Controls and Control Theory Commons^™

Decoupling And Disturbance Rejection Control For Target Circulation, Jian Ma, Joon S. Lee, Woosoon Yim

Reactor Campaign (TRP)

The Target Complex loop TC-1 was originally conceived as part of an accelerator-driven system (ADS) pilot plant that was designed and developed by the Institute of Physics and Power Engineering (IPPE) and Experimental and Development Organization (EDO) “Gidropress” in Obninsk, Russia, under the International Science and Technology Center Project #559 in 1998. It was to be used as the target in a 1 MWth ADS experiment run off of the LANSCE proton accelerator at Los Alamos National Laboratory (LANL). When the U.S. transmutation program changed priorities from accelerator-driven systems towards nuclear fission reactors, the TC-1 loop was brought to UNLV …

Decoupling And Disturbance Rejection Control For Target Circulation, Jian Ma, Joon S. Lee, Woosoon Yim

Reactor Campaign (TRP)

In 1998, the Institute of Physics and Power Engineering (IPPE) and Experimental and Development Organization “Gidropress” in Russia, began the design and construction of a prototype lead-bismuth eutectic (LBE) accelerator target, the Target Complex 1 (TC-1), under the International Science and Technology Center (ISTC) project #559 (“Pilot Flow Lead-Bismuth Target of 1 MW Power for Accelerator Driven Systems”) in support of the international efforts to develop accelerator-driven spallation systems for nuclear transmutation and other applications.

During the thermal and engineering test of the TC-1 in 2005 at UNLV, it was observed that the existing control algorithm led to a very …

A Fuzzy Logic Controller For Autonomous Wheeled Vehicles, Mohamed Trabia, Linda Z. Shi, Neil Eugene Hodge

Mechanical Engineering Faculty Research

Autonomous vehicles have potential applications in many fields, such as replacing humans in hazardous environments, conducting military missions, and performing routine tasks for industry. Driving ground vehicles is an area where human performance has proven to be reliable. Drivers typically respond quickly to sudden changes in their environment. While other control techniques may be used to control a vehicle, fuzzy logic has certain advantages in this area; one of them is its ability to incorporate human knowledge and experience, via language, into relationships among the given quantities. Fuzzy logic controllers for autonomous vehicles have been successfully applied to address various …

A Fast And Simple Algorithm For Computing M Shortest Paths In Stage Graph, M. Sherwood, Laxmi P. Gewali, Henry Selvaraj, Venkatesan Muthukumar

Electrical & Computer Engineering Faculty Research

We consider the problem of computing m shortest paths between a source node s and a target node t in a stage graph. Polynomial time algorithms known to solve this problem use complicated data structures. This paper proposes a very simple algorithm for computing all m shortest paths in a stage graph efficiently. The proposed algorithm does not use any complicated data structure and can be implemented in a straightforward way by using only array data structure. This problem appears as a sub-problem for planning risk reduced multiple k-legged trajectories for aerial vehicles.

Comparison Of Two Distributed Fuzzy Logic Controllers For Flexible-Link Manipulators, Linda Z. Shi, Mohamed Trabia

Mechanical Engineering Faculty Presentations

The paper suggests that fuzzy logic controllers present a computationally efficient and robust alternative to conventional controllers. The paper presents two possible structures for the distributed fuzzy logic controller of a single-link flexible manipulator. A linear quadratic regulator method is used to prove the effectiveness of fuzzy logic controllers.

Design Of Fuzzy Logic Controllers For Optimal Performance, Mohamed Trabia

Mechanical Engineering Faculty Presentations

While fuzzy logic controllers are generally robust, the performance of a system whose behavior is not well understood, or that has a large number of coupled inputs and outputs, may be less than optimal. In this paper, nonlinear programming techniques are used to improve the performance of a fuzzy logic controller for navigating an autonomous vehicle.

Overview Of Fuzzy Logic, Mohamed Trabia

Mechanical Engineering Faculty Presentations

The presentation includes a brief introduction to fuzzy logic and fuzzy logic controllers. These concepts are illustrated by an example of an autonomous vehicle controller.

Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove

Electrical & Computer Engineering Faculty Research

This paper presents a feedback control design for isolated ramp metering control. This feedback control design, unlike the existing isolated feedback ramp controllers, also takes into account the ramp queue length. Using a nonlinear H∞ control design methodology, we formulate the problem in the desired setting to be able to utilize the results of the methodology.

Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results

Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

This paper presents an effort to validate the traffic incident duration estimation model of WAIMSS (wide area incident management support system). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northern Virginia. Due to the limited sample size, a full scale test of the distribution, mean and variance of incident duration was performed only for the root node of the estimation tree, white only mean tests were executed at all other nodes whenever a data subset was available. Further studies were also conducted on the model error …

Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …

Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.

Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.