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Full-Text Articles in Controls and Control Theory
Comparison Of Two Distributed Fuzzy Logic Controllers For Flexible-Link Manipulators, Linda Z. Shi, Mohamed Trabia
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
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.
Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay
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
Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo
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.