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Operations Research, Systems Engineering and Industrial Engineering Commons

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Series

Missouri University of Science and Technology

Lyapunov Methods

2006

Articles 1 - 2 of 2

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

Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani Jan 2006

Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In radio frequency identification (RFID) systems, the detection range and read rates will suffer from interference among high power reading devices. This problem grows severely and degrades system performance in dense RFID networks. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a desired read rate. The power control scheme and MAC protocol dynamically adjusts the RFID reader power output in response to the interference level seen locally during tag reading for an acceptable signal-to-noise ratio (SNR). We present novel distributed adaptive power control (DAPC) and probabilistic …


Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He Jan 2006

Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …