Journal of Intelligent & Fuzzy Systems - Volume 3, issue 1

Article Type: Other

DOI: 10.3233/IFS-1995-3110

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. I-I, 1995

Authors: Wang, Fei-Yue | Geng, Z. Jason | Jamshidi, Mo

Article Type: Other

DOI: 10.3233/IFS-1995-3101

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 1-2, 1995

Authors: Cao, Tiehua | Sanderson, Arthur C.

Article Type: Research Article

Abstract: This article proposes a generalized definition of the fuzzy Petri net (FPN) and the reasoning structures of transitions in the FPN. Three types of fuzzy variables, local fuzzy variables, fuzzy marking variables, and global fuzzy variables, are used to model uncertainty based on different aspects of fuzzy information. A fuzzy Petri net is used to model the incomplete, uncertain, and approximate information associated with firing of transitions and changing of states in robotics and manufacturing systems. Using FPNs to model a system, a fuzzy reasoning strategy may be used to infer new fuzzy values in output places after the corresponding …enabled transition is fired. A global fuzzy variable is used to sequence operations with key precedence relations for a manufacturing system. A local fuzzy variable is used to represent the uncertainty in local configuration variables of the system and may be used to control on-line reasoning about sensor-based execution. Several basic types of fuzzy Petri nets are analyzed, and the necessary and/or sufficient conditions of safeness, liveness, and reversibility are given. An example of modeling sensory transitions in a robotic system is discussed to illustrate reasoning about input local fuzzy variables to obtain mutually exclusive tokens in the output places. Show more

DOI: 10.3233/IFS-1995-3102

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 3-19, 1995

Authors: Kumbla, Kishan Kumar | Jamshidi, Mo

Article Type: Research Article

Abstract: This article describes the implementation of hierarchical control on a robotic manipulator using fuzzy logic. A decentralized control approach is implemented, i.e., individual controllers control the two links of the robot. The kinematic aspect of the control is treated as the supervisory mode at a higher level, and the joint control is treated as the lower level. Fuzzy logic based rules determine the inverse kinematic mapping, which maps the Cartesian coordinates to the individual joint angles. This scheme is implemented using Togai Infra Logic software and the entire simulation software is implemented using the “C” language. The results of the …simulation are discussed. This experiment is a proof of the principle that the fuzzy controller can be used to map the nonlinear mapping, which can be implemented to more complex problems of inverse kinematics of higher degree of freedom robots. A fuzzy PD controller is implemented on a Rhino robot. The performance is compared with a traditional PD controller. The fuzzy controller, being an adaptive technique, gives better performance than a traditional linear PD controller over a typical operational range. The fuzzy controller reaches the desired position with no overshoot, which is unlikely with a PD controller. Show more

DOI: 10.3233/IFS-1995-3103

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 21-29, 1995

Authors: Lever, Paul J.A. | Wang, Fei-Vue | Chen, Deqian D. | Shi, Xiaobo

Article Type: Research Article

Abstract: This article describes our initial investigation into using neural networks and fuzzy behaviors for autonomous excavation control of a robotic front-end-loader-type mining machine. To utilize the experience and expertise from skilled human operators, a behavior-control approach based on fuzzy logic is developed. Nine typical behavior programs for general excavation tasks are constructed and implemented with fuzzy logic rules. Two neural networks are built to assess excavation situations and then select the corresponding behavior programs based on force/torque feedback data. Simple strategies for self-evaluation and fusion of fuzzy behaviors are presented. To verify the proposed approach, laboratory experiments are conducted using …a PUMA 560 robot arm, a Zebra force/torque sensor, and a SUN workstation. Experimental results indicate that fuzzy behaviors are capable of reacting to unpredicted events during the excavation process and can complete the desired excavation goals successfully. Show more

DOI: 10.3233/IFS-1995-3104

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 31-42, 1995

Authors: Manikopoulos, Constantine N. | Zhou, MengChu | Nerurkar, Sujit S.

Article Type: Research Article

Abstract: Although many industrial applications of fuzzy logic control have been reported, few of them start with an existing industrial process under conventional PID control implemented with programmable logic controllers (PLCs). This article aims to illustrate to practicing engineers and academic researchers the usefulness of fuzzy logic control through the design and implementation of an industrial heat exchanger in a water-for-injection (WFI) system. After a basic FLC was designed and tested, this article shows how its rule base evolved to achieve superior system performance by utilizing additional low-cost sensing information in the process and its environment. A method for the implementation …of FLCs into the existing PLC is also reported. The system performance of the five designed FLC rule bases is compared with that of the original PID controller. This article concludes that better performance can be achieved by using the fuzzy logic control technology. It reports the authors' experience in FLC design and implementation. Finally, this article discusses some blocking problems in widespread industrial applications of FLCs and the possible solutions to them. Show more

DOI: 10.3233/IFS-1995-3105

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 43-57, 1995

Authors: Baras, John S. | Patel, Nital S.

Article Type: Research Article

Abstract: In this article we derive the rules for a fuzzy logic based PID tuner (expert) for dominant pole systems with large rise times. We present applications of the expert to a third-order plant, separator temperature control, and pH control. It is observed that the expert can successfully tune the PlD gains without requiring any process identification.

DOI: 10.3233/IFS-1995-3106

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 59-69, 1995

Authors: Cellier, François E. | Mugica, Francisco

Article Type: Research Article

Abstract: In this article, a new systematic design methodology for fuzzy controllers is presented. For any desired plant output, it is possible to find off-line the optimal plant input that will produce a plan output that is as close as possible to the desired one. However, this constitutes an open-loop design. In this article, a new methodology is introduced that allows computing a signal on-line that is close to the optimal plant input as a function of system inputs and plant outputs. To this end, an inductive reasoning model is created that estimates the optimal plant input from given system inputs …and plant outputs. The inductive reasoning model can be interpreted and realized as a fuzzy controller. Thereby, a large portion of the controller is realized through feedback, and the previous open-loop design is converted to an equivalent and more robust closed-loop design. The inductive reasoning technique is described in detail in the first part of this article. An example is shown in the second part of the article to demonstrate the validity of the chosen approach. Show more

DOI: 10.3233/IFS-1995-3107

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 71-85, 1995

Authors: Geng, Z. Jason

Article Type: Research Article

Abstract: This article reveals the connection between the cerebellar model arithmetic computer (CMAC) neural network and fuzzy inference systems. A novel artificial neural network architecture called the fuzzy CMAC neural network is established that achieves the synergistic combination of the preferred features of the CMAC neural network and the fuzzy logic controller. The proposed combination of fuzzy logic and neural net techniques has significant potential to decrease the cost, complexity, and learning time over conventional neural nets. It retains the benefits of learning arbitrary functions through training, but it also captures the benefits of fuzzy logic, which allows heuristic rules to …be generated by experts using linguistic variables of meaning to the particular problem domain. We believe that the work herein proposed will produce a generic fuzzy CMAC for a wide range of applications. Show more

DOI: 10.3233/IFS-1995-3108

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 87-102, 1995

Article Type: Other

DOI: 10.3233/IFS-1995-3109

Citation: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 1, pp. 103-105, 1995