Prosthetic Hand Finger Control Using Fuzzy Sliding Modes

In order to improve the life quality of amputees, providing approximate manipulation ability of a human hand to that of a prosthetic hand is considered by many researchers. In this study, a biomechanical model of the index finger of the human hand is developed based on the human anatomy. Since the activation of finger bones are carried out by tendons, a tendon configuration of the index finger is introduced and used in the model to imitate the human hand characteristics and functionality. Then, fuzzy sliding mode control where the slope of the sliding surface is tuned by a fuzzy logic unit is proposed and applied to have the finger model to follow a certain trajectory. The trajectory of the finger model, which mimics the motion characteristics of the human hand, is pre-determined from the camera images of a real hand during closing and opening motion. Also, in order to check the robust behaviour of the controller, an unexpected joint friction is induced on the prosthetic finger on its way. Finally, the resultant prosthetic finger motion and the tendon forces produced are given and results are discussed.     

Full perimeter obstacle contact sensor based on flex sensors

This paper presents an obstacle contact sensor system that can detect both the contact state and the direction of contact parallel to the movement plane of a mobile system carrying the sensor. This sensor system is based on a regular- or irregular-shaped ring surrounding the mobile system’s perimeter, connected to the mobile system’s body by a set of soft springs and also coupled mechanically to a set of four flex sensors measuring the relative displacement and direction of the ring when contacting an obstacle. The set of flex sensors is connected to a low-cost electronic module that implements a data acquisition block and a fuzzy processing block, delivering a value representing the estimated contact zone of the ring. Some experiments show how this detection system effectively reduces the sensor count needed for full coverage of the mobile system’s perimeter. Despite the kind of output implemented in the experiments, the contact force can also be estimated.     

Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation

This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e. agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads. Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume also that the global traffic replicates the behavior of agents in different situations.     

Classification of Fuzzy Mathematical Morphologies Based on Concepts of Inclusion Measure and Duality

Mathematical morphology was originally conceived as a set theoretic approach for the processing of binary images. Extensions of classical binary morphology to gray-scale morphology include approaches based on fuzzy set theory. This paper discusses and compares several well-known and new approaches towards gray-scale and fuzzy mathematical morphology. We show in particular that a certain approach to fuzzy mathematical morphology ultimately depends on the choice of a fuzzy inclusion measure and on a notion of duality. This fact gives rise to a clearly defined scheme for classifying fuzzy mathematical morphologies. The umbra and the level set approach, an extension of the threshold approach to gray-scale mathematical morphology, can also be embedded in this scheme since they can be identified with certain fuzzy approaches.

Condition evaluation of existing reinforced concrete bridges using fuzzy based analytic hierarchy approach

There is an urgent need for a systematic methodology for condition assessment of the bridges because the old bridges of most of the countries are inadequate to carry current-day traffic and satisfy the present codal provisions and even in newer bridges, deterioration caused by unforeseen service condition and deferred maintenance is of great concern. In view of this, an attempt has been made in this study to develop a systematic procedure and formulations for condition evaluation of existing bridges using Analytic Hierarchy Process in a fuzzy environment. Analytic Hierarchy Process (AHP) is an efficient decision making tool for complicated problems with multiple evaluation criteria and uncertainty. Fuzzy logic approach has been used to take care of the uncertainties and imprecision in the bridge inspector’s observations. In this paper, first, a methodology has been proposed for condition ranking of number of reinforced concrete (RC) bridges. Then, based on the results obtained from prioritization, rating of the most deserved bridge has been carried out using MADM based fuzzy logic. Computer programs have been developed based on the formulations presented in this paper for evaluating condition of existing bridges and the details are presented in the paper. The methodology and its application are demonstrated through a case study. This methodology would certainly help the engineers and policy makers concerned with bridge management to overcome the problem related to prioritization and decision on funding related to rehabilitation of bridges.     

Design of variable structure control for fuzzy nonlinear systems

In this paper, the variable structure control problem is presented for Takagi–Sugeno fuzzy systems with uncertainties and external disturbances. The sliding surfaces for the T–S fuzzy system are proposed by using a Lyapunov function and a fuzzy Lyapunov function, respectively. And we design the variable structure controllers such that the global T–S fuzzy system confined on the sliding surfaces is asymptotically stable. Two examples are given to illustrate the effectiveness of our proposed methods.     

A neural net-based time-delay compensation scheme and disturbance rejection for pneumatic systems

In practical electro-pneumatic or hydraulic servo mechanism, there is usually an unavoidable operating delay time in the solenoid valves. This may sometimes cause closed-loop instability if the time delay is not treated carefully in the control system designs. Furthermore, pneumatic actuators can offer high performance at low cost, but are often suffered from external disturbances depending on the operating conditions. This paper proposes a non-model-based design approach for pneumatic actuating systems. In the proposed control system, a gain scheduled fuzzy-PID controller ensures tracking performance an adaptable wavelet neuro compensator compensates for time-delay of the control valve, and a disturbance rejecter diminishes influence from load changes. A condition ensuring the closed-loop stability is derived. The proposed design is experimentally verified to show its effectiveness.     

Implementation of call admission control scheme in next generation mobile communication networks using particle swarm optimization and fuzzy logic systems

In the present and next generation wireless networks, cellular system remains the major method of telecommunication infrastructure. Since the characteristic of the resource constraint, call admission control is required to address the limited resource problem in wireless network. The call dropping probability and call blocking probability are the major performance metrics for quality of service (QoS) in wireless network. Many call admission control mechanisms have been proposed in the literature to decrease connection dropping probability for handoffs and new call blocking probability in cellular communications. In this paper, we proposed an adaptive call admission control and bandwidth reservation scheme using fuzzy logic control concept to reduce the forced termination probability of multimedia handoffs. Meanwhile, we adopt particle swarm optimization (PSO) technique to adjust the parameters of the membership functions in the proposed fuzzy logic systems. The simulation results show that the proposed scheme can achieve satisfactory performance when performance metrics are measured in terms of the forced termination probability for the handoffs, the call blocking probability for the new connections and bandwidth utilization.     

一般模糊极大-极小神经网络的研究与应用

分析一般模糊极大-极小神经网络的基本原理,阐述模糊计算方法在分类中的准确性和高效性。将一般模糊极大-极小神经网络应用于企业资信评估中,实现模糊区间的输入,缩小企业评估指标定量化中的误差范围。资信评估结果表明,该算法能快速、有效地对企业进行分类,为资信评估提供了解决方案。     

模糊C-均值(FCM)聚类算法的实现

传统的FCM算法能够将靠近边界的具有固有形状的两个簇合并成为一个大的簇.然而,对于一些稍微复杂的数据,如果没有其它的像去除小簇之类的机制的话,FCM算法很难将非常接近的类聚类到一起.给出的聚类算法是在传统FCM算法的循环之后添加了去除掉空簇的步骤,解决了上述很难将非常接近的类聚到一个簇中的问题.另外,为便于选出最优结果,在递归之后又添加了计算聚类有效性的步骤.最后用Java实现了该算法并在数据集上进行了实验,证实了改进方法的有效性.