The performance of cooperative localization can be degraded in the partially connected wireless sensor network (WSN). In this letter, we address the localization problem based on the incomplete distance information. By considering the input of distance-based localization algorithms, we proposed a novel Gram matrix completion method. With the function of Gram matrix, we indirectly represent the measurement of Gram matrix by the Euclidean distance matrix (EDM). The recovered Gram matrix can directly used for multidimensional scaling (MDS) or semi-definite programming (SDP) to localize the nodes. Then we present the procedure of MDS and rigid transformation estimation to localize the nodes. The performance of the proposed algorithm is evaluated compared with low rank matrix completion and positioning algorithms.

A robust model predictive control (RMPC) framework is proposed for nonlinear cyber-physical systems (CPSs) with input saturation and energy-bounded disturbance in this article. The coexistence of Lipschitz nonlinearity and actuator saturation remains a challenging problem in controller design. In our article, a major concern is to address the incorporation of bipartite nonlinear characteristics and exogenous disturbance under RMPC scheme. Via the saturation relaxation and Lipschitz condition, the conversion of a tractable linear matrix inequalitie-constrained problem is proposed in a less conservative way. For the purpose of enhancing the robustness and disturbance rejection, the proposed RMPC framework is associated with mixed$H_{2}$/$H_{\infty }$requirements. In particular, the algorithm is then cast into minimizing the upper bound of infinite-horizon cost function, and it is updated online for the linear control law. The computational feasibility is proved recursively, which is the key point in the practical implementation. Also, both the closed-loop stability and performance of CPS are derived. Eventually, the laboratory tank and reactor–separator process are presented to verify and illustrate the effectiveness of the proposed RMPC with mixed$H_{2}$/$H_{\infty }$performance.

Abstract This paper uses a fuzzy set scheme to present an adaptive fractional differential algorithm for image edge enhancement and texture preservation. In the proposed algorithm, an image's membership function and area feature are used to calculate the fuzzy set of images. The function of adaptive fractional differential order (FAFDO) can be constructed by making the linear transformation of the fuzzy set. Then, the fuzzy adaptive fractional differential mask (FAFDM) is obtained by substituting the FAFDO into the fractional differential mask. Finally, the image edge and texture are enhanced and preserved by applying airspace filtering of the FAFDM convolution. The experimental results show that, compared to fractional differential or fuzzy set‐based image enhancement algorithms, the proposed algorithm can adaptively enhance the image edge and preserve the image texture by analysing the fuzziness of the image itself.

The application of cyber-physical system (CPS) and edge computing in smart logistics systems has greatly improved the work efficiency. This article mainly focuses on the planning and scheduling problems in the CPS-based multiple automatic guided vehicles logistics system. A virtual network map with uneven time constraints is first proposed, which realizes the control and interaction of actual work in the control layer. Then, an improved A* path planning algorithm based on the characteristics of the path network model is implemented. A novel traffic control method is added to the planning process to achieve time-sensitive and proactive scheduling and collision avoidance. Results of the numerical experiments reveal that the proposed CPS-based heuristic method could be effectively applied to the multiple automatic guided vehicles logistics system to further improve system security as well as work efficiency.

The leader-following consensus method is studied in the connected vehicle systems (CVSs) with the constant time delay. Based on the neighboring vehicle information, the distributed control protocols are designed for the second-order CVSs with the time delay. The necessary and sufficient conditions of internal stability are derived, in which the relationship between the controller parameters and eigenvalues of the Laplician matrix of the network topology is revealed in absence of time delays. Based on such conditions, the sufficient conditions of internal stability are derived and the resulting thresholds of the controller gains are obtained, which are independent of general network topologies. For the CVSs in the presence of the time delay, the necessary and sufficient conditions of internal stability are also derived and the explicit time-delay upper boundary is also given. The two main results are applied to PLF topology and achieve the corresponding necessary and sufficient conditions of internal stability in both the absence and presence of time-delays cases. Considering influence of perturbations, the conditions of the string stability are further derived under the PLF topology, which can ensure perturbations are not amplified downstream, besides guaranteeing stability of the CVSs. Considering time delays and perturbations simultaneously, furthermore, the conditions of both internal stability and string stability are obtained for the PLF topology. Such conditions only depend on the controller parameters and the network weights. So it is convenient to tune the threshold of the controller parameters and determine the time-delay boundary. Simulations are conducted to validate the theoretical results.

In this paper, an improved L2 gain performance controller synthesis is proposed for Takagi-Sugeno (T-S) fuzzy system. The T-S fuzzy controller can be easily derived by a three-step procedure with the linear matrix inequalities (LMIs) technique. First, a new T-S fuzzy model structure is presented, which includes the original T-S fuzzy plant with stable pre- and post filters on the input and output of the original plant. Second, by using this structure the L2 gain performance controller design problem can be easily transformed into standard LMIs formulation. Compared with the previous results, it not only gives us a simple structure of the T-S fuzzy controller, but also provides us effective LMIs-based conditions, which include a small number of unknown matrix variables; consequently, less value of L2 gain performance of the closed-loop system can be obtained. Third, an augmented T-S fuzzy controller which guarantees L2 gain performance is obtained for the original T-S fuzzy plant, which is composed of the T-S controller derived from step two and two stable pre- and post filters. Finally, some numerical examples are demonstrated to show the effectiveness of the proposals.