Derivation and analysis on the analytical structure of interval type-2 fuzzy controller with two nonlinear fuzzy sets for each input variable

Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a type-2 fuzzy controller functions and lay a foundation for more rigorous system analysis and design. In this study, we derive and analyze the analytical structure of an interval type-2 fuzzy controller that uses the following identical elements: two nonlinear interval type-2 input fuzzy sets for each variable, four interval type-2 singleton output fuzzy sets, a Zadeh AND operator, and the Karnik-Mendel type reducer. Through dividing the input space of the interval type-2 fuzzy controller into 15 partitions, the input-output relationship for each local region is derived. Our derivation shows explicitly that the controller is approximately equivalent to a nonlinear proportional integral or proportional differential controller with variable gains. Furthermore, by comparing with the analytical structure of its type-1 counterpart, potential advantages of the interval type-2 fuzzy controller are analyzed. Finally, the reliability of the analysis results and the effectiveness of the interval type-2 fuzzy controller are verified by a simulation and an experiment.

PRI modulation recognition and sequence search under small sample prerequisite

Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide radars are highly confusing.There are few available training samples in practical situations,which leads to a low recognition accuracy and poor search effect of the pulse sequence.In this paper,an approach based on bi-directional long short-term memory(BiLSTM)networks and the temporal correlation algorithm for PRI modulation recognition and sequence search under the small sample prerequisite is proposed.The simulation results demonstrate that the proposed algorithm can recognize unilinear,bilinear,sawtooth,and sinusoidal PRI modulation types with 91.43% accuracy and complete the pulse sequence search with 30% missing pulses and 50% spurious pulses under the small sample prerequisite.

Atmospheric environmental capacity and urban atmospheric load in China's Mainland

Daily and annual average atmospheric environmental capacity coefficient(A-value) sequences for China's Mainland are calculated from hourly data recorded at 378 ground stations over 1975–2014. A-values at different recurrence intervals are calculated by fitting the sequences to Pearson type III distribution curves. Based on these A-values and source-sink balance(reference concentration 100 μg m^(-3)), atmospheric environmental capacities at the recurrence intervals are calculated for all of China's Mainland and each provincial administrative region. The climate average atmospheric environmental capacity reference value for the entire mainland is 2.169×10~7 t yr^(-1). An urban atmospheric load index is defined for analyses of the impact of population density on the urban atmospheric environment. Analyses suggest that this index is also useful for differentiating whether air quality changes are attributable to varying meteorological conditions or variations of artificial emission rate.Equations guiding the control of unorganized emission sources are derived for preventing air quality deterioration during urban expansion and population concentration.