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This article proposes a guidance strategy that enables the interceptor to control its impact time against stationary targets, while also meeting the field-of-view (FOV) constraints of the on-board seeker. The guidance strategy, so designed, always keeps the target within its FOV using its seeker. A barrier Lyapunov function is used to meet the FOV constraints, and an approximate expression for the interceptor's lead angle is obtained analytically. This facilitates the computation, as well as control, of impact time. The proposed guidance consists of two stages, with the former stage being deviated pursuit, while during the latter stage, the deviation angle or lead angle decreases to zero. This, in turn, ensures a zero terminal lateral acceleration. Furthermore, through a cooperative selection of tuning parameters, simultaneous interception of the target by multiple interceptors (also called salvo) can be achieved. Simulations, that are run for different engagement scenarios and with varying tuning parameters, vindicate the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this article, a nonlinear three-dimensional guidance strategy for multiple identical constant speed interceptors is proposed to capture a stationary target simultaneously. To design this proposed guidance strategy, a proportional navigation based time-to-go estimate, without any small angle assumption, is used. Based on the maximum value of time-to-go estimates of all interceptors, the range error for each interceptors is computed. Sufficiency conditions for simultaneous capture are satisfied by ensuring the range errors and their rates converge to zero for all interceptors. The proposed guidance strategy employs Lyapunov and sliding-mode control-based techniques to achieve these sufficiency conditions. Simulation studies demonstrate that this proposed strategy performs satisfactorily for various geometric engagements and in the presence of a first-order autopilot. [ABSTRACT FROM AUTHOR]

This article proposes sliding-mode-control-based guidance strategies for a team comprised of aircraft and a defending interceptor against an attacker. The proposed guidance strategies are based on the line-of-sight guidance concept. Problems such as performance degradation under large heading angle errors, arising from linearization of engagement dynamics, are circumvented due to the nonlinear framework considered here. We show that knowledge of the bound on attacker acceleration suffices to ensure interception of an attacking interceptor. Cooperative strategies are derived for the aircraft–defender team, corresponding to cost functions based on the $\ell _p$ norm, using static optimization at each time instant. Simulations validate the efficacy of the proposed strategies. [ABSTRACT FROM AUTHOR]

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]

This paper presents impact angle guidance based on finite-horizon robust optimal control. This approach, a fusion of newly proposed finite-time state-dependent Riccati equation and integral sliding-mode-control, solves finite-horizon tracking problem for input-affine nonlinear systems with specified terminal conditions. It also ensures robustness against external disturbances and uncertainties from beginning. The technique for ensuring specified final-time involves deriving closed-form control expression in terms of approximate solution of differential Riccati equation, which further reduces to solutions of algebraic Riccati and Lyapunov equations. This yields computationally efficient algorithm. To alleviate chattering, the supertwisting algorithm is incorporated with the proposed technique. Guidance strategy is derived after converting impact angle problem to tracking one using the proposed algorithm. Efficacy of the proposed guidance is vindicated for various engagement geometries, and also compared with an existing guidance strategy. [ABSTRACT FROM AUTHOR]

A cooperative salvo guidance strategy using fixed finite-time consensus is proposed here. The consensus algorithm is based on sliding mode control. The cooperative salvo attack problem is transformed to a consensus problem over a cycle digraph. This aids in designing a guidance strategy through selection of heterogeneous gains. The proposed strategy guarantees convergence to a common impact time for all the interceptors, within a fixed time, from a wide range of initial heading angles. Subsequently, the guidance strategy is extended to cooperatively intercept a constant velocity target. The efficacy of the proposed algorithm is vindicated through simulations on both stationary and constant velocity targets. Numerical simulations are also performed on realistic missile models that account for aerodynamic parameter variations, yielding satisfactory performance. [ABSTRACT FROM AUTHOR]

In this paper, sliding mode control-based impact time guidance laws are proposed. Even for large heading angle errors and negative initial closing speeds, the desired impact time is achieved by enforcing a sliding mode on a switching surface designed by using the concepts of collision course and estimated time-to-go. Unlike existing guidance laws, the proposed guidance strategy achieves impact time successfully even when the estimated interception time is greater than the desired impact time. Simulation results are also presented. [ABSTRACT FROM AUTHOR]

The communication infrastructure of a complex multicore system-on-a-chip is getting an increasing fraction of the overall chip area. According to the International Technology Roadmap for Semiconductors, killer defect density does not decrease over successive technology generations. For this reason, the probability that a manufacturing defect affects the communication system is predicted to increase. In this paper, we deal with manufacturing defects which affect the links in a network-on-chip-based interconnection system. The goal of this paper is to show that by using effective routing functions, supported by appropriate selection policies and with a limited amount of extra logic in the router, it is easy to exploit partially faulty links to improve the performance of the system. We show that, instead of discarding partially faulty links, they can be used at reduced capacity to improve the distribution of the traffic over the network, yielding performance and power improvements. We couple an application-specific routing function with a set of selection policies which are aware of link fault distribution and evaluate them on both synthetic traffic and a real complex multimedia application. We also present an implementation of the router, augmented with the extra logic, to support both the proposed selection functions and the transmission of messages over partially faulty links. We analyze the router in terms of silicon area, timing, and power dissipation. [ABSTRACT FROM AUTHOR]

Abstract-In this paper,we present a methodology to develop efficient and deadlock-free routing algorithms for Network-on-Chip (NoC) platforms that are specialized for an application or a set of concurrent applications. The proposed methodology,called the Application- Specific Routing Algorithm (APSRA),exploits the application-specific information regarding pairs of cores that communicate and other pairs that never communicate in the NoC platform to maximize communication adaptivity and performance. The methodology also exploits the known information regarding concurrency/nonconcurrency of communication transactions among cores for the same purpose. The methodology does not require virtual channels to guarantee deadlock freedom. We demonstrate,through analysis of adaptivity and simulation-based evaluation of latency and throughput,that algorithms produced by the proposed methodology give significantly higher performance as compared to other deadlock-free algorithms for both homogeneous and heterogeneous 2D mesh topology NoC systems. Since the APSRA methodology is topology agnostic,the most appropriate general implementation of the routing function within the router is using a table. A table-based implementation of the router is costlier as compared to an algorithm-based implementation. We also propose a technique to compress the routing table in a mesh topology NoC to very small sizes with very little negative effect on routing adaptivity. [ABSTRACT FROM AUTHOR]

Production planning of a flexible manufacturing system (FMS) is plagued by two interrelated problems, namely 1) part-type selection and 2) operation allocation on machines. The combination of these problems is termed a machine loading problem, which is treated as a strongly NP-hard problem. In this paper, the machine loading problem has been modeled by taking into account objective functions and several constraints related to the flexibility of machines, availability of machining time, tool slots, etc. Minimization of system unbalance (SU), maximization of system throughput (TH), and the combination of SU and TH are the three objectives of this paper, whereas two main constraints to be satisfied are related to time and tool slots available on machines. Solutions for such problems even for a moderate number of part types and machines are marked by excessive computational complexities and thus entail the application of some random search optimization techniques to resolve the same. In this paper, a new algorithm termed as constraints-based fast simulated annealing (SA) is proposed to address a well-known machine loading problem available in the literature. The proposed algorithm enjoys the merits of simple SA and simple genetic algorithm and is designed to be free from some of their drawbacks. The enticing feature of the algorithm is that it provides more opportunity to escape from the local minimum. The application of the algorithm is tested on standard data sets, and superiority of the same is witnessed. Intensive experimentations were carried out to evaluate the effectiveness of the proposed algorithm, and the efficacy of the same is authenticated by efficiently testing the performance of algorithm over well-known functions. [ABSTRACT FROM AUTHOR]