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The robust formation tracking problems (FTPs) are investigated for noncooperative heterogeneous multiagent systems (MASs). The parameters and state dimensions of each agent in the MASs can be heterogeneous. The leader is noncooperative and has an unknown external input. The followers are affected by uncertainties and disturbances. A distributed extended state observer is designed to estimate the leader’s state and the unknown external input. Then a robust formation tracking control method is proposed. It turns out that the output formation tracking error can reduce to any size neighborhood near the origin by selecting appropriate parameters. Finally, the effectiveness of the proposed observer and controller is demonstrated by a numerical simulation example and a hardware-in-the-loop (HITL) simulation example.

This article studies a zero-sum reach-avoid game in the 2-D plane with one defender and two cooperative attackers. The attackers try to enter the target region protected by the defender who tries to capture both of them. This work aims to obtain the value function and equilibrium strategies, for which the analysis of singular surfaces is needed. To this end, we investigate the game problem in two steps. First, a constrained game scenario is considered in which the defender needs to capture the attackers in a predefined order. The value function is constructed using geometric tools and proved using the viscosity solution method. The attackers can cooperate with each other by adopting the equilibrium strategies corresponding to the value function. Second, on the basis of the solution to the first game scenario, we analyze the general game problem in which there is no capture order restriction for the defender. The singular surfaces are discussed and the local properties of the value function in the vicinity of the singular surfaces are given. It is shown that the defender can perform better than to capture the attackers in any predefined order. Moreover, the construction of singular surfaces is illustrated with numerical results.

This study addresses the task assignment problem with robot coalitions, as encountered in practical scenarios, such as multiplayer reach-avoid games. Unlike the classical assignment problem where a single robot performs each task, the problem considered here involves tasks that require execution by a robot coalition consisting of two robots. This task assignment problem is a special instance of 3-set packing problem, which is known to be nondeterministic polynomial time (NP)-hard. We introduce the concept of $\epsilon$-coalition-competitive equilibrium ($\epsilon$-CCE) to characterize a kind of approximate solution that offers guaranteed performance. A distributed auction algorithm is developed to find an $\epsilon$-CCE within a finite number of iterations. In addition, several enhancements have been implemented to adapt the auction algorithm for practical applications where the task assignment problem may vary over time. Numerical simulations demonstrate that the distributed algorithm achieves satisfactory approximation quality.

This article studies a planar Homicidal Chauffeur reach-avoid differential game, where the pursuer is a Dubins car and the evader has simple motion. The pursuer aims to protect a goal region from the evader. The game is solved in an analytical approach instead of solving Hamilton–Jacobi–Isaacs equations numerically. First, an evasion region is introduced, based on which a pursuit strategy guaranteeing the winning of a simple-motion pursuer under specific conditions is proposed. Motivated by the simple-motion pursuer, a strategy for a Dubins-car pursuer is proposed when the pursuer–evader configuration satisfies separation condition (SC) and interception orientation (IO). The necessary and sufficient condition on capture radius, minimum turning radius, and speed ratio to guarantee the pursuit winning is derived. When the IO is deviated (Non-IO), a heading adjustment pursuit strategy is proposed, and the condition to achieve IO within a finite time is given. Based on it, a two-step pursuit strategy is proposed for the SC and Non-IO case. A nonconvex optimization problem is introduced to give a condition guaranteeing the winning of the pursuer. A polynomial equation gives a lower bound of the nonconvex problem, providing a sufficient and efficient pursuit winning condition. Finally, we extend to multiplayer games by collecting pairwise outcomes for pursuer–evader matchings. Simulations are provided to illustrate the theoretical results.

This article considers a planar multiple-pursuer single-evader reach-avoid game played in a constant flow field. Such a game problem arises in practical applications, such as maritime escort, aircraft confrontation in airflow fields, and defense of moving targets. The dominance boundary, which serves as an analogy to the Apollonius circle and the Cartesian oval, is investigated. The existence of semipermeable surfaces in the game is shown. Under reasonable assumptions, there exists a semipermeable surface, which is part of the barrier surface separating the winning regions for the evader and pursuers. The winning strategies are designed for both sides of players in their corresponding winning regions. It is also shown that at most two pursuers are necessary for successful protection, as in the situation where there is no flow field. Finally, numerical results are given to illustrate the conclusions.

ABSTRACTMatrix metalloproteinases (MMPs) are important regulators of the extracellular matrix (ECM) and are involved in many stages of cellular growth and development. An imbalance of MMP expression is also the basis of many diseases, including eye diseases, such as diabetic retinopathy (DR), glaucoma, dry eye, corneal ulcer, keratoconus. This paper describes the role of MMPs in the glaucoma and their role in the glaucomatous trabecular meshwork (TM), aqueous outflow channel, retina, and optic nerve (ON). This review also summarizes several treatments for glaucoma that target MMPs imbalance and suggests that MMPs may represent a viable therapeutic target for glaucoma.

ABSTRACTGlaucoma is a group of diseases characterized by distinctive visual field defect and optic nerve atrophy usually associated with elevated intraocular pressure (IOP). It is one of the most serious visual disorders and the leading cause of irreversible blindness worldwide. As a multifactorial disease, the pathogenesis of glaucoma is complicated and has been far from fully understood, where vascular factors are recognized to play an important role in its development and progression of glaucoma. Empirical researches have shown that parapapillary choroidal microvasculature dropout (CMvD) is closely associated with the impairment of optic nerve head (ONH) perfusion, probably accelerating the progression of glaucoma. Accordingly, it is necessary to explore the details regarding the relationship between CMvD and glaucoma progress, hoping to enhance the understanding of pathogenesis of glaucoma. In this review, we aimed to establish comprehensive understanding of the relationship between CMvD and glaucoma with generally going through relevant up-to-date literatures. Among the events that are closely associated with CMvD, we summarized the ones specifically involved in the term of glaucomatous pathological process, including thickness of retinal nerve fiber layer (RNFL) thickness, lamina cribrosa (LC) morphology, cricumpapillary vessel density (cpVD) and visual function such as visual field (VF) defect as well as the prognosis of glaucoma. Although researchers have made great advances, there are still many issues need to be addressed particularly concerning the pathogenic role of CMvD in glaucoma development and its clinical implications with respect to glaucoma prognosis.

Formation control problems for high-order linear time-invariant multiagent systems with time delays are investigated. First, a general time-varying formation control protocol is proposed. Then, based on consensus approaches, necessary and sufficient conditions for multiagent systems to achieve a given time-varying formation are presented. An explicit expression of the time-varying formation reference function is also given. It is shown that the motion modes of the formation reference can be specified. Furthermore, necessary and sufficient conditions for formation feasibility are proposed. An approach to expand the feasible formation set and an algorithm to design the protocol for multiagent systems to achieve time-varying formations are provided, respectively. Finally, numerical simulations are presented to demonstrate theoretical results.

Based on the two-dimensional (2D) system theory, an integrated predictive iterative learning control (2D-IPILC) strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control (ILC) and model predictive control (MPC) is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By minimizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type (P-type) ILC despite the model error and disturbances.

Fine-grained allocation of compute resources, in terms of configurable clock speed of virtual machines, is essential for processing efficiency and resource utilization of data streaming applications. For a data streaming application, its processing speed is expected to approach the allocated bandwidth as much as possible. Automatic control technology is a feasible solution, but the plant model is hard to be derived. In relation to the model free characteristic, a fuzzy logic controller is designed with several simple yet robust rules. Performance of this controller is verified to out-perform classic controllers in response rapidness and less oscillation. An empirical formula on tuning an essential parameter is obtained to achieve better performance.

Abstract: Data streaming applications, usually composed of sequential/parallel data processing tasks organized as a workflow, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to the high volumes of data and relatively limited storage capability, resource allocation and data streaming have to be storage aware. Also to improve system performance, the data streaming and processing have to be concurrent. This study used a genetic algorithm (GA) for workflow scheduling, using on-line measurements and predictions with gray model (GM). On-demand data streaming is used to avoid data overflow through repertory strategies. Tests show that tasks with on-demand data streaming must be balanced to improve overall performance, to avoid system bottlenecks and backlogs of intermediate data, and to increase data throughput for the data processing workflows as a whole. [Copyright &y& Elsevier]

Bicycles and similar two-wheeled vehicles are a scientifically interesting category of means of transportation, whose simultaneous localization and mapping problem, in contrast to other ground vehicles, has yet to be examined in depth and fully resolved. In this article, we introduce for the first time a comprehensive theoretical framework for the application of simultaneous localization and mapping specifically for autonomous bicycles and akin vehicles, based on the kinematics and dynamics models of the bicycle and the specific effects they have on the motion/odometry and measurement models that are essential for the solution of the simultaneous localization and mapping problem. In addition, we present our laboratory’s first autonomous bicycle platform and its functional sensor system and sensor rotation pattern, specifically adjusted to the special characteristics of bicycles. Moreover, we investigate the effect of the bicycle frame roll, the main uncertainty factor of the bicycle simultaneous localization and mapping problem, on the overall simultaneous localization and mapping performance. The experimental results performed on our bicycle platform verify the potency of our proposed modeling and simultaneous localization and mapping application framework and provide further insight on future improvements for the two-wheeled vehicle simultaneous localization and mapping problem.