Fazel Naghdy

An Energy-Efficient Mobile-Sink Path Selection Strategy for Wireless Sensor Networks

Several studies have demonstrated the benefits of using a mobile sink to reduce the energy consumption of nodes and to prevent the formation of energy holes in wireless sensor networks (WSNs). However, these benefits are dependent on the path taken by the mobile sink, particularly in delay-sensitive applications, as all sensed data must be collected within a given time constraint. An approach proposed to address this challenge is to form a hybrid moving pattern in which a mobile-sink node only visits rendezvous points (RPs), as opposed to all nodes. Sensor nodes that are not RPs forward their sensed data via multihopping to the nearest RP. The fundamental problem then becomes computing a tour that visits all these RPs within a given delay bound. Identifying the optimal tour, however, is an NP-hard problem. To address this problem, a heuristic called weighted rendezvous planning (WRP) is proposed, whereby each sensor node is assigned a weight corresponding to its hop distance from the tour and the number of data packets that it forwards to the closest RP. WRP is validated via extensive computer simulation, and our results demonstrate that WRP enables a mobile sink to retrieve all sensed data within a given deadline while conserving the energy expenditure of sensor nodes. More specifically, WRP reduces energy consumption by 22% and increases network lifetime by 44%, as compared with existing algorithms.

Force Application During Cochlear Implant Insertion: An Analysis for Improvement of Surgeon Technique

Highly invasive surgical procedures, such as the implantation of a prosthetic device, require correct force delivery to achieve desirable outcomes and minimize trauma induced during the operation. Improvement in surgeon technique can reduce the chances of excessive force application and lead to optimal placement of the electrode array. The fundamental factors that affect the degree of success for cochlear implant recipients are identified through empirical methods. Insertion studies are performed to assess force administration and electrode trajectories during implantations of the Nucleusreg 24 Contourtrade and Nucleusreg 24 Contour Advancetrade electrodes into a synthetic model of the human Scala Tympani, using associated methods. Results confirm that the advance off- stylet insertion of the soft-tipped contour advance electrode gives an overall reduction in insertion force. Analysis of force delivery and electrode positioning during cochlear implantation can help identify and control key factors for improvement of insertion method. Based on the findings, suggestions are made to enhance surgeon technique.

Active control of along wind response of tall building using a fuzzy controller

Abstract This paper focuses on the benchmark problem application regarding the vibration control of tall buildings under along wind excitation. The building under consideration is the 76-story, 306 meter tall reinforced concrete office tower proposed for the city of Melbourne, Australia. The adopted control scheme consists of an Active Tuned Mass Damper (ATMD) where the control action is achieved by a Fuzzy Logic Controller (FLC). The main advantage of the fuzzy controller is its inherent robustness and ability to handle any non-linear behaviour of the structure. This benchmark study is based on specified design constraints for the ATMD to be considered in the design of the proposed control scheme. The robustness of the controller has been demonstrated through the uncertainty in stiffness (+15% and −15% variation from initial stiffness) of the building. The results of the simulation show a good performance by the fuzzy controller for all cases tested. Also the results show that the fuzzy controller performs slightly better than the LQG controller, while possessing several advantages over the LQG controller.

Coordination in wireless sensor-actuator networks: A survey

Wireless Sensor-Actuator Networks (WSANs) have a myriad of applications, ranging from pacifying bulls to controlling light intensity in homes automatically. An important aspect of WSANs is coordination. Unlike conventional Wireless Sensor Networks (WSNs), sensor and actuator nodes must work hand-in-hand to collect and forward data, and act on any sensed data collaboratively, promptly and reliably. To this end, this paper reviews current state-of-the-art techniques that address this fundamental problem. More specifically, we review techniques in the following areas: (i) sensor-actuator coordination, (ii) routing protocols, (iii) transport protocols, and (iv) actuator-to-actuator coordination protocols. We provide an extensive qualitative comparison of their key features, advantages and disadvantages. Finally, we present unresolved problems and future research directions.

Extended active observer for force estimation and disturbance rejection of robotic manipulators

The current control methods applied to robotic manipulators either require full state and force measurements, or use the state and force estimation in the absence of any kind of disturbance. As an alternative approach, a new adaptive motion control approach for robotic manipulators extending the existing active observer for simultaneous inertial parameters and force estimation is proposed. The scheme provides accurate force and full state estimation in the presence of robot inertial parameter variations and measurement noise, both subsequently used in the design of a controller. Since the proposed method relies mainly on the position of the plant, it significantly reduces the difficulty and cost of implementation. The velocity, parameter and force signals are estimated from the position. The approach is applied to a typical two-degree-of-freedom (2DOF) robotic manipulator through computer simulation. The results are encouraging and demonstrate the noise rejection ability of the scheme.

Application of Adaptive Controllers in Teleoperation Systems: A Survey

A survey of the adaptive controllers deployed to address major inherent control issues in robotic teleoperation systems is carried out. The study in particular explores the application of adaptive controllers in dealing with master and slave model uncertainties, operator and environment force model uncertainties, unknown external disturbances, and communication delay. The reviewed literature is structured according to the objectives envisaged for the adaptive controllers. Meanwhile, some adaptive methods deployed in human-robot interaction, where robots collaborate with people and actively support them, and local robot control, where robot manipulators are controlled at the same location as the operator, are also considered in the review as they can be used in teleoperation with some minor adjustment. A comparison of the strengths, deficiencies, and requirement of methods in each category is carried out. The study indicates that the majority of the proposed methods either require additional hardware such as sensors, or assume an accurate model of the system under study. The possible future research directions are outlined based on the gaps identified in the survey.

Application of wave-variable control to bilateral teleoperation systems: A survey

Abstract Teleoperation systems allow an operator to perform complex tasks in a remote environment. Stability of a bilateral teleoperation system is quite sensitive to time delays. One of the methods to guarantee the stability of bilateral telerobotics in the presence of time delays is wave variable control. A review of various applications of wave variable methods in telerobotics has been conducted. An evaluation of different methods proposed to compensate for the intrinsic problems associated with wave variable methods, including position drift, wave reflection and time varying delay, has also been carried out. In addition, different techniques developed to enhance the performance of the wave-based systems are also identified and reviewed. The research gaps in this field are identified and future directions for further research are proposed.

Recognizing human motions through mixture modeling of inertial data

Systems that recognize patterns in human motion are central to improvements in automation and human computer interaction. This work addresses challenges which arise in the context of recognizing arbitrary human actions from body-worn sensors. Chiefly the invariance to temporal scaling of events, coping with unlabeled data and estimating an appropriate model complexity. In order to deal with the severe case of unlabeled data, a method is proposed based on dynamic time alignment of Gaussian mixture model clusters for matching actions in an unsupervised temporal segmentation. In facilitation of this, an extensive corpus of continuous motion sequences composed of everyday tasks was recorded as analysis scenarios. The technique achieved an average accuracy of 72% for correctly merging actions performed by different participants. With labeled data and recognition models designed for particular classes, an accuracy of 89% was achieved in classifying the motion of participants left out of the modeling process. These results are contrasted with benchmark methods for recognition in a systematic validation revealing, in particular, an improved performance for mixture model prediction utilizing segments. HighlightsA method is proposed for unsupervised segment clustering of human motion capture data.Gaussian mixture models and dynamic time warping are used to compare similar data sequences.Human motion capture data was collected with a set of body-worn inertial sensors.The resultant classifier is compared with k-nearest-neighbor and support vector machine approaches.

Human Motion Recognition through Fuzzy Hidden Markov Model

A new type of hidden Markov model (HMM) developed based on the fuzzy clustering result is proposed for identification of human motion. By associating the human continuous movements with a series of human motion primitives, the complex human motion could be analysed as the same process as recognizing a word by alphabet. However, because the human movements can be multi-paths and inherently stochastic, it is indisputable that a more sophisticated framework must be applied to reveal the statistic relationships among the different human motion primitives. Hence, based on the human motion recognition results derived from the fuzzy clustering function, HMM is modified by changing the formulation of the emission and transition matrices to analyse the human wrist motion. According to the experimental results, the complex human wrist motion sequence can be identified by the novel HMM holistically and efficiently

Active control of wind excited structures using fuzzy logic

The first stage in the development of a fuzzy controller for active control of vibration in a wind excited tall structure is reported. The initial rule base of the fuzzy controller is developed based on the input/output data obtained from the performance of the system under a state feedback controller. The performance of the developed controller is validated through computer simulation. The controller is applied to both the building model from which the rule base is extracted and another building with similar dynamics but different parameters. The developed controller has significantly outperformed a state feedback controller and a previously developed intuitive fuzzy controller in terms of the maximum required control force. The amplitude of the steady state oscillation produced by the state feedback controller has, however, proved to be marginally better than the other two controllers.