Design and optimization of fuzzy controllers based on the operator's knowledge

Industrial processes are normally operated by skilled humans who have cumulative and logical information about the systems. Fuzzy control has been investigated for many applications. Intelligent control approaches based on fuzzy logic might be able to include human thinking. This article describes a modeling approach based upon an operator's knowledge without a mathematical model of the system and optimization of the controller. The test system applied was constructed to send a ball into the goal position using wind from two DC motors in a predefined path. A vision camera to mimic human eyes detects the ball's position. The system used in this experiment was difficult to model by mathematical methods, and could not easily be controlled by conventional methods. The controller is designed based on the input-output data as well as experimental knowledge obtained by trials, and optimized under predefined performance criteria. This work was presented, in part, at the Sixth International Symposium on Artifical Life and Robotics, Tokyo, Japan, January 15–17, 2001     

高速公路实时交通流模糊逻辑优化控制系统设计

高速公路交通流特征复杂多变,受到诸多影响因素的共同作用,如天气、道路状况、车辆类型等等。因此,如何获取交通流逻辑控制条件并实现精准调节难度较大。为此,本研究设计新的高速公路实时交通流模糊逻辑优化控制系统。对于系统的硬件部分,设计车流控制模块、无线传输车载终端、实时交通流逻辑调度模块、模糊控制器模块,并确定各个模块之间实时连接关系。对于系统的软件部分,求解交通流逻辑控制条件,联合高速公路实时通行相位条件,调节模糊控制器,并根据高速公路交通路网模型,推导交通流优化控制条件的求解表达式,完成高速公路实时交通流模糊逻辑优化控制系统的设计。实验结果表明,本系统可以解决逻辑协调错误的问题,且能够有效控制高速公路车流量。     

基于元胞自动机理论的快速公交系统能耗研究

交通运输能源消耗已经成为决策管理者高度关注的信息。采用元胞自动机（CA）理论研究了快速公交系统能耗问题,以元胞自动机NaSch交通流模型为基础,通过结合动能定理,建立了快速公交系统的元胞自动机能耗动力学仿真模型。并以目前建设的兰州市快速公交系统为例,仿真研究了周期性边界条件下,不同行车密度、不同停靠站时间以及驾驶员行为差异下随机慢化对快速公交车系统能耗的影响,得到了相应的定量分析结论。仿真结果表明,快速公交车辆停靠站时间越长,拥堵的范围越大,路面交通流能耗损失越小,对应的流量、速度也越小,系统越早进入堵塞相。     

An evaluation of a lane support system for bus rapid transit on narrow shoulders and the relation to bus driver mental workload

The use of dedicated bus shoulders is a key method for implementing bus rapid transit (BRT) in areas that do not have the space for additional infrastructure. However, the narrow width of the bus shoulder and the need to anticipate traffic hazards in the adjacent lane can both be significant stressors for bus drivers. Bus driver mental workload and stress in response to these conditions should be a significant concern both for operational safety and driver health.

This pilot study evaluated the potential stressors of traffic density and shoulder width in the context of an express BRT service in a large US metropolitan area. In addition, the study considered the potential role of a prototype lane support system (LSS) to support vehicle control within the narrow shoulder boundaries. Ten experienced bus drivers drove an actual route with an instrumented bus equipped with and without LSS. Self-reported effort was recorded along with performance measures of speed and position control relevant to mobility and safety objectives.

Bus drivers did note stressors in the BRT environment and the prototype LSS. However, the use of the shoulder during high-density traffic conditions did improve mobility. Moreover, the LSS did enhance safety on the shoulder when there was high-density traffic in the adjacent lane. However, there was no evidence that the LSS reduced bus driver workload while operating in the narrow shoulder. Future research should consider the impact of BRT operations and support systems on bus driver mental workload and stress, and support the deployment of such devices for bus operations on shoulders during high traffic volumes.     

A fuzzy quality control-decision support system for improving operational reliability of liquid transfer operations in laboratory automation

Quality control in liquid transfer operations can eliminate false assay results due to transfer failures, monitor the stability of laboratory equipment, provide baselines for continuous improvement, and enable automatic recovery actions for a number of fault conditions. This paper describes the work done to add real-time quality control capability in liquid transfer operations on a closed-loop controlled MEMS based liquid transfer device.Real-time data acquisition enables the interpretation of system variables. Using fuzzy logic as a decision support tool, an overall quality metric and failure mode is deduced from these variables for each channel per operation. Detection of ordinary fault conditions like clogged tips or unexpected empty source wells can activate automatic recovery actions without human intervention, leading to 24/7 utilization of an automated laboratory system. Exported quality data can be used for bio-informatics data analysis as well as documentation for regulatory agencies.     

A fuzzy expert system for noise-induced sleep disturbance

In this paper, an attempt has been made to develop a fuzzy expert system for predicting the effects of sleep disturbance by noise on humans as a function of noise level, age, and duration of its occurrence. The modelling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. It has been established on the basis of findings of various researchers that the effect of noise on sleep disturbance depends to a large extent on age. The middle-aged people have more probability of sleep disruption than the young people at the same noise levels. However, very little difference is found in sleep disturbance due to noise between young and old people. In addition, the duration of occurrence of noise is an important factor in determining the sleep disturbance over the limited range from few seconds to few minutes. Finally, we have compared our model results with some of the findings of researchers reported in International Journals.     

Robust adaptive fuzzy logic power system stabilizer

This paper introduces a robust adaptive fuzzy controller as a power system stabilizer (RFPSS) used to damp inter-area modes of oscillation following disturbances in power systems. In contrast to the IEEE standard multi-band power system stabilizer (MB-PSS), robust adaptive fuzzy-based stabilizers are more efficient because they cope with oscillations at different operating points. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, components that ensure robust and adaptive performance are included in the control law to compensate for modelling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearities. The second system is an adaptive one that compensates for modelling errors. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.     

Design of a force reflection controller for telerobot systems using neural network and fuzzy logic

This paper presents a new method for selecting the force-reflection gain in a position-force type bilateral teleoperation system. The force-reflection gain greatly affects the task performance of a teleoperation system; too small gain results in poor task performance while too large gain results in system instability. The maximum boundary of the gain guaranteeing the stability greatly depends upon characteristics of the elements in the system such as: a master arm which is combined with the human operator's hand and the environments with which the slave arm contacts. In normal practice, it is, therefore, very difficult to determine such maximum boundary of the gain. To overcome this difficulty, this paper proposes a force-reflection gain selecting algorithm based on artificial neural network and fuzzy logic. The method estimates characteristics of the master arm and the environments by using neural networks and, then, determines the force-reflection gain from the estimated characteristics by using fuzzy logic. In order to show the effectiveness of the proposed algorithm, a series of experiments are conducted under various conditions of teleoperation using a laboratory-made telerobot system.     

Analysis of assembly operations difficulty: a fuzzy expert system approach

Typical mechanical products can be assembled in various sequences of assembly operations. These sequences have high impact on the assembly time, machine utilization and even on the product quality. In order to select the best sequence of assembly operations, proper evaluation of the various sequences of assembly operations is required. This, in turn, requires the consistent evaluation of each assembly operation in the sequence. The assembly operations can be evaluated for various criteria, of which the operation difficulty is the most meaningful. This paper describes a methodology to analyse the assembly operations and calculates an operation's degree of difficulty using an expert system. This analysis consists of two steps: the first one identifies the main parameters that affect the assembly difficulty and assigns fuzzy triangular values to these parameters. The second step assigns weights to the parameters in order to maximize the agreement with a domain expert. The expert system analyses the difficulty of the assembly operation performed in two orientations: horizontal and vertical. The expert system then assigns a triangular fuzzy number as the aggregate measure of the operation's difficulty.     

防治公交串车的近似动态规划法

公交串车是公交系统运行失效的集中体现。为防治公交串车,建立了公交线路运行的近似动态规划模型,从而实现公交线路的动态自适应式控制。利用Q学习算法和基于人工神经网络近似的价值函数求解上述模型可以得到公交线路控制的最优策略,即基于系统状态确定站点滞留时间的状态价值函数。新的防治方法不仅可以利用仿真模型细致刻画公交线路的实际运行过程,而且可以动态整合在线和离线数据实现控制策略的动态优化调整。数值分析验证了新方法的有效性。与无控制情景相比,新方法可以不仅能防止公交串车发生,而且可有效降低公交车头时距的波动。     

低速总线分析系统的设计实现

提出了一种适用于弹箭的多种总线自动诊断系统,弹上总线诊断分析主要包括对多种总线的电气层和协议层的诊断分析,论述了该诊断系统的方案、硬件架构和软件设计,并阐述了系统实现原理和技术特点;试验表明自动诊断系统能够实时分析多种总线数据的各种电气特性和通信协议,并且能够对总线数据进行实时记录,从而能够全面的对总线进行评价,快速诊断多种总线中差分电压共模电压、显性电压、隐性电压、波特率等主要电气特性参数,提高故障定位和分析的能力和手段.     

A real-time system for pattern recognition of human sleep stages by fuzzy system analysis

A pattern recognition system for the analysis of human sleep stages using the EEG data is presented. The system is designed by using concepts of the fuzzy system analysis and it is implemented in hardware for real-time applications.     

Xrays: A fuzzy expert system for qualitative XRD analysis

This paper describes the development of a fuzzy expert system termed XRAYS for identification of minerals via X-ray diffractograms. The system emulates the well-known (manual) Hanawalt method, thus avoiding the black-box approach of most computer search/match programs. The mineral subfile of the JCPDS Powder Diffraction file is stored in a database, from which the Hanawalt groups are created by the program. The expert system then carries out “manual” search following the steps prescribed for the Hanawalt method. Fuzzy comparisons and fuzzy arithmetic operations are employed in searching for matches. A list of candidate minerals is output in decreasing order of confidence. Graphical comparisons between the unknown pattern and candidate patterns are displayed on the screen to allow the diffractionists to make visual comparison as to the degree of match. Several examples containing from two to six minerals are used for illustration.     

A fuzzy expert system for optimizing parameters and predicting performance measures in hard-milling process

The main focus of research in hard-milling domain has been the enhancement of tool life and the improvement in workpiece surface quality. This paper deals with the application of expert system technology in order to use the experimental data for optimization of milling parameters so as to achieve targets of enhancing tool life and improving workpiece surface finish. Hard-milling experiments were conducted to study the effects of workpiece material hardness, cutter’s helix angle, milling orientation and coolant upon tool life, workpiece surface roughness, and cutting forces. The experimental data were converted to useful information using ANOVA and numeric optimization, and this information was used to develop the knowledge-base in form of IF–THEN rules. Expert system utilized fuzzy logic for its reasoning mechanism, while, fuzzy data sets and crisp sets were freely mixed in antecedents and consequents of the rules. Effectiveness of the expert system was based upon two modules, namely optimization module and prediction module, with each of them operating upon different set of rules. Optimization module provides the optimal selection and combination of aforementioned milling parameters according to the desired objective, while the prediction module provides the prediction of performance measures for the combination of parameters finalized by the optimization module.     

Interval type-2 fuzzy expert system for prediction of carbon monoxide concentration in mega-cities

This paper presents an indirect approach to interval type-2 fuzzy logic system modeling to forecaste the level of air pollutants. The type-2 fuzzy logic system permits us to model the uncertainties among rules and the parameters related to data analysis. In this paper, we propose an indirect method to create an interval type-2 fuzzy logic system from a historical data, where Footprint of Uncertainties of fuzzy sets are extracted by implementation of an interval type-2 FCM algorithm and based on an upper and lower value for the level of fuzziness m in FCM. Finally, the proposed model is applied for prediction of carbon monoxide concentration in Tehran air pollution. It is shown that the proposed type-2 fuzzy logic system is superior in comparison to type-1 fuzzy logic systems in terms of two performance indices.     

A fuzzy PID thermal control system for casting dies

In high-pressure die casting processes, proper control of die temperature is essential for producing superior quality components and yielding high production rates. However, die temperature distribution depends on various die design and process variables for which accurate models are normally very difficult to obtain. In this paper, a new intelligent control scheme is proposed for die thermal management. In this scheme, extra cooling waterlines controlled by a pump and solenoid valves are attached to the established cooling channels. A fuzzy PID controller is designed to minimize the temperature differences between channels. The experimental results obtained from a laboratory die casting process simulator indicate that the developed control system is capable of adjusting the desirable supply of cooling water into multiple cooling lines. Hence, the local temperature distribution of the die insert may become more homogeneous.     

Modelling the software development process using an expert simulation system having fuzzy logic

This paper describes an intelligent computerized tool designed to aid managers of software development projects in planning, managing and controlling the development process of medium- to large-scale software projects. Systems dynamics is used to model and simulate the dynamic process of software development. The software development process is affected by some imprecise and vague variables that are treated as fuzzy variables. The simulation model is integrated with two expert systems. The fuzzy input variables to the system dynamics simulation model are handled by an input expert system having fuzzy logic. This expert system is designed to check the consistency of input variables. The simulation results are analysed by an output expert system having fuzzy logic. This expert system is designed to make recommendations based on experimentation with the simulation model.     

A new GRASS GIS fuzzy inference system for massive data analysis

GIS systems are frequently coupled with fuzzy logic systems implemented in statistical packages. For large GIS data sets including millions or tens of millions of cells, such an approach is relatively time-consuming. For very large data sets there is also an input/output bottleneck between the GIS and external software. The aim of this paper is to present low-level implementation of Mamdani’s fuzzy inference system designed to work with massive GIS data sets, using the GRASS GIS raster data processing engine.     

交流伺服系统模糊滑模控制器设计

针对交流伺服系统的位置控制，设计出一种新型滑模控制器，以前馈信号作为平均控制，采用模糊推理来调节开关控制的幅度，仿真研究表明，该控制器能较好地实现对指令信号的跟踪，具有较强的抗参数摄动和抗干扰能力，表现出良好的控制性能。