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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Learning Streams: A Case Study In Curriculum Integration, Mani Mina, Arun K. Somani, Akhilesh Tyagi, Diane T. Rover, Matthew Feldmann, Mack C. Shelley Oct 2005

Learning Streams: A Case Study In Curriculum Integration, Mani Mina, Arun K. Somani, Akhilesh Tyagi, Diane T. Rover, Matthew Feldmann, Mack C. Shelley

Political Science Presentations and Posters

During 2004-2005, the Departments of Electrical and Computer Engineering and Mechanical Engineering at Iowa State University in collaboration with educational colleagues in the Research Institute for Studies in Education piloted a new curricula model to improve student learning through vertical integration of educational activities using new program structures. We offered an experimental course sequence during Fall 2004 and Spring 2005, defined as a “learning stream.” A learning stream is a basic element of a novel program structure designed specifically to vertically integrate subject matter across courses. A learning stream merges and re-organizes material to more effectively present and reinforce key ...


Reinforcement Learning-Based Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani Feb 2005

Reinforcement Learning-Based Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) -based output feedback controller with magnitude constraints is designed to deliver a desired tracking performance for a class of multi-input-multi-output (MIMO) discrete-time strict feedback nonlinear systems. Reinforcement learning in discrete time is proposed for the output feedback controller, which uses three NN: 1) a NN observer to estimate the system states with the input-output data; 2) a critic NN to approximate certain strategic utility function; and 3) an action NN to minimize both the strategic utility function and the unknown dynamics estimation errors. The magnitude constraints are manifested as saturation nonlinearities in the output feedback ...


Work In Progress - Automated Discourse Interventions And Student Teaming, Ray Luechtefeld, Steve Eugene Watkins, Ralph E. Flori Feb 2005

Work In Progress - Automated Discourse Interventions And Student Teaming, Ray Luechtefeld, Steve Eugene Watkins, Ralph E. Flori

Engineering Management and Systems Engineering Faculty Research & Creative Works

The ability to successfully work in teams is a crucial part of an engineer's workplace success. Engineering education can be improved through a better understanding of how effective teamwork develops. A (patent pending) software tool that "listens" to team conversations and generates automatic interventions into team discourse can effectively mimic the actions of a skilled facilitator. Automated facilitation tools may help students improve their team skills by providing a simplified model for conversational interventions, which students can readily imitate. This paper describes this tool and presents preliminary findings from student reactions to the tool's use.


Block Phase Correlation-Based Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani Jan 2005

Block Phase Correlation-Based Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Automatic nanomanipulation and nanofabrication with an Atomic Force Microscope (AFM) is a precursor for nanomanufacturing. In ambient conditions without stringent environmental controls, nanomanipulation tasks require extensive human intervention to compensate for the many spatial uncertainties of the AFM. Among these uncertainties, thermal drift is especially hard to solve because it tends to increase with time and cannot be compensated simultaneously by feedback. In this paper, an automatic compensation scheme is introduced to measure and estimate drift. This information can be subsequently utilized to compensate for the thermal drift so that a real-time controller for nanomanipulation can be designed as if ...


Decentralized Discrete-Time Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani Jan 2005

Decentralized Discrete-Time Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel decentralized neural network (NN) controller in discrete-time is designed for a class of uncertain nonlinear discrete-time systems with unknown interconnections. Neural networks are used to approximate both the uncertain dynamics of the nonlinear systems and the unknown interconnections. Only local signals are needed for the decentralized controller design and the stability of the overall system can be guaranteed using the Lyapunov analysis. Further, controller redesign for the original subsystems is not required when additional subsystems are appended. Simulation results demonstrate the effectiveness of the proposed controller. The NN does not require an offline learning phase and the weights ...


Robotics In Scansorial Environments, Kellar Autumn, Martin Buehler, Mark Cutkosky, Ronald Fearing, Robert J. Full, Daniel Goldman, Richard Groff, William Provancher, Alfred A. Rizzi, Uluc Saranli, Aaron Saunders, Daniel Koditschek Jan 2005

Robotics In Scansorial Environments, Kellar Autumn, Martin Buehler, Mark Cutkosky, Ronald Fearing, Robert J. Full, Daniel Goldman, Richard Groff, William Provancher, Alfred A. Rizzi, Uluc Saranli, Aaron Saunders, Daniel Koditschek

Departmental Papers (ESE)

We review a large multidisciplinary effort to develop a family of autonomous robots capable of rapid, agile maneuvers in and around natural and artificial vertical terrains such as walls, cliffs, caves, trees and rubble. Our robot designs are inspired by (but not direct copies of) biological climbers such as cockroaches, geckos, and squirrels. We are incorporating advanced materials (e.g., synthetic gecko hairs) into these designs and fabricating them using state of the art rapid prototyping techniques (e.g., shape deposition manufacturing) that permit multiple iterations of design and testing with an effective integration path for the novel materials and ...


Special Session - Team Training To Promote Constructive (Not Destructive) Conflict, Ray Luechtefeld, Steve Eugene Watkins Jan 2005

Special Session - Team Training To Promote Constructive (Not Destructive) Conflict, Ray Luechtefeld, Steve Eugene Watkins

Engineering Management and Systems Engineering Faculty Research & Creative Works

Advancing technology increases the need for engineering students to perform effectively on multidisciplinary teams. While conflict is a normal, and even necessary, component of team dynamics, if not managed effectively it can lead to destructive (rather than constructive) outcomes. An Action Science approach to group and individual effectiveness can help teams handle conflict constructively. This session uses a "Teach the Teacher" approach to give participants a basic understanding of skills underlying the approach. It provides practice in Action Science through a set of learning modules. These skills can be brought back and integrated into the participants' courses to provide student ...


Taxonomy Of Systems-Of-Systems, James Gideon, Cihan H. Dagli, Ann K. Miller Jan 2005

Taxonomy Of Systems-Of-Systems, James Gideon, Cihan H. Dagli, Ann K. Miller

Engineering Management and Systems Engineering Faculty Research & Creative Works

The study of systems-of-systems is an increasingly important topic in systems engineering. Though there is not complete agreement, a more precise definition of what these highly evolved systems are and what attributes they possess has certainly emerged. However, there are still areas in the study where the topic can be advanced by a more rigorous presentation of the basic elements. One such area is the taxonomy of systems-ofsystems. This paper will begin with the definition of systems-of-systems as it currently stands and will present the taxonomy from a broader view with additional considerations for classification. These taxonomic categories will consider ...


A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani Jan 2005

A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A suite of novel robust controllers is presented for the manipulation and handling of micro-scale objects in a micro-electromechanical system (MEMS) where adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The robust controller overcomes the unknown system dynamics and ensures the performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive controller, the unknown forces are estimated online. Using the Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop manipulation error is shown for ...


Energy-Efficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2005

Energy-Efficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Resource constraints in ad hoc wireless networks require that they are energy efficient during both transmission and rate adaptation. In this paper, we propose a novel energy-efficient rate adaptation protocol that selects modulation schemes online to maximize throughput based on channel state while saving energy. This protocol uses the distributed power control (DPC) algorithm (M. Zawodniok et al., 2004) to accurately determine the necessary transmission power and to reduce the energy consumption. Additionally, the transmission rate is altered using energy efficiency as a constraint to meet the required throughput, which is estimated with queue fill ratio. Moreover, back-off scheme is ...


Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He Jan 2005

Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement learning-based adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to deliver a desired tracking performance for a class of non-strict feedback nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The adaptive critic NN controller architecture includes a critic NN and two action NNs. The critic NN approximates certain strategic utility function whereas the action neural networks are used to minimize both the strategic utility function and the unknown dynamics estimation errors. The NN weights are tuned online so as to minimize certain performance index. By using gradient descent-based ...


Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2005

Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated ...