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Computer Sciences

Electrical and Computer Engineering Faculty Research & Creative Works

2003

Articles 1 - 6 of 6

Full-Text Articles in Engineering

One-Layer Neural-Network Controller With Preprocessed Inputs For Autonomous Underwater Vehicles, Sarangapani Jagannathan, Gustavo Galan Sep 2003

One-Layer Neural-Network Controller With Preprocessed Inputs For Autonomous Underwater Vehicles, Sarangapani Jagannathan, Gustavo Galan

Electrical and Computer Engineering Faculty Research & Creative Works

Navigating, guiding, and controlling autonomous underwater vehicles (AUVs) are challenging and difficult tasks compared to the autonomous surface-level operations. Controlling the motion of such vehicles require the estimation of unknown hydrodynamic forces and moments and disturbances acting on these vehicles in the underwater environment. in this paper, a one-layer neural-network (NN) controller with preprocessed input signals is designed to control the vehicle track along a desired trajectory, which is specified in terms of desired position and attitude. in the absence of unknown disturbances and modeling errors, it is shown that the tracking error system is asymptotically stable. in the presence …

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Million City Traveling Salesman Problem Solution By Divide And Conquer Clustering With Adaptive Resonance Neural Networks, Samuel A. Mulder, Donald C. Wunsch Jan 2003

Million City Traveling Salesman Problem Solution By Divide And Conquer Clustering With Adaptive Resonance Neural Networks, Samuel A. Mulder, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

The Traveling Salesman Problem (TSP) is a very hard optimization problem in the field of operations research. It has been shown to be NP-complete and is an often-used benchmark for new optimization techniques. One of the main challenges with this problem is that standard, non-AI heuristic approaches such as the Lin-Kernighan algorithm (LK) and the chained LK variant are currently very effective and in wide use for the common fully connected, Euclidean variant that is considered here. This paper presents an algorithm that uses adaptive resonance theory (ART) in combination with a variation of the Lin-Kernighan local optimization algorithm to …

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Rate-Based End-To-End Congestion Control Of Multimedia Traffic In Packet Switched Networks, Mingsheng Peng, S. R. Subramanya, Jagannathan Sarangapani Jan 2003

Rate-Based End-To-End Congestion Control Of Multimedia Traffic In Packet Switched Networks, Mingsheng Peng, S. R. Subramanya, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an explicit rate-based end-to-end congestion control mechanism to alleviate congestion of multimedia traffic in packet switched networks such as the Internet. The congestion is controlled by adjusting the transmission rates of the sources in response to the feedback information from destination such as the buffer occupancy, packet arrival rate and service rate at the outgoing link, so that a desired quality of service (QoS) can be met. The QoS is defined in terms of packet loss ratio, transmission delay, power, and network utilization. Comparison studies demonstrate the effectiveness of the proposed scheme over New-Reno TCP (a variant …

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Adaptive Critic Neural Network-Based Controller For Nonlinear Systems With Input Constraints, Pingan He, Sarangapani Jagannathan Jan 2003

Adaptive Critic Neural Network-Based Controller For Nonlinear Systems With Input Constraints, Pingan He, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel adaptive critic-Based multilayer neural network (NN) controller in discrete-time is designed to deliver a desired tracking performance for a class of nonlinear systems in the presence of magnitude constraints on the input. Reinforcement learning scheme in discrete time is proposed for the NN controller, where the action generating NN learning is performed based on a certain performance measure, which is supplied from a critic. using the Lyapunov approach and with a novel weight update, the uniform ultimately boundedness (UUB) of the closed loop tracking error and weight estimates are shown. the adaptive critic NN does not require an …

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Welcome To The Special Issue: The Best Of The Best, Donald C. Wunsch, Mike Hasselmo, De Liang Wang, Ganesh K. Venayagamoorthy Jan 2003

Welcome To The Special Issue: The Best Of The Best, Donald C. Wunsch, Mike Hasselmo, De Liang Wang, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani Jan 2003

Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control …

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