SummaryIn this article, considering one type of fuzzy discrete‐time networked control systems (NCSs) under stochastic communication protocol (SCP), a fuzzy‐based nonfragile H∞ filter is developed to detect the subsistent fault signal. The Takagi‐Sugeno (T‐S) mathematical model is employed to approximate the nonlinearities in the concerned fuzzy NCSs. The SCP is adopted to decide which sensor gets the access to the communication network at certain time instant, and the scheduling model of which is constructed as a Markov chain. Taking into account that the filter gain parameters in real practice may suffer fluctuations during the implementation, a modified nonfragile fuzzy filter is designed to detect the fault occurred in the signal transmission. By using the strong centralized stochastic analysis technique and the matrix calculation method, a Lyapunov function is adopted to derive sufficient conditions under which the filtering error dynamics is stochastically stable and the H∞ performance is satisfied. Then, the desired nonfragile fuzzy fault detection filter is realized by solving a certain linear matrix inequality. Finally, the effectiveness of the develop fault detection scheme is verified in the simulation example.
The ultimate goal of distributed renewable energy control is to minimize disorder disturbance to the power grid while ensuring maximum energy utilization. Taking wind power as an example, a coupling system using flywheel energy storage system to balance the output variables of wind power system was proposed while using hill climb searching (HCS) to maximize the utilization of wind energy. These methods can obtain stable DC output voltage. In the case of wind speed variation, as a limited capacity energy pool structure, flywheel energy storage system can ensure the maximum utilization of wind energy. Based on fully utilization of wind energy resources, the rapid and comprehensive compensation of wind power output can effectively smooth the output voltage of grid-connected wind power system, thus achieving the purpose of improving the power quality of grid-connected wind power system.
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