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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- Neurocontrollers (12)
- Lyapunov Methods (10)
- Nonlinear Control Systems (9)
- Adaptive Control (8)
- Closed Loop Systems (8)
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- Control System Synthesis (7)
- Discrete-time systems (6)
- Learning (Artificial Intelligence) (6)
- Neural Networks (6)
- Discrete Time Systems (5)
- Neural Network (5)
- Adaptive Systems (4)
- Decentralized Control (4)
- Lyapunov Method (4)
- Observers (4)
- Access Protocols (3)
- Complex Networks (3)
- Distributed Power Control (3)
- Embedded Systems (3)
- Feedback (3)
- Formation Control (3)
- Learning Systems (3)
- Neural Networks (NNs) (3)
- Nonlinear control theory (3)
- Optimal Control (3)
- Power System Control (3)
- Telecommunication Congestion Control (3)
- Wireless Sensor Network (3)
- Adaptive Critic (2)
- Congestion Control (2)
Articles 61 - 65 of 65
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani
A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel distributed power control (DPC)⋅ scheme and a MAC protocol for wireless ad hoc networks in the presence of radio channel uncertainties such as path loss, Shadowing and Rayleigh fading is presented. The DPC quickly estimates the time-varying nature of the channel and uses the information to select a suitable transmitter power value in order to maintain a target Signal-to-Interference ratio (SIR) at the receiver. The standard assumption of a constant interference during a link's power update used in other works is relaxed. The performance of the proposed DPC is demonstrated analytically. The power used for all RTS-CTS-DATA-ACK frames …
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement learning-based neural network (RLNN) controller is presented for the manipulation and handling of micro-scale objects in a microelectromechanical system (MEMS). In MEMS, adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The RLNN controller consists of an action NN for compensating the unkoown system dynamics, and a critic NN to tune the weights of the action NN. Using the Lyapunov approach, the uniformly ultimate houndedness (UUB) of the closed-loop tracking error and weight estimates are shown by using a novel weight updates. Simulation results are presented to substantiate the …
Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani
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 …
Rate-Based End-To-End Congestion Control Of Multimedia Traffic In Packet Switched Networks, Mingsheng Peng, S. R. Subramanya, Jagannathan Sarangapani
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 …
Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan
Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan
Electrical and Computer Engineering Faculty Research & Creative Works
A multilayer neural network (NN) controller in discrete-time is designed to deliver a desired tracking performance for a class of nonlinear systems with input deadzones. This multilayer NN controller has an adaptive critic NN architecture with two NNs for compensating the deadzone nonlinearity and a third NN for approximating the dynamics of the nonlinear system. A reinforcement learning scheme in discrete-time is proposed for the adaptive critic NN deadzone compensator, where the learning is performed based on a certain performance measure, which is supplied from a critic. The adaptive generating NN rejects the errors induced by the deadzone whereas a …