Journal of Intelligent & Fuzzy Systems - Volume 4, issue 2

Article Type: Other

DOI: 10.3233/IFS-1996-4209

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. I-I, 1996

Authors: Wang, Danwei | Soh, Y.C. | Gu, Mingkun

Article Type: Research Article

Abstract: Kinematic redundancy enables a robot to change its joint configuration without changing the position of the end effector of the robot. In addition to the requirement of path tracking in Cartesian space, many tasks require a manipulator to achieve more than one performance criteria or take into account some manipulation constraints. In this article, a fuzzy logic approach is proposed for the desired joint path generation for redundant manipulators with consideration of multiple criteria. Performance criteria are fuzzified and their relative importance is introduced. The desired joint path is determined based on the relative importance of various criteria and the …satisfaction measures of each candidate joint path to all criteria by a fuzzy logic multiple criteria decision making process. Simulation results are presented to demonstrate that the proposed method can generate a path that can satisfy two performance criteria. Show more

DOI: 10.3233/IFS-1996-4201

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 89-99, 1996

Authors: Lee, Chul-Heui | Yager, Ronald R.

Article Type: Research Article

Abstract: A new variable step size least mean squares (LMS) algorithm using fuzzy logic (FVSS-LMS) is presented. The change of the step size at each iteration, which increases or decreases according to the degree of misadaption, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed while preserving low misadjustment. The norm of the cross correlation between the estimation error and input data is used as a measure of misadaption. Simulation results are presented to verify the performance of the proposed algorithm.

DOI: 10.3233/IFS-1996-4202

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 101-106, 1996

Authors: Neo, S.S. | Er, M.J.

Article Type: Research Article

Abstract: The performance of two adaptive robot control algorithms, namely the adaptive algorithm by Slotine and Li and the proposed direct adaptive fuzzy control algorithm, were studied. In Slotine and Li's method, the algorithm consists of proportional derivative feedback and a full dynamics feed forward part, with the unknown manipulator and payload parameters being estimated on-line. The algorithm depends heavily on the particular structure of manipulator dynamics and needed three simplifying properties to derive the adaptive law. The direct adaptive fuzzy algorithm uses a fuzzy logic system as the controller. The derivation of the controller does not require any knowledge of …the manipulator dynamics and the uncertainty in the system, only the boundary of the dynamics. The predominant concern of the two adaptation laws is to reduce the tracking errors. In particular, they require no feedback of joint accelerations. Theoretical results and simulation studies on a two-link robot manipulator show that both methods are robust and stable. The direct adaptive fuzzy controller outperforms the adaptive controller in mass variation. Show more

DOI: 10.3233/IFS-1996-4203

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 107-119, 1996

Authors: Kleyle, R. | de Korvin, A.

Article Type: Research Article

Abstract: In this article we consider a situation in which an item (e.g., some type of equipment) can be in one of several states defined in terms of the attributes of the item. Some states are desirable and some are not. The goal is to take some action designed to improve the state of the item. A policy is a rule defining what action to take depending upon the state that the item currently occupies. Thus, we encounter a situation that can be modeled by a finite state Markov chain. However, due to uncertainty concerning the effectiveness of any course of …action, precise transition probabilities are replaced with linguistic terms. Thus, the matrix of transition probabilities is fuzzy. For the same reason, the initial state probability vector can also be fuzzy. Furthermore, associated with each course of action is a cost that may in part depend on the ultimate outcome of the action taken. Again, due to uncertainty, costs may also be expressed linguistically causing the cost matrix to be fuzzy. The methodology described here establishes a procedure for associating a fuzzy expected cost with each policy. Then, after defuzzification, the policy with the smallest expected cost is selected. Show more

DOI: 10.3233/IFS-1996-4204

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 121-130, 1996

Authors: Dounis, A.I. | Bruant, M. | Santamouris, M. | Guarracino, G. | Michel, P.

Article Type: Research Article

Abstract: This article compares various techniques for the control of indoor air quality in a naturally ventilated building: ON-OFF, proportional-integral-derivative (PID), proportional-integral with deadband (PIdb), and fuzzy control. The control system for the fuzzy controllers is a typical two input (carbon dioxide concentration and its time derivative), one output (change in window opening area) system. Two different fuzzy controllers are modeled: one based on Mamdani's max-min inference, and the other using Gupta's multivariable structure. The results show that the fuzzy controllers and the Pldb controller are much more suitable than the PID or the ON-OFF controllers. The number of cycles of …the controlled parameter (i.e., the window opening fluctuations) is actually much smaller. Minor differences between the two fuzzy controllers are observed. Show more

DOI: 10.3233/IFS-1996-4205

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 131-140, 1996

Authors: Chelette, Tamara L. | Repperger, Daniel W. | Phillips, Chandler A.

Article Type: Research Article

Abstract: This article involves an application of an intelligent control system in biomedical engineering specifically dealing with patients who have difficulty in making smooth commanded arm motions. Individuals who experience random motor spasms during forearm motion were selected from diagnostic groups including head trauma, cerebrovascular accident, and cerebral palsy. An engineering analysis technique involving pursuit target tracking examination in the error phase plane provided distinct insight into the unique characteristics of uncommanded motion. Approximate reasoning, or fuzzy logic, is applied to the problem of recognition of an uncommanded motion of the forearm. Two fuzzy logic pattern recognition algorithms are presented as …potential devices to distinguish between commanded and uncommanded motion. The fuzzy logic approach in the error phase plane is shown to have fairly good results, while the acceleration-velocity phase plane has reduced information and provides results that are less reliable. These patterns are then used as the basis for a proposed adoptive controller that would assist the individual in overcoming the motor spasm and returning to useful control. Show more

DOI: 10.3233/IFS-1996-4206

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 141-160, 1996

Authors: Patyra, Marek J. | Braun, Eric | VanMeeteren, Mike

Article Type: Research Article

Abstract: This article discusses the design and development of a high-speed digital defuzzifier circuit that can be used as a stand alone chip associated with a conventional or fuzzy logic processor or as a macrofunctional block built into the fuzzy logic processor chip. As a case example, the presented defuzzifier circuit is designed to have 64*5 bit input data bus and 32 bit output data bus. The choice of the input/output data bus size is arbitrary and the design can be modified according to the user's needs. The output data bus, representing the scalar output value, is organized in such a …way that the first 8 bits represent the real number and the remaining 24 bits represent its fraction. The accuracy of the defuzzification equals 11256. The defuzzifier is pipelined to assist in higher throughput, and therefore, for a used technology (n-well 1.2-μm CMOS) its maximum frequency of operation is 100 MHz. This means that as soon as the pipeline is filled, the defuzzifier reads 64*5 bit fuzzy input and generates the 32-bit scalar output every 10 ns. This defuzzifier, as an element of the fuzzy logic controller design, was simulated at the postlayout stage of development. Show more

DOI: 10.3233/IFS-1996-4207

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 161-173, 1996

Authors: Filev, Dimitar P.

Article Type: Book Review

DOI: 10.3233/IFS-1996-4208

Citation: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 175-176, 1996