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This article proposes a leader–follower cooperative salvo guidance strategy to intercept nonmaneuvering targets by exploiting the advantages of supertwisting sliding mode control. An improved estimate of time-to-go, that does not assume interceptor's small heading angle, is used in the guidance design. This allows the guidance strategy to remain effective even for large initial heading of the interceptor. Under the action of supertwisting control, the error in impact time settles precisely to zero in finite time. The proposed guidance strategy provides robustness against uncertainties and a smooth control signal, along with finite-time convergence of error. The guidance performance has been shown for one-to-one engagement, and in a cooperative framework, to achieve a salvo in a predetermined time. Numerical simulations are presented for various engagement scenarios to aid the analysis, and illustrate the efficacy of the proposed guidance scheme, even under noisy environment. [ABSTRACT FROM AUTHOR]

With advancements in mobile robot olfaction, networked multiagent systems (MASs) are used in odor source localization (OSL). These MASs are often equipped with small microprocessors that have limited computing capabilities, and they usually operate in a bandwidth and energy-constrained environment. The exigent need for a faster localizing algorithm under communication and computational resource constraints invites many design challenges. In this paper, we have designed a two-level hierarchical cooperative control strategy for heterogeneous nonlinear MASs for OSL. The agents are forced toward consensus expeditiously once the information on the whereabouts of the source is attained. The synthesis of the controller occurs in a hierarchical manner—obtaining a group decision, followed by resource-efficient robust control. Odor concentration and wind information have been used in a group decision-making layer to predict a probable location of the source as a tracking reference. This reference is then fed to the control layer that is synthesized using event-triggered sliding-mode control (SMC). The advantage of using event-triggered control scheduling in conjunction with the SMC is rooted in retaining the robustness of the SMC while lowering the resource utilization burden. Numerical simulations confirm the efficiency of the scheme put forth. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of the task of localizing an unknown source of an odor by heterogeneous multiagent systems. A hierarchical cooperative control strategy has been proposed as a potential candidate to solve the problem. The agents are driven into consensus as soon as the information about the location of source is acquired. The controller has been designed in a hierarchical manner of group decision making, agent path planning, and robust control. In group decision making, the particle swarm optimization algorithm has been used along with the information of the movement of odor molecules to predict the odor source location. Next, a trajectory has been mapped using this predicted location of source, and the information is passed to the control layer. A variable structure control has been used in the control layer due to its inherent robustness and disturbance rejection capabilities. Cases of movement of agents toward the source under consensus and parallel formation have been discussed. The efficacy of the proposed scheme has been confirmed by simulations. [ABSTRACT FROM AUTHOR]

Mechanism design for incentivizing strategic agents to maximize their sum of utilities (SoU) is a well-studied problem in the context of resource allocation in networks. There are, however, a number of network resource allocation problems of interest where a designer may have a different objective than maximization of the SoU. The obvious reason for seeking a different objective is that this notion of efficiency does not account for fairness of allocation. A second, more subtle, reason for demanding fairer allocation is that it indirectly implies less variation in taxes paid by agents. This is desirable in a situation where implicit individual agent budgetary constraints make payment of large taxes unrealistic. In this paper, we study a family of social utilities that provide fair allocation (with SoU being subsumed as an extreme case) and derive conditions under which Bayesian and dominant strategy implementation is possible. Furthermore, it is shown how a modification of the above-mentioned mechanism by adding just one message per agent can guarantee full Bayesian implementation, i.e., no extraneous equilibria. We consider the problem of demand-side management in smart grids as a specific motivating application, and through numerical analysis, it is demonstrated that in this application, the proposed method can result in significant gains in fairness of allocation and a reduction in tax variation among agents. [ABSTRACT FROM AUTHOR]