This paper examines the problem of robust H/sub /spl infin// static output feedback control of a Takagi-Sugeno fuzzy system. The proposed robust H/sub /spl infin// static output feedback controller guarantees the L/sub 2/ gain of the mapping from the exogenous disturbances to the regulated output to be less than or equal to a prescribed level. The existence of a robust H/sub /spl infin// static output feedback control is given in terms of the solvability of bilinear matrix inequalities. An iterative algorithm based on the linear matrix inequality is developed to compute robust H/sub /spl infin// static output feedback gains. To reduce the conservatism of the design, the structural information of membership function characteristics is incorporated. A numerical example is used to illustrate the validity of the design methodologies.

Industrial automation is entering a new era of the Industrial Internet with enhanced computing, communication, and storage capabilities provided by cloud computing and field devices. The paradigm of automation systems is shifting from the ISA-95 pyramid to the two-layers architecture: industrial cloud and edge computing. Industrial software is also evolving under the new architecture in ways for which dedicated software applications are no longer suited. Service-based industrial cloud and edge applications provide maximum flexibility, interoperability, and efficiency by combining the IEC 61499 standard, microservice architecture, and container technology. This article provides orchestration methods and deployment procedures for the OT-IT hybrid industrial edge applications. The feasibility of the proposed approach is demonstrated by an industrial case study with accompanying performance analysis.

The Industry 4.0 and Industrial Internet provides vertical and horizontal integration between edge devices and industrial cloud platforms. A flexible and interoperable information model is crucial for enabling device-level intelligence as well as cloud-edge collaboration. Deep integration between the control and information model is necessary for supporting closed-loop optimization between the cloud and edge devices. This article proposes an automatic information model generation method based on the IEC 61499 and OPC unified architecture standards. Model transformation rules between two models from design time to runtime are presented. A discrete manufacturing case study is used to prove that the proposed method can significantly reduce the development time for distributed information models. The integrated control and information models at runtime can provide strong support for dynamic reconfiguration to address changing requirements.

This brief investigates the analysis issue for global asymptotic stability of a class of generalized neural networks with multiple discrete and distributed delays. To tackle delays arising in different neuron activation functions, we employ a generalized model with multiple discrete and distributed delays which covers various existing neural networks. We then generalize the Bessel-Legendre inequalities to deal with integral terms with any linearly independent functions and nonlinear function of states. Based on these inequalities, we design the Lyapunov-Krasovskii functional and derive hierarchical linear matrix inequality stability conditions. Finally, three numerical examples are provided to demonstrate that the proposed method is less conservative with a reasonable numerical burden than the existing results.