraint and to improve the stability of the system in this paper. This ensures that the observer and the estimator can be designed independently. An analysis of the improved EID approach explains the mechanism of disturbance rejection. The simulation and experimental results of position control of a ball-and-beam system demonstrate the validity of the method. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) is an emerging technology that can realize electric power transmission over certain distances without physical contact, offering significant benefits to modern automation systems, medical applications, consumer electronics, etc. This paper provides a comprehensive review of existing compensation topologies for the loosely coupled transformer. Compensation topologies are reviewed and evaluated based on their basic and advanced functions. Individual passive resonant networks used to achieve constant (load-independent) voltage or current output are analyzed and summarized. Popular WPT compensation topologies are given as application examples, which can be regarded as the combination of multiple blocks of resonant networks. Analyses of the input zero phase angle and soft switching are conducted as well. This paper also discusses the compensation requirements for achieving the maximum efficiency according to different WPT application areas. [ABSTRACT FROM PUBLISHER]

Many of today’s stretchable interconnection technologies make extensive use of meandered interconnections, these provide 2-D in-plane springs capable of extending and compressing as the need arises. While a significant quantity of research work exists on these interconnects, few generic methodologies exist to design circuits in a consistent manner. This shortfall leads to questionable design practices, which can negatively affect reliability and performance. Presented within this paper is a method to quickly determine which meander fits within a given area based on common geometric boundary conditions. [ABSTRACT FROM AUTHOR]

Different from conventional wired line connections, industrial control through wireless transmission is widely regarded as a promising solution due to its reduced cost, increased long-term reliability, and enhanced reliability. However, mission-critical applications impose stringent quality of service (QoS) requirements that entail ultra-reliability low-latency communications (URLLC). The primary feature of URLLC is that the blocklength of channel codes is short, and the conventional Shannon’s Capacity is not applicable. In this paper, we consider the URLLC in a factory automation (FA) scenario. Due to densely deployed equipment in FA, wireless signal are easily blocked by the obstacles. To address this issue, we propose to deploy intelligent reflecting surface (IRS) to create an alternative transmission link, which can enhance the transmission reliability. In this paper, we focus on the performance analysis for IRS-aided URLLC-enabled communications in a FA scenario. Both the average data rate (ADR) and the average decoding error probability (ADEP) are derived under finite channel blocklength for seven cases: 1) Rayleigh fading channel; 2) With direct channel link; 3) Nakagami-m fading channel; 4) Imperfect phase alignment; 5) Multiple-IRS case; 6) Rician fading channel; 7) Correlated channels. Extensive numerical results are provided to verify the accuracy of our derived results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a novel collision probability-aware human-machine cooperative planning and tracking method for enhancing safety of automated vehicles. Firstly, a long-term trajectory prediction is obtained by using Gaussian mixture models with vehicle historical data. After that, a novel risk assessment system based on the dynamic potential field (DPF) and the fuzzy inference system (FIS) is proposed to evaluate the risk level of the human driver's behaviors. Based on the assessed human driving risk, the human-machine cooperation is activated adaptively during the trajectory planning. A novel human-machine cooperative trajectory planning algorithm, named as HM- $p$ RRT, is proposed and used to incorporate the driver's intent and automation's corrective actions during trajectory planning. Testing results show that the proposed HM- $p$ RRT algorithm is able to simultaneously mitigate collision and provide a safe trajectory, effectively ensuring the safety of the vehicle and reducing conflicts during human-machine interactions. [ABSTRACT FROM AUTHOR]

The authors comment on the importance of the periodical relative to the study of machine intelligence. They pointed that the submission rate for articles to be featured has doubled, with more than 900 contributions expected for 2006. They also praised the contributions of associate editors and reviewers in screening articles to be featured in the periodical.

This paper focuses on the fault-tolerant control problem for an Internet-based three-tank system in the presence of possible sensor bias faults. The Internet-based three-tank system is an experimental setup that can be regarded as a typical networked system for evaluating networked fault-diagnosis and fault-tolerant control methods. Packet dropout phenomenon in the sensor-to-controller link is considered in this paper, and the fault type we deal with is chosen as the sensor bias fault. Fault-diagnosis unit is designed toward an auxiliary system. Sensor bias faults can be detected by comparing the residual signal generated by the fault detection filter and a prescribed threshold. After that, the fault can be isolated by using the residual analysis approach. Once the fault is isolated, it can be estimated iteratively in the least-squares sense. A fault accommodation method is proposed, and a fault-tolerant control strategy is achieved based on the fault information provided by the fault-diagnosis unit. The approach brought forward in this paper is demonstrated via an experimental study on the practical Internet-based three-tank system. Results show the effectiveness and the applicability of the proposed techniques. [ABSTRACT FROM PUBLISHER]

The article presents views and insights of the author concerning the implementation of more and more complex control systems for industrial applications. According to the author, the fast progress of very large scale integration technology and electronic design automation (EDA) techniques in recent years has created the opportunity for the development of complex and compact high-performance controllers for industrial systems.

Validation and debug challenges of system-on-chips (SoCs) are getting increasingly difficult. As we reach the limits of Dennard scaling, efforts to improve system performance and energy efficiency have resulted in the integration of a wide variety of complex hardware accelerators in SoCs. Hence, it is essential to address the validation and debug of hardware accelerators. High-level synthesis (HLS) is a promising technique to rapidly create customized hardware accelerators. In this paper, we present the hybrid quick error detection (H-QED) approach that overcomes validation and debug challenges for hardware accelerators by leveraging HLS techniques in both the presilicon and post-silicon stages. H-QED improves error detection latencies (time elapsed from when a bug is activated to when it is detected) by 2–5 orders of magnitude with one cycle latencies in presilicon scenarios and bug coverage threefold higher compared to traditional validation techniques. H-QED also uncovered previously unknown bugs in the CHStone benchmark suite, which is widely used by the HLS community. H-QED incurs an 8% accelerator area overhead with negligible silicon performance impact for post-silicon stage, and we also introduce techniques to minimize any possible intrusiveness introduced by H-QED. [ABSTRACT FROM AUTHOR]

In general, there are two kinds of cooperative driving strategies, planning-based strategy, and ad hoc negotiation-based strategy, for connected and automated vehicles merging problems. The planning-based strategy aims to find the globally optimal passing order, but it is time-consuming when the number of considered vehicles is large. In contrast, the ad hoc negotiation-based strategy runs fast, but it always finds a locally optimal solution. In this paper, we propose a grouping-based cooperative driving strategy to make a good tradeoff between computation time and coordination performance. The key idea is to fix the passing orders for some vehicles whose inter-vehicle headways are small enough (e.g., smaller than the pre-selected grouping threshold). From the viewpoint of optimization, this method reduces the size of the solution space. Then, two analyses are given to explain why this kind of strategy is good and how to determine suitable values for the strategy parameters. A series of simulation experiments are carried out to validate that the proposed strategy can yield a satisfied coordination performance with less computation time and is promising to be used in practice. [ABSTRACT FROM AUTHOR]

Objective: Croup, a respiratory tract infection common in children, causes an inflammation of the upper airway restricting normal breathing and producing cough sounds typically described as seallike “barking cough.” Physicians use the existence of barking cough as the defining characteristic of croup. This paper aims to develop automated cough sound analysis methods to objectively diagnose croup. Methods: In automating croup diagnosis, we propose the use of mathematical features inspired by the human auditory system. In particular, we utilize the cochleagram for feature extraction, a time-frequency representation where the frequency components are based on the frequency selectivity property of the human cochlea. Speech and cough share some similarities in the generation process and physiological wetware used. As such, we also propose the use of mel-frequency cepstral coefficients which has been shown to capture the relevant aspects of the short-term power spectrum of speech signals. Feature combination and backward sequential feature selection are also experimented with. Experimentation is performed on cough sound recordings from patients presenting various clinically diagnosed respiratory tract infections divided into croup and non-croup. The dataset is divided into training and test sets of 364 and 115 patients, respectively, with automatically segmented cough sound segments. Results: Croup and non-croup patient classification on the test dataset with the proposed methods achieve a sensitivity and specificity of 92.31% and 85.29%, respectively. Conclusion: Experimental results show the significant improvement in automatic croup diagnosis against earlier methods. Significance: This paper has the potential to automate croup diagnosis based solely on cough sound analysis. [ABSTRACT FROM AUTHOR]

Automated material handling systems (AMHSs) used in semiconductor fabrication are sophisticated and integrated control systems that transfer materials from one machine to another within a manufacturing facility via hundreds of vehicles. Vehicular congestion in AMHSs causes significant production inefficiency. In this paper, we demonstrate the reasons for and classification of congestion, and suggest congestion metrics for material handling systems. We develop and implement a congestion monitoring system (CMS) based on the proposed metrics at an actual manufacturing site. We provide practical case studies on three applications to address the effectiveness of CMS: 1) congestion monitoring; 2) redistribution of routing; and 3) enhancing a routing algorithm. Simulation results demonstrated that the proposed routing algorithm decreased the average delivery time by 12.41% in heavy congestion. The shorter average delivery time reduces the loss in production by at least 1%. [ABSTRACT FROM AUTHOR]

Information and operational technologies merge into the so-called industrial Internet of Things, which is one of the basic pillars of the Industry 4.0 paradigm. Roughly speaking, yet-to-come services will be offered in the automation scenario by industrial devices having an internet connection for sharing data in the cloud. Currently, most efforts are in the development of protocols able to ensure horizontal interoperability among heterogeneous applications. Consequently, poor attention is devoted to time-related performance. In this paper, a new, full software, platform-independent approach is proposed for experimentally evaluating the delay in transferring information across local and intercontinental routes by applications leveraging on messaging middleware. The application is realized using the node-RED web-based framework, due to its availability on different platforms; the widely accepted message queue telemetry transport protocol has been chosen thanks to its low overhead and complexity. For sake of completeness, five different, private and public, brokers are used. The adopted industrial-grade hardware, complemented by global positioning system time reference, permits an overall synchronization and timestamping accuracy of a few milliseconds. The vast measurement campaign highlighted that, generally, quality of service (QoS) type 1 offers low end-to-end delay (average value less than 0.5 s) with reduced variability (0.1 s). However, the maximum end-to-end one-way delay ranges from 1 s for QoS 0 to less than 1.5 s for fully acknowledged QoS 2. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sliding mode control (SMC) via finite-time stabilization (FTS) for a class of conic-type nonlinear semi-Markovian jumping systems (SMJSs). Comparing with the classical Markovian jumping systems, the transition rates of SMJSs are related to the random sojourn-time $g$. Based on this, a suitable SMC law for driving the state trajectories to the designed sliding surface within a finite-time interval is given. Then, the FTS over reaching phase and sliding motion phase is further proved to guarantee the FTS of the whole SMJSs. Finally, the effectiveness of the proposed method is demonstrated by a time-delayed Chua’s circuit simulation. [ABSTRACT FROM AUTHOR]

Being important information of both network conditions and energy trading, distribution locational marginal prices (DLMPs) are greatly useful for distribution network (DN) management. The goal of this paper is to develop a market mechanism that motivates price-making agents to trade active and reactive power at DLMPs. According to the optimal power flow problem based on second-order cone (SOC) relaxation, we first design the market rules that allow agents to strategically submit proposals of price and power generation/consumption. The market rules induce a noncooperative game between the DN operator and distributed generators. We prove that DLMP pricing can be implemented at any generalized Nash equilibrium (GNE) of the game. We also show that economic properties of strong budget balance, individual rationality, and system cost minimization can be achieved at any GNE. A decentralized algorithm is developed to reach a GNE of the game. Further, based on the convex-concave procedure, an extension of the market mechanism is proposed to cope with the situations that SOC relaxation is inexact. In simulation, the proposed market mechanism is compared with other game-theoretic models, and the economic properties are verified. [ABSTRACT FROM AUTHOR]

This paper describes a simple approach for model-based template matching, which is robust to undergo rotation and scaling variations. An efficient image warping scheme spiral aggregation image (SAI), which has been utilized in this paper, provides a method for generating projection profiles for matching. In addition, it determines the rotation angle and is invariant to scale changes. The proposed spiral projection algorithm (SPA) for template matching enables the simultaneous representation for each value of projection profile, obtained through SAI, and provides structural and statistical information on the template. The experimental evaluation shows that the proposed SPA achieves very attractive results for template matching in the industrial automation application. [ABSTRACT FROM PUBLISHER]

In this paper, a sensorless control of an electromagnetic valve actuator for automotive applications is presented. Based on a nonlinear model, a switching esti mator combined with a two-stage observer structure is proposed. The presented structure is basically a high-gain observer (HGO) to reduce the effects of the uncertainties on the electromagnetic valve actuator model and unmeasurable external disturbances coming from the burning phase of the engine and acting against the actuator movement. The proposed sliding-mode observer has the capability of guaranteeing zero average estimation error in finite time, even in the presence of model uncertainties and bounded disturbances. Considerations on constructive aspects concerning observability are made. Two constructive propositions are proven in this paper to realize the observer. A general comparative analysis is proposed, considering other contributions which use Kalman filters, in which aspects of optimality, robustness, and chattering problems are discussed. In particular, an analysis of the computational effort is also reported. Laboratory experiments of the controlled system, which demonstrate promising behavior, are presented and discussed for exhaust valves of an engine. [ABSTRACT FROM PUBLISHER]

This paper studies the $ {H}_{ {\infty }}$ sliding mode control (SMC) problem for a class of discrete-time conic-type nonlinear systems with time-delays and uncertainties. The nonlinear terms satisfy the conic-type constraint condition that lies in a know hyper-sphere with an uncertain center. By choosing a proper Lyapunov candidate, sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics while achieving a prescribed $ {H}_{ {\infty }}$ disturbance attenuation level and finally converted into a minimization problem. The controller is constructed to guarantee the discrete-time reach condition and maintain the states on the prespecified sliding surface. A simulation result and a practical example related to the Chua’s circuit are given at last to show the validity of our SMC strategy. [ABSTRACT FROM AUTHOR]

There are few results concerning consensus of multiagent systems (MASs) based on partial differential equations (PDEs), and the problem of how to act boundary control based on distributed measurement on spatial boundary points of MASs has not been solved. This paper addresses boundary control based on distributed measurement for output consensus of leader-following directed MASs modeled by parabolic PDEs. First, a boundary controller acting on spatial boundary points is designed by considering the delivered information produced by agents communicating with neighborhoods. Without considering input constraint, the Lyapunov’s direct method is used to obtain a sufficient condition on the existence of the boundary controller to achieve output consensus. The condition is expressed as a form of the feasibility of LMIs. After that, the whole input constraint for MASs is given. And then, one more condition on control gains is obtained to ensure the existence of the boundary controller with input constraint. Finally, one numerical example with two cases illustrates the theoretical analysis results. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented that focuses on reference for solutions that leverage techniques and insights from the domains of artificial intelligence, internet of things, edge computing, and big data to address security, reliability, privacy, and quality challenges in industrial applications.

Efficient water management is a major concern in many cropping systems in semiarid and arid areas. Distributed in-field sensor-based irrigation systems offer a potential solution to support site-specific irrigation management that allows producers to maximize their productivity while saving water. This paper describes details of the design and instrumentation of variable rate irrigation, a wireless sensor network, and software for real-time in-field sensing and control of a site~specific precision linear-move irrigation system. Field conditions were site-specifically monitored by six in-field sensor stations distributed across the field based on a soil property map, and periodically sampled and wirelessly transmitted to a base station. An irrigation machine was converted to be electronically controlled by a programming logic controller that updates georeferenced location of sprinklers from a differential Global Positioning System (GPS) and wirelessly communicates with a computer at the base station. Communication signals from the sensor network and irrigation controller to the base station were successfully interfaced using low-cost Bluetooth wireless radio communication. Graphic user interface-based software developed in this paper offered stable remote access to field conditions and real-time control and monitoring of the variable-rate irrigation controller. [ABSTRACT FROM AUTHOR]

This paper analyzes a disturbance observer with a focus on parameter variations. The parameter variations are the inertia variation and the variation of torque coefficient. Conventionally, their nominal values are designed not as control parameters but the same values as the actual ones. However, disturbance observer is able to include the effect of phase compensation by properly selecting the nominal model parameters. In this paper, these nominal model parameters are actively designed to achieve the phase compensation. This paper proposes the design method of observer to achieve phase compensation based on disturbance observer. Compared with implementing phase compensator, the control system is simple and easy to design. The selection of these parameters has some restriction. When the nominal model parameters are much separated from the actual ones, the stability of the control system deteriorates. This paper focuses on the inertia variation and neglects the variation of torque coefficient. Furthermore, the stability of position and force control systems is analyzed. The validity of the proposed design method and the effect of phase compensation are verified by some experimental results. [ABSTRACT FROM AUTHOR]

In this paper, simplified necessary and sufficient conditions are derived for H∞ static output feedback (OPFB). This paper also presents a numerically efficient solution algorithm to solve the coupled design equations for the bounded L2 gain static OPFB controller. No initial stabilizing OPFB gain is needed. The effectiveness of the proposed method is demonstrated through implementation on an industrial-type mass spring damper system. [ABSTRACT FROM AUTHOR]

In this paper, we study the difference between two major strategies of cooperative driving at nonsignalized intersections: namely the “ad hoc negotiation-based” strategy and the “planning-based” strategy. The fundamental divide of these two strategies lies in how to determine the passing order of vehicles at intersections. The “ad hoc negotiation-based” strategy makes vehicles roughly follow first-come-first-served order but allows some adjustments. This leads to a local optimal solution in many situations. The “planning-based” strategy aims to find a global optimal passing order of vehicles. However, constrained by the planning complexity and time requirement, we often stop at a local optimal solution, too. We carry out a series of simulations to compare the solutions found by two strategies, under different traffic scenarios. Results indicate the performance of a strategy mainly depends on the passing order of vehicles that it finds. Although there exist several trajectory planning algorithms associating with the solving process of passing orders, their differences are negligible. Moreover, if the traffic demand is very low, the performance difference between two strategies is small. When the traffic demand becomes high, the “planning-based” strategy yields significantly better performance since it finds better passing orders. These findings are important to cooperative driving study. [ABSTRACT FROM PUBLISHER]

Motor control assets are foundational elements in many industrial operations. In the mining industry, these assets primarily consist of motor control centers and drives, which are available with a comprehensive assortment of control and monitoring devices. Various intelligent electronic devices (IEDs) are now used to prevent machine damage and downtime. As motor control devices have advanced in technology, so too have the IEDs that protect them. These advances have resulted in new standards, such as the International Electrotechnical Commission (IEC) 61850, that have embedded intelligence and a standard set of communication schemes by which IEDs can share information in a peer-to-peer or one-to-many fashion. This paper discusses the merits and steps involved with interfacing IEDs to a mining process control network via the use of the IEC 61850 standard. [ABSTRACT FROM PUBLISHER]

Cyber-physical systems (CPSs) are becoming common in the industrial automation domain. In industrial CPS, distributed programmable logic controllers collaborate to control manufacturing plants. Design and analysis of such systems require a system model that covers control, computation, and communication with physical plant dynamics. This paper focuses on execution semantics for industrial CPS with the aim of providing a deterministic and platform-independent execution environment. A discrete-event-based execution semantics augmented with timestamp mechanism is proposed for IEC 61499 to provide deterministic behavior and guarantee compliance with real-time constraints for industrial CPS. The timestamped discrete-event-based execution semantics is implemented in an IEC 61499 runtime with service-enabled features. A case study of building automation system is used to prove the proposed semantics. [ABSTRACT FROM AUTHOR]

A conventional power grid is criticized by its poor capability of power usage management, especially in handling dynamically varying power demands over time. The concept of smart grid has been introduced to mitigate this problem by satisfying not only real-time power demands, but also by restricting power usage within the capacity. Its consistent outperformance and new perspective in computer intelligence to control the grid for autonomous power consumption has been gradually replacing the conventional power grid. However, even in smart grid, providing high satisfaction to users often leads smart grid operator (SGO) to loss and vice versa. In this paper, we develop an optimal dynamic pricing mechanism for trading-off (ODPT), for SGOs that tradeoff between user utility and operator profit in smart grid systems. It allows the operator to purchase power from multiple energy producers and to set selling price to users dynamically following the demand-supply theory of economics. It also exploits an artificial neural network model to more accurately predict the power usage. The simulation results, carried out on a commercially available optimization modeling tool using practical power usage data, prove the effectiveness of the proposed ODPT in increasing the operator profit while satisfying user demands. [ABSTRACT FROM AUTHOR]

This paper is devoted to the industrial practices and theoretical approaches for detection and isolation of quality-related multiple faults in large-scale processes. In contrast to the previous schemes, the main innovations are as follows: 1) it is the first time a hierarchical detection and isolation framework for quality-related multiple faults in large-scale processes is developed; 2) a combination method of adaptive kernel canonical variable analysis and Bayesian fusion for real-time and hierarchical detection of varying and unknown quality-related multiple faults is presented; and 3) a robust sparse exponential discriminant analysis algorithm for accurate isolation of multimode quality-related multiple faults is proposed. Finally, the whole framework is applied to a typical large-scale process, i.e., hot strip mill process, where the performance and effectiveness are further demonstrated from real industrial data. [ABSTRACT FROM AUTHOR]