The paper presents a model-based sensor fault detection and isolation system applied in real-time to unmanned ground vehicles. Structural analysis is applied on the nonlinear model of the vehicle for building the residual generation module, followed by an ad-hoc residual evaluation module for detecting single and multiple sensor faults. The overall proposed diagnosis scheme has been tested in realtime on a real mobile robot in an outdoors environment and for different tasks. The obtained experimental results are satisfactory in terms of diagnosis performance and real-time implementation.
Keywords Fault detection • Fault diagnosis • Real-time systems 1 IntroductionThis paper has been motivated by the challenge of deriving a model-based sensor Fault Detection and Isolation (FDI) system to be implemented and tested in realtime on an Unmanned Ground Vehicle (UGV). The conceptual structure of the
In this paper average power consumption, write access time, read access time and retention time of dram cell designs have been analyzed for the nano-meter scale memories. Many modern day processors use dram cell for on chip data and program memory storage. The major power in dram is the off state leakage current. Improving on the power efficiency of a dram cell is critical for the improvement in average power consumption of the overall system. 3T dram cell, 4T dram and 3T1D DRAM cells are designed with the schematic design technique and their average power consumption are compared using TANNER EDA tool .average power consumption, write access time, read access time and retention time of 4T, 3T dram and 3T1D DRAM cell are simulated and compared on 32 nm technology.
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