As wireless sensor networks (WSNs) become more advanced, they are gradually applied to various fields, such as medical monitoring, and receive increased attention because of their great potential. WSN localization methods are crucial for numerous applications. To increase localization accuracy, a method is proposed that calculates the number of hops between nodes using the degree of irregularity model. The amorphous method is then adopted to calculate the average distance, and multidimensional scaling is used to estimate the coordinates of unknown nodes. Finally, boundary correction and multipower transmission techniques are adopted to reduce the error of estimation. This integrated localization method reduces localization errors which may occur at each step of distance vector (DV)-hop localization. The proposed method-boundaryimproved amorphous localization with multipower multidimensional scaling (BIA-MMS)-substantially improved the localization accuracy compared with other localization methods when tested through simulations.
By referencing the adaptive stator flux estimator (ASFE) framework in the model reference adaptive system (MRAS), this study designed an adaptive rotor speed estimator and a stator resistance estimator, and applied the Takagi-SugenoKang (TSK) fuzzy system and projection algorithms to the estimators to establish an induction motor direct torque controlled system without a speed sensor and possessing stator resistance adjustment abilities. In addition, the adaptive TSK fuzzy controller (ATSKFC) was adopted as the speed controller of the system, and was capable of online learning. The transient response was improved by the integration of a refined compensation controller.Induction motor controlled drive system was implemented in this study by using direct torque control (DTC) technology, which had the advantages of a rapid dynamic response, simple system structure, and low computational complexity. In addition, the application of the voltage space vector pulse width modulation (VSVPWM) technique reduced the torque ripples and noise, which are common in a traditional DTC system.The simulation and experimental results demonstrated that, with the proposed adaptive TSK fuzzy rotor speed estimator (ATSKFRSE), adaptive TSK fuzzy stator resistance estimator (ATSKFSRE), and an ATSKFC implanted into the induction motor DTC system, the system provided an excellent speed dynamic response and was able to estimate the rotor speed and stator resistance accurately at an 8-Nm load torque and a wide speed range of 36-2000 rpm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.