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Xiaozhi Qi, Yu Sun, Xiaohang Ma, Ying Hu, Jianwei Zhang, Wei Tian
The lumbar spinal stenosis (LSS) is a kind of orthopedic disease which causes a series of neurological symptom. Vertebral lamina grinding operation is a key procedure in decompressive laminectomy for LSS treatment. With the help of image-guided navigation system, the robot-assisted technology is applied to reduce the burdens on surgeon and improve the accuracy of the operation. This paper proposes a multilevel fuzzy control based on force information in the robot-assisted decompressive laminectomy to improve the quality and the robotic dynamic performance in surgical operation...
2018: Advances in Experimental Medicine and Biology
Shaolong Kuang, Yucun Tang, Andi Lin, Shumei Yu, Lining Sun
Cooperation between surgeon and robot is one of the key technologies that limit the robot to be widely used in orthopedic clinics. In this study, the evolution of human-robot cooperation methods and the control strategies for typical human-robot cooperation in robot-assisted orthopedics surgery were reviewed at first. Then an intelligent admittance control method, which combines the fuzzy model reference learning control with the virtual constraint control, is proposed to solve the requirements of intuitive human-robot interaction during orthopedics surgery...
2018: Advances in Experimental Medicine and Biology
Chia-Feng Juang, Chan-Hung Lin, Trong Bac Bui
This paper proposes a new rule-based cooperative framework for multiobjective evolutionary fuzzy systems (FSs). Based on the framework, a multiobjective rule-based cooperative continuous ant-colony optimization (MO-RCCACO) algorithm is proposed to optimize all of the free parameters in FSs. Instead of optimization using a single colony of FSs (solutions), the MO-RCCACO consists of r subcolonies of size N cooperatively optimizing an FS that consists of r rules, with a subcolony optimizing only a single fuzzy rule...
October 8, 2018: IEEE Transactions on Cybernetics
Saeed Bahrami Moqadam, Seyed Mohammad Elahi, An Mo, WenZeng Zhang
In this research, the combination of fuzzy/PD and EMG signals, as direct command control, is proposed. Although fuzzy/PD strategy was used to control force position of the artificial hand, the combination of that with EMG signaling to voluntary direct command control is a novel method. In this paper, the EMG signal and its role in effective communication between a DC motor with a voltage trigger and neurofeedback are initially explained. Moreover, by introducing a filtration method, EMG pulses are obtained as stepping pulses with a signal-specific height of a voltage between 0 and 6 V, according to EMG domain voltage, with a time interval adapted from the EMG stimulus pulses...
2018: Robotics and Biomimetics
Yanyan Wang, Sen Wu, Linyan Xu, Yanan Zeng
Atomic Force Microscopy (AFM) plays a vital role in nanoscience and nanotechnology due to its nanoscale resolution. However, the realization of highly precise measurement for AFM is still a challenge. A main factor is the positioning accuracy of the piezoelectric scanner (PZT), affected significantly by the hysteresis of PZT. The paper reports a new dynamic polynomial fitting method modeling hysteresis to achieve the inverse model of the PZT. The inverse model is used as the feedforward input, combined with the fuzzy feedback controller proposed in our former paper, to correct the nonlinear errors induced by the hysteresis...
September 21, 2018: Ultramicroscopy
Hang Su, Weihai Zhang
This paper focuses on an input-to-state practical stability problem for a class of stochastic nonlinear systems with unmodeled dynamics and fuzzy dead zones. A feasible adaptive fuzzy control method is proposed for the developed stochastic system with the slope of dead zone being certain or fuzzy. Based on stochastic small-gain theorem and backstepping technique, the closed-loop system is guaranteed to be input-state-practically stable in probability. The main contributions of this paper lie in that the considered system is more general, and the modified Lemma 2 makes the presentation of the formulas in lemma consistent with their application forms...
October 1, 2018: IEEE Transactions on Cybernetics
Ziran Chen, Baoyong Zhang, Yijun Zhang, Qian Ma, Zhengqiang Zhang
This paper presents an auxiliary random series approach to model the effect of network induced problems, such as data losses and transmission delay subject to event-based communication scheme for nonlinear continuous time systems. T-S fuzzy model is employed to describe the nonlinear systems. In order to save the bandwidth and energy, we introduce the event-triggered mechanism to reduce the number of data for transmission and computation. Thus, it is necessary to consider the influence of data losses, data disorder, and transmission delay since the transmitted data packets become more important...
September 26, 2018: IEEE Transactions on Cybernetics
Liang Cao, Hongyi Li, Qi Zhou
This paper investigates the problem of adaptive fuzzy control on the basis of an event-triggered mechanism for nonlinear strict-feedback systems with time-varying external disturbances and virtual control coefficients in the presence of actuator failures. Virtual control coefficients are correlated with the designed adaptive law and control signal. In the backstepping technique procedure, fuzzy logic systems are utilized to approximate an unknown nonlinear function, and the tuning function is implemented to cope with the destabilizing problem of the control design...
September 26, 2018: IEEE Transactions on Cybernetics
Zohreh Kheradpisheh, Amir Hossein Mahvi, Masoud Mirzaei, Mehdi Mokhtari, Reyhane Azizi, Hossein Fallahzadeh, Mohammad Hassan Ehrampoush
Background: Artificial neural networks (ANNs) and adaptive neural-fuzzy Inference system (ANFIS) are the best solutions to finding the correlation between some water parameters and human hormones. The correlation between thyroid stimulating hormone (TSH) and drinking water fluoride studied by ANNS and ANFIS models in Yazd city. Method: In this study, eighty people with thyroid gland disorder and 213 healthy people invited. Their thyroid hormones and fluoride drinking water analyzed...
June 2018: Journal of Environmental Health Science & Engineering
Xianghui Deng, Tian Xu, Rui Wang
Risk assessment for tunnel portals in the construction stage has been widely recognized as one of the most critical phases in tunnel construction as it easily causes accident than the overall length of a tunnel. However, the risk in tunnel portal construction is complicated and uncertain which has made such a neural network very attractive to the construction projects. This paper presents a risk evaluation model, which is obtained from historical data of 50 tunnels, by combining the fuzzy method and BP neural network...
2018: Computational Intelligence and Neuroscience
R Sakthivel, S A Karthick, B Kaviarasan, Faris Alzahrani
This paper investigates the β-dissipativity-based reliable non-fragile sampled-data control problem for a class of interval type-2 (IT2) fuzzy systems. In particular, it is allowed to have randomly occurring time-varying delays in the controller design, which are modeled by Bernoulli distributed white noise sequences. Precisely, the IT2 fuzzy model and the non-fragile sampled-data controller are formulated by considering the mismatched membership functions. By constructing an appropriate Lyapunov-Krasovskii functional, a set of delay-dependent conditions is derived to guarantee that the closed-loop IT2 fuzzy system is strictly <Q,S,R>-β-dissipative...
September 11, 2018: ISA Transactions
Zheng Wang, Yuan Yuan, Hongjiu Yang
In this paper, an adaptive fuzzy tracking controller is developed for a class of strict-feedback Markovian jumping systems subjected to multisource uncertainties. The unpredictable actuator failures, the unknown nonlinearities, and the unmodeled dynamics are simultaneously taken into consideration, which evolve according to the Markov chain. It is noted that the elements in the transition rate matrix of the Markov chain are not fully available. In virtue of the norm estimation approach, the challenges caused by the complex multiple uncertainties and actuator failures are effectively handled...
September 17, 2018: IEEE Transactions on Cybernetics
Fazel Rajabi, Mehdi Jahangiri, Hossein Molaeifar, Marzieh Honarbakhsh, Payam Farhadi
Healthcare professionals, especially nurses and pre-hospital emergency (PHE) staff, are influenced by many stressors due to their responsibility to provide comfort as well as care and treatment of patients. The aim of the present study was to identify and rank the occupational stressors in nurses and PHE staff using Fuzzy Analytic Hierarchy Process (FAHP) method. In this cross-sectional study, occupational stress factors in nurses and PHE staffs were identified and ranked by 30 experts, using FAHP method. Occupational stress factors were collected by General Health Questionnaire (GHQ), Job Stress Questionnaires as well as a literature review...
2018: EXCLI Journal
Daniel Leitold, Agnes Vathy-Fogarassy, Janos Abonyi
Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is particularly small when compared to the size of the system, and, although structural observability is ensured, the system demands additional sensors to provide the small relative order needed for fast and robust process monitoring and control...
September 14, 2018: Sensors
Hossein Yazdani, Aazam Yazdani, Len Cheng, David Christiani
Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample belongs to a cluster. Variation of membership degrees in each cluster provides information about the cluster as a whole and each sample individually which enables to have insights toward precision medicine. Membership degrees are measured more accurately through removing restrictions from clustering samples...
September 12, 2018: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Hong Zhang, Chuansheng Wang, Xiaorui Li, Boyan Sun, Dong Jiang
A novel way to measure humidity through testing the emissivity of an area radiant source is presented in this paper. The method can be applied in the environment at near room temperature (5~95 °C) across the relative humidity (RH) range of 20~90% RH. The source, with a grooved radiant surface, works in the far infrared wavelength band of 8~12 μm. The Monte-Carlo model for thermal radiation was set up to analyze the V-grooved radiant surface. Heat pipe technology is used to maintain an isothermal radiant surface...
September 13, 2018: Sensors
Chedia Latrech, Ahmed Chaibet, Moussa Boukhnifer, Sébastien Glaser
This paper investigates platoon control of vehicles via the wireless communication network. An integrated longitudinal and lateral control approaches for vehicle platooning within a designated lane is proposed. Firstly, the longitudinal control aims to regulate the speed of the follower vehicle on the leading vehicle while maintaining the inter-distance to the desired value which may be chosen proportional to the vehicle speed. Thus, based on Lyapunov candidate function, sufficient stability conditions formulated in BMIs terms are proposed...
September 13, 2018: Sensors
Ying Li, Zhijun Yao, Huaxiang Zhang, Bin Hu
BACKGROUND: Optimized abnormalities of individual brain network may allow earlier detection of mild cognitive impairment (MCI) and accurate prediction of its conversion to Alzheimer's disease (AD). Currently, most studies constructed individual networks based on region-to-region correlation without employing multi-region information. In order to develop the potential discriminative power of network and provide supportive evidence for feasibility of individual metabolic network study, we propose a new approach to extract features from network with indirect relation based on 18 F-FDG PET data...
November 1, 2018: Journal of Neuroscience Methods
Shaoxin Sun, Huaguang Zhang, Yingchun Wang, Yuliang Cai
This paper is concerned with fault-tolerant control (FTC) for a class of nonlinear discrete-time systems. A dynamic output feedback controller is designed for Takagi-Sugeno (T-S) fuzzy systems with state and input parameter uncertainties, exogenous disturbances, measurement noise and multiple intermittent faults. Compared with the existing research results, the proposed controller has a wider application range. The stability of the closed-loop systems is guaranteed by H∞ performance and sufficient conditions are proposed for the considered system with multiple sensor faults, multiple actuator faults, multiple sensor and actuator faults, respectively, by solving linear matrix inequalities (LMIs)...
August 22, 2018: ISA Transactions
Hao Ma, Chunhao Zhong, Bing Chen, Kai-Ming Chan, Wei-Hsin Liao
Patients suffering from neurological and orthopedic diseases or injuries usually have mobility impairment problems, and they require customized rehabilitation training to recover. In recent years, robotic assistive devices have been widely studied for gait rehabilitation. In this paper, methods to determine user-adaptive assistance of assistive knee braces (AKBs) in gait rehabilitation are investigated. A fuzzy expert system, which takes a patient's physical condition and gait analysis results as inputs, is proposed to configure suitable levels of different assistive functions of the AKB...
October 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
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