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American Control Conference (ACC)

作者： Liang-Wei Ho G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University USA

Prompted by the increasing demands in system reliability and survivability, fault detection and accommodation has quickly become one of the most active research areas in the intelligent control community. In this work, the necessary and sufficient conditions for system online stability under catastrophic failures have been derived based upon discrete-time Lyapunov stability theory. An online fault accommodation control framework is proposed to deal with the desired trajectory-tracking problem for systems suffering from various unknown and unanticipated catastrophic component failures. The approach is to continuously monitor the system performance and identify the system's current state by using an efficient online fault detection scheme based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, a neural network is suggested as the online estimator to learn and approximate the unknown system failure dynamics. Effective control signals to accommodate the dynamic failures are then computed through the realization of the neural network estimator for the unknown failures based only upon the partially available information of the faults.

关键词： Control systems Fault detection Neural networks Reliability intelligent control Sufficient conditions Stability Lyapunov method Condition monitoring System performance

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Use of clustering to improve performance in fuzzy gene expression analysis

Use of clustering to improve performance in fuzzy gene expre...

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International Joint Conference on Neural Networks (IJCNN)

作者： R. Reynolds H. Ressom M.T. Musavi C. Domnisoru Department of Electrical & Computer Engineering Intelligent Systems Laboratory University of Maine Orono ME USA

ISBN: (纸本)0780370449

This paper proposes the use of fuzzy modeling algorithms to analyze gene expression data. Current algorithms apply all potential combinations of genes to a fuzzy model of gene interaction (for example, activator/inhibitor/target) and are evaluated on the basis of how well they fit the model. However, the algorithm is computationally intensive; the activator/inhibitor model has an algorithmic complexity of O(N/sup 3/), while more complex models (multiple activators/inhibitors) have even higher complexities. As a result, the algorithm takes a significant amount of time to analyze an entire genome. The purpose of this paper is to propose the use of clustering as a preprocessing method to reduce the total number of gene combinations analyzed. By first analyzing how well cluster centers fit the model, the algorithm can ignore combinations of genes that are unlikely to fit. This will allow the algorithm to run in a shorter amount of time with minimal effect on the results.

关键词： Gene expression Performance analysis Inhibitors Algorithm design and analysis Clustering algorithms Differential equations Genomics Bioinformatics Data engineering systems engineering and theory

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Adaptive critic neural network-based object grasping control using a three-finger gripper

Adaptive critic neural network-based object grasping control...

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IEEE Conference on Decision and Control

作者： G. Galan S. Jagannathan Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Robotic grippers that are capable of manipulating objects such as plant trays, fruits, vegetable and so on are required in MARS' greenhouse operation. Grasping and manipulation of objects have been a challenging task for robots. It is important that the manipulator performs these tasks accurately and faster without damaging the object. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact task is defined for the fingers in terms of following a trajectory accurately. On the other hand, the grasping task is defined in terms of maintaining a predefined applied force by the fingers so that the object is properly secured. A sophisticated controller is required for the grasping task since the process of grasping an object without apriori knowledge of the object's size, texture, and softness is rather difficult task. The proposed scheme consists of a feedforward action generating neural network (NN) that compensates for the nonlinear gripper and contact dynamics. The learning of this NN is performed on-line based on a critic signal so that a three-finger gripper track a predefined desired trajectory, which is specified in terms of a desired position and velocity for object contact control while it applies a desired force on the object for grasping. Novel NN weight tuning updates are derived for the action generating NN and a Lyapunov-based stability analysis is presented. Simulation results are shown for a three-finger gripper grasping an object.

关键词： Adaptive systems Programmable control Adaptive control Neural networks Grippers Grasping Robots Fingers Mars Manipulators

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Providing early feedback in the development cycle through automated application of model checking to software architectures 16

Providing early feedback in the development cycle through au...

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16th Annual IEEE International Conference on Automated Software engineering, ASE 2001

作者： Barber, K. Suzanne Graser, Thomas Holt, Jim Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Motorola 7700 West Parmer Lane MD:PL31 AustinTX78729 United States

ISBN: (纸本)076951426X

The benefits of evaluating properties of software architectures stem from two important software architecture roles: (1) providing an opportunity to evaluate requirements and correct defects prior to implementation and (2) serving as a blueprint for system developers. This paper focuses on a new software architecture evaluation tool called Architecture Analysis Dynamic Environment (Arcade) that uses model checking to provide software architecture safety and liveness evaluation during the requirements gathering and analysis phase. Model checking requires expertise not typically held by systems analysts and software developers. Thus, two barriers to applying model checking must be addressed: (1) translation of the software architecture specification to a form suitable for model checking, and (2) interpretation of the results of model checking. Arcade provides an automated approach to these barriers, allowing model checking of software architectures to be added to the list of techniques available to software analysts and developers focusing on requirements gathering and analysis. © 2001 IEEE.

关键词： Model checking

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Congestion control of ATM networks using multilayer neural network approach: multiple source/single switch scenario

Congestion control of ATM networks using multilayer neural n...

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American Control Conference (ACC)

作者： S. Jagannathan J. Talluri Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Technology San Antonio TX USA

This paper proposes an adaptive control methodology using neural networks (NNs) for the available bit rate service class in an ATM network. Adaptive methodology is developed to control traffic where sources adjust their transmission rates in response to the feedback information from the network switches. Specifically, the ATM traffic at a given switch is modeled as a nonlinear discrete-time system, and a two-layer NN controller is designed to prevent congestion. Tuning methods are provided for the NN to estimate the unknown traffic. Mathematical analysis is given to demonstrate the stability of the closed-loop system so that a desired quality of service (QoS) can be guaranteed. No learning phase is required for the NN and initialization of the network weights is straightforward. Simulation results are provided to justify the theoretical conclusions for multiple source/single buffer scenario with and without feedback delays present.

关键词： Multi-layer neural network Neural networks Asynchronous transfer mode Communication system traffic control Traffic control Switches Adaptive control Quality of service Bit rate Adaptive systems

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A hybrid intelligent system for medical diagnosis

A hybrid intelligent system for medical diagnosis

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International Joint Conference on Neural Networks (IJCNN)

作者： P. Meesad G.G. Yen School of Electrical and Computer Engineering Intelligent Systems and Control Laboratory Oklahoma State University Stillwater OK USA

ISBN: (纸本)0780370449

We propose a novel hybrid intelligent system (HIS) that is a combination of numerical and linguistic knowledge representation. The proposed HIS is a hierarchical integration of an incremental learning fuzzy neural network (ILFN) and a fuzzy linguistic model optimized via the genetic algorithm. The ILFN is self-organizing network with the capability of fast, online, incremental learning. The linguistic model is constructed based on knowledge embedded in the trained ILFN. The knowledge captured from the low-level ILFN can be mapped to the higher-level linguistic model and vice versa. The GA is applied to optimize the linguistic model to maintain high accuracy and comprehensibility. The resulted HIS is capable of dealing with low-level numerical computation and higher-level linguistic computation. After the system completely constructed, it can incrementally learn new information in both numerical and linguistic structures. To evaluate the system's performance the well-known benchmark Wisconsin breast cancer data was studied as an application to medical diagnosis. The simulation results show that the proposed HIS perform better than the individual standalone systems.

关键词： Hybrid intelligent systems Medical diagnosis Fuzzy neural networks Knowledge representation Genetic algorithms Self-organizing networks System performance Breast cancer Computational modeling Medical simulation

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Coordination of exploration and exploitation in a dynamic environment

Coordination of exploration and exploitation in a dynamic en...

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International Joint Conference on Neural Networks (IJCNN)

作者： G. Yen Fengming Yang T. Hickey M. Goldstein School of Electrical and Computer Engineering Intelligent Systems and Control Laboratory Oklahoma State University Stillwater OK USA

ISBN: (纸本)0780370449

One much researched issue in reinforcement learning is the trade off between exploration and exploitation. Being able to effectively balance exploration and exploitation activities becomes even more crucial in a dynamic environment. An algorithm is proposed herein that provides one solution to the exploration vs. exploitation dilemma. The algorithm is presented in the context of a path-finding agent in a dynamic grid-world problem. The state-value function used is penalty based, allowing the agent to act over the space of paths with minimal penalties. A forgetting mechanism is implemented that allows the agent to explore paths that were previously determined to be suboptimal. Simulation results are used to analyze the behavior of the proposed algorithm in a dynamic environment.

关键词： Learning systems Genetic algorithms systems engineering and theory intelligent systems intelligent control Control systems Analytical models Algorithm design and analysis Heuristic algorithms Acceleration

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Adaptive critic-based neural network object contact controller for a three-finger gripper

Adaptive critic-based neural network object contact controll...

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IEEE International Symposium on intelligent Control (ISIC)

作者： G. Galan S. Jagannathan Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Texas San Antonio San Antonio TX USA

MAR'S greenhouse operation requires robot arms that are capable of manipulating objects such as plant trays, fruits, vegetables and so on. Grasping and manipulation of objects have been a challenging task for robots. It is important that the manipulator performs these tasks accurately and faster with out damaging the object. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact subtask is defined in terms of following a trajectory accurately so that the object to be grasped is in contact with the gripper. The proposed controller scheme consists of a feedforward action generating neural network (NN) that compensates for the nonlinear gripper and object contact dynamics. The learning of this NN is performed online based on a critic signal so that a 3-finger gripper tracks a predefined desired trajectory, which is specified in terms of a desired position and velocity for object contact control. Novel weight tuning updates are derived for the action generating NN and a Lyapunov-based stability analysis is presented. Simulation results are shown for a 3-finger gripper making contact with an object.

关键词： Adaptive systems Programmable control Adaptive control Neural networks Grippers Robots Manipulators Feedforward neural networks Trajectory Velocity control

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Belief revision process based on trust: Agents evaluating reputation of information sources

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001年 2246卷 73-82页

作者： Suzanne Barber, K. Kim, Joonoo The Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering The University of Texas at Austin AustinTX78722 United States

In this paper, we propose a multi-agent belief revision algorithm that utilizes knowledge about the reliability or trustworthiness (reputation) of information sources1. Incorporating reliability information into belief revision mechanisms is essential for agents in real world multi-agent systems. This research assumes the global truth is not available to individual agents and agents only maintain a local subjective perspective, which often is different from the perspective of others. This assumption is true for many domains where the global truth is not available (or infeasible to acquire and maintain) and the cost of collecting and maintaining a centralized global perspective is prohibitive. As an agent builds its local perspective, the variance on the quality of the incoming information depends on the originating information sources. Modeling the quality of incoming information is useful regardless of the level and type of security in a given system. This paper introduces the definition of the trust as the agent’s confidence in the ability and intention of an information source to deliver correct information and reputation as the amount of trust an information source has created for itself through interactions with other agents. This economical (or monetary) perspective of reputation, viewing reputation as an asset, serves as social law that mandates staying trustworthy to other agents. Algorithms (direct and indirect) maintaining the model of the reputations of other information sources are also introduced. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Bayesian networks

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Meta-reasoning for a distributed agent architecture

Meta-reasoning for a distributed agent architecture

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Southeastern Symposium on System Theory

作者： D. Chelberg L. Welch A. Lakshmikumar M. Gillen Qiang Zhou Laboratory for Intelligent Real-Time and Secure Systems Department of Electrical Engineering and Computer Science Ohio University Athens OH USA

ISBN: (纸本)0780366611

Agent based computing offers the ability to decentralize computing solutions by incorporating autonomy and intelligence into cooperating, distributed applications. It provides an effective medium for expressing solutions to problems that involve interaction with real-world environments and allows modelling of the world state and its dynamics. This model can be then used to determine how candidate actions affect the world and how to choose the best from a set of actions. Most agent paradigms overlook real-time requirements and computing resource constraints. We discuss the application of agent based computing to RoboCup and examine methods to improve it. In particular, we discuss the incorporation of a meta-level reasoning mechanism that handles individual agent organization, plan generation, task allocation, integration and plan execution. We also propose an architecture where a meta-agent is further enhanced by combining it with system-level resource allocation and optimization. The approach adopted by us unifies agent based computing with adaptive resource management for dynamic real-time systems. The goal is to build and implement a distributed, intelligent, agent based system for dynamic real-time applications.

关键词： Quality of service Real time systems Resource management computer architecture Distributed computing intelligent agent Monitoring Laboratories Application software Testing

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