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Nonlinear dynamics is frequently encountered in practical applications. Adaptive dynamic programming (ADP), which is implemented via actor/critic neural networks with excellent approximation capabilities, is appropriate to be used in finding the solution for the control problem in the presence of known/unknown nonlinear dynamics. The objective of this paper is to introduce state-of-the-art ADP-based algorithms and survey the recent advances in the ADP-based control strategies for nonlinear systems with various engineering-oriented complexities. Firstly, the main motivation of the ADP-based algorithms is thoroughly discussed, and the way of implementing the ADP-based algorithms is highlighted. Then, the latest research results concerning ADP-based control policy design for nonlinear systems are reviewed in detail, Finally, we conclude the survey by outlining the challenges and possible research topics in the future. [ABSTRACT FROM AUTHOR]

Real-world graphs exhibit many interesting properties that differentiate them from random graphs, which have been extensively studied for the past decades. For various proposed generative models, a majority of them build the graph by sequentially adding each node and the attached edges. However, the growth of many real-world graphs, such as social networks, is naturally modeled by the sequential insertion of edges. Unfortunately, to the best of our knowledge, no generative model has been proposed to reveal this process. We propose the first sequence-of-edges model, denoted as temporal preferential attachment (TPA). It relies on preferential attachment (PA), one of the most influential mechanisms to generate scale-free graphs, and takes time-decay effect and node fitness into consideration. Empirical analysis demonstrates that our model preserves several key properties of the real-world graphs, including both the properties observed from the snapshot graphs (e.g., power-law distribution) and temporal properties observed from the graph generation process (e.g., shrinking diameter). Meanwhile, our model is sufficiently general to accommodate several forms of time decay and fitness distributions. Then, we design two efficient algorithms that generate TPA graphs with billions of edges in several minutes. [ABSTRACT FROM AUTHOR]

In this paper, the target tracking problem is investigated for a class of wireless localization systems with degraded measurements and quantization effects. The measurement degradations induced by unreliable channels are characterized by a random parameter matrix, and the quantization effects are modeled by sector-bounded uncertainties. A recursive filtering algorithm is proposed in order to track the plant states as accurately as possible. An upper bound on the filtering error covariance is first derived and such an upper bound is then minimized by properly designing the filter gain at each sampling instant. The desired filter parameters are obtained by solving two sets of Riccati-like difference equations that are in a recursive form suitable for online application. Finally, a simulation experiment is carried out for the scenario of personnel localization/tracking problems in a mine industrial site and the effectiveness of the proposed filter method is demonstrated. [ABSTRACT FROM AUTHOR]

Due to its wide applications, subgraph query has attracted lots of attentions in database community. In this paper, we focus on subgraph query over a single large graph G, i.e., finding all embeddings of query Q in G. Different from existing feature-based approaches, we map all edges into a two-dimensional space R and propose a bitmap structure to index R. At run time, we find a set of adjacent edge pairs (AEP) or star- style patterns (SSP) to cover Q. We develop edge join (EJ) algorithms to address both AEP and SSP subqueries. Based on the bitmap index, our method can optimize I/O and CPU cost. More importantly, our index has the linear space complexity instead of exponential complexity in feature-based approaches, which indicates that our index can scale well with respect to large data size. Furthermore, our index has light maintenance overhead, which has not been considered in most of existing work. Extensive experiments show that our method significantly outperforms existing ones in both online and offline processing with respect to query response time, index building time, index size and index maintenance overhead. [ABSTRACT FROM AUTHOR]

In real-world graphs such as social networks, Semantic Web and biological networks, each vertex usually contains rich information, which can be modeled by a set of tokens or elements. In this paper, we study a subgraph matching with set similarity (SMS$^2$ ) query over a large graph database, which retrieves subgraphs that are structurally isomorphic to the query graph, and meanwhile satisfy the condition of vertex pair matching with the (dynamic) weighted set similarity. To efficiently process the SMS $^2$ query, this paper designs a novel lattice-based index for data graph, and lightweight signatures for both query vertices and data vertices. Based on the index and signatures, we propose an efficient two-phase pruning strategy including set similarity pruning and structure-based pruning, which exploits the unique features of both (dynamic) weighted set similarity and graph topology. We also propose an efficient dominating-set-based subgraph matching algorithm guided by a dominating set selection algorithm to achieve better query performance. Extensive experiments on both real and synthetic datasets demonstrate that our method outperforms state-of-the-art methods by an order of magnitude. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we study a variant of reachability queries, called label-constraint reachability (LCR) queries. Specifically, given a label set S and two vertices u 1 and u 2 in a large directed graph G, we check the existence of a directed path from u 1 to u 2, where edge labels along the path are a subset of S. We propose the path-label transitive closure method to answer LCR queries. Specifically, we t4ransform an edge-labeled directed graph into an augmented DAG by replacing the maximal strongly connected components as bipartite graphs. We also propose a Dijkstra-like algorithm to compute path-label transitive closure by re-defining the “distance” of a path. Comparing with the existing solutions, we prove that our method is optimal in terms of the search space. Furthermore, we propose a simple yet effective partition-based framework (local path-label transitive closure+online traversal) to answer LCR queries in large graphs. We prove that finding the optimal graph partition to minimize query processing cost is a NP-hard problem. Therefore, we propose a sampling-based solution to find the sub-optimal partition. Moreover, we address the index maintenance issues to answer LCR queries over the dynamic graphs. Extensive experiments confirm the superiority of our method. [Copyright &y& Elsevier]

In this paper, a new strategy is developed to plan the smooth path for mobile robots through an improved PSO algorithm in combination with the continuous high-degree Bezier curve. Rather than connecting several low-degree Bezier curve segments, the use of continuous high-degree Bezier curves facilitates the fulfillment of the requirement of high-order continuity such as the continuous curvature derivative, which is critical for the motion control of the mobile robots. On the other hand, the smooth path planning of mobile robots is mathematically an optimization problem that can be dealt with by evolutionary computation algorithms. In this regard, an improved particle swarm optimization (PSO) algorithm is proposed to tackle the local trapping and premature convergence issues. In the improved PSO algorithm, an adaptive fractional-order velocity is introduced to enforce some disturbances on the particle swarm according to its evolutionary state, thereby enhancing its capability of jumping out of the local minima and exploring the searching space more thoroughly. The superiority of the improved PSO algorithm is verified by comparing with several standard and modified PSO algorithms on some benchmark functions, and the advantages of the new strategy is also confirmed by several comprehensive simulation experiments for the smooth path planning of mobile robots. • In this paper, a new strategy is developed to plan the smooth path for mobile robots. • An improved PSO algorithm is proposed in combination with the continuous high-degree Bezier curve. • An adaptive fractional-order velocity is introduced to enforce some disturbances on the particle. • The superiority of the improved PSO algorithm is verified by comparing with several standard benchmark functions. • The advantages of the new strategy is also confirmed by simulation experiments for the smooth path planning of mobile robots. [ABSTRACT FROM AUTHOR]

This paper deals with the replay attack detection problem for a class of cyber–physical systems. A dynamic encryption–decryption scheme is proposed with the purpose of detecting the replay attacks launched by the malicious adversary. First, a new attack model is established to describe the periodic replay attacks that are generated by making use of a series of recorded past measurements. Then, the stealthiness is discussed for the proposed replay attack scheme against the χ 2 detector. Subsequently, on basis of the established model, a dynamic encryption–decryption scheme is developed without sacrificing any system performance, guaranteeing 100% detection probability in the occurrence of attacks. Finally, a simulation example is provided to firstly verify the stealthiness of the proposed replay attack and secondly demonstrate the effectiveness of the exploited dynamic encryption–decryption detection algorithm. [ABSTRACT FROM AUTHOR]

Given a record set D and a query score function F, a top-k query returns k records from D, whose values of function F on their attributes are the highest. In this paper, we investigate the intrinsic connection between top-k queries and dominant relationships between records, and based on which, we propose an efficient layer-based indexing structure, Pareto-Based Dominant Graph (DG), to improve the query efficiency. Specifically, DG is built offline to express the dominant relationship between records and top-k query is implemented as a graph traversal problem, i.e., Traveler algorithm. We prove theoretically that the size of search space (that is the number of retrieved records from the record set to answer top-k query) in our algorithm is directly related to the cardinality of skyline points in the record set (see Theorem 3). Considering I/O cost, we propose cluster-based storage schema to reduce I/O cost in Traveler algorithm. We also propose the cost estimation methods in this paper. Based on cost analysis, we propose an optimization technique, pseudorecord, to further improve the search efficiency. In order to handle the top-k query in the high-dimension record set, we also propose N-Way Traveler algorithm. In order to handle DG maintenance efficiently, we propose “Insertion” and “Deletion” algorithms for DG. Finally, extensive experiments demonstrate that our proposed methods have significant improvement over its counterparts, including both classical and state art of top-k algorithms. [ABSTRACT FROM AUTHOR]

This paper is concerned with the target tracking problem for a class of wireless localization systems with unknown but bounded noises. Since the energy supply of wireless sensor nodes is rather scarce, a component-based event-triggered mechanism is utilized to reduce the signal transmission frequency by discarding the unnecessary information transmissions. The objective of the addressed problem is to design an event-triggered set-membership filter for target tracking with guaranteed performance. An estimate-based linearization approach is employed to reconstruct the innovation and a particle swarm optimization (PSO) algorithm is adopted to determine the uncertain scaling matrix generated by the linearization. The desired time-varying filter gain matrix is derived by solving a convex optimization problem. Finally, the personnel safety monitoring problem in a mine industrial site is considered in the simulation experiment to demonstrate the effectiveness of the proposed filtering algorithm. [ABSTRACT FROM AUTHOR]