Intelligent distributed and supervised flow control methodology for production systems

Decentralized Discrete Model Reference Adaptive Control

Adaptive global coordination of local routing policies for communication networks

Modelling and modular supervisory control for the AODV routing protocol

In this paper, the thyristor controlled system dynamic braking resistor and the nonlinear optimal control theory are approached simultaneously within a hierarchical framework. This creates a multiple local feedback controllers that can be realistically implemented using only local measurements and whose performance is consistent with respect to changes in network configuration, loading and power transfer conditions. Following a major disturbance, the rotor angle and rotor speed of each generator unit are determined and the firing angle of the thyristor switch associated with the braking resistor is calculated by the local controllers. By controlling the firing-angle of the thyristor, braking resistor controls the accelerating power in each generator and thus enhances the stability margins and damping oscillations. Since the local controllers rely only on information particular to their own subsystem, interconnection effects and the nonlinearities introduced by them, are accounted for by a supervisory controller. The proposed control strategy was tested on the IEEE Western States Coordinating Council (WSCC) test system. Results show that the method is capable of bringing the system under control when starting with inherently unstable conditions, even when the severity of the disturbances is increased.

Integration of fuel cell and electrolyzer on DC bus is a promising alternative to solve voltage fluctuation and balance of power problems in a standalone hybrid renewable power generation systems. The hybrid renewable power generation systems consist of photovoltaic, wind turbine, fuel cell and hydrogen electrolyzer. Each the component integrated on DC bus through the converter DC – DC using local controller to supply the inverter which connected to the islanded load. Local controller in each part will make the system become flexible if there are additional generating units in the future. The local control methods used in this hybrid renewable power generation system is MPPT and constant voltage control. MPPT control applied to photovoltaic and wind turbine converters to maximize power generation from photovoltaic and wind turbine. Constant voltage controller applied to the fuel cell and electrolyzer converters to control the DC bus voltage alternately. This research is a new design system for remote areas by utilizing the potensial of renewable energy in the area. The result show the power quality and continuity of electricity services.

Multi-view clustering can mine the underlying structure of multi-view data and has attracted increasing attention. Most existing multi-view clustering methods either construct the similarity matrix from the global level through self-representation learning or construct the similarity matrix from the local level through graph learning. Spectral clustering method can be used to yield the clustering results based on the similarity matrix. However, the similarity matrix that only considers global information or local information is not robust. Moreover, separating the similarity matrix learning and clustering as two steps may lead to sub-optimal clustering results. To address these issues, we propose in this paper, a multi-view subspace clustering with local and global information (MVSCLG) method. Our method combines the self-representation learning and graph learning to learn a similarity matrix with global and local information, and simultaneously utilizes the spectral decomposition and the spectral rotation techniques to yield the clustering results. We also develop an effective optimization algorithm to solve the resulting optimization problem. The effectiveness and superiority of this method are verified on four multi-view benchmark data sets.

Planning, operation and control of active distribution grids by increasing the number of dispersed generators is becoming more important but also more complex. Hence, the importance of controlling the voltage is highlighted in many research papers. Traditionally, in passive distribution networks the voltage rise has been mitigated by network reinforcement. Nowadays, local voltage control, coordinated voltage control and centralized voltage control have been discussed for active networks in research papers. Although all the approaches have been proven to solve the problem of voltage rise in distribution grids, using plenty of sensors to gather huge number of measurement could cause complexity. This paper represents a literature review of different voltage control approaches in active distribution grids and proposes a new procedure to set up a local voltage control law devoted to properly manage the voltage profile (e.g. minimizing losses on MV feeders).

In the paper a compiler that transforms a universal fuzzy system into a Takagi-Sugeno fuzzy system is presented. A universal fuzzy system is defined as a fuzzy system with generic membership functions, T-norm, T-conorm, propagation operator, aggregation operator and defuzzification algorithm. The Takagi-Sugeno system obtained is an approximation of the original fuzzy system based on keeping the certainty of the designer. This means that the inputs for which the designer had a complete certainty will be approximated without error.

Cloud-based collaborative learning of optimal feedback controllers

In this paper a decentralized guaranteed cost control for a class of interconnected large scale networked control system is presented. For this purpose a local state feedback controller is designed for each system. There is high interconnection between each subsystem. The control loop of each subsystem is closed via communication network. Packet Loss, network induced delay and delays at interconnected states are considered in problem formulation. New sufficient conditions for the existence of guaranteed cost controllers are proposed by introducing a Lyapunov-Krasovskii functional. An explicit expression for the desired robust decentralized local state feedback control law is also given. Finally, numerical example shows the efficiency of proposed method in comparison with conventional controls.

10 - DC microgrids for electric vehicle wireless charging

Exponential [formula omitted] filter design for uncertain Takagi–Sugeno fuzzy systems with time delay

Distributed supervisory control is a method to synthesize local controllers in discrete-eventsystems with a systematic observation of the plant. Some works were reported on extending this methodby which local controllers are constructed so that observation properties are preserved from monolithic todistributed supervisory control, in an up-down approach. In this paper, we find circumstances in whichobservation properties are preserved from monolithic to distributed supervisory control. Local observationproperties, i.e. local normality and local relative observability are employed for investigating observationproperties of each local controller, which are constructed by any localization algorithm that preserves controlequivalency to the monolithic supervisor with respect to the plant. These properties enable us to investigatethe observation properties from monolithic to distributed supervisory control. Moreover, observationequivalence property is defined according to the control equivalence in a distributed supervisory controlwith partial observation. It is proved that with preserving observation equivalence of the local controllers tothe monolithic supervisor, the control equivalence is satisfied, if and only if the intersection of local eventsets is a subset of or equal to the global observable event set.

Motion-inhibition control of a multi-robot mooring system using an actuating force fuzzy control method

It is now known that the complexity of network topology has a great impact on the stabilization of complex dynamical networks. In this work, we study the control of random networks and scale-free networks. Conditions are investigated for globally or locally stabilizing such networks. Our strategy is to apply local feedback control to a small fraction of network nodes. We propose the concept of virtual control for microscopic dynamics throughout the process with different pinning schemes for both random networks and scale-free networks. We explain the main reason why significantly less local controllers are required by specifically pinning the most highly connected nodes in a scale-free network than those required by the randomly pinning scheme, and why there is no significant difference between specifically and randomly pinning schemes for controlling random dynamical networks. We also study the synchronization phenomenon of controlled dynamical networks in the stabilization process, both analytically and numerically.