Date of Award
2022
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Electrical and Computer Engineering
Committee Chair
Laurie L. Joiner
Committee Member
Yuri Shtessel
Committee Member
Farbod Fahimi
Committee Member
Shangbing Ai
Committee Member
Mark Tillman
Subject(s)
Detectors--Reliability, Sliding mode control
Abstract
Sensor dynamics adversely affect the accuracy of the obtained measurement by dynamically distorting the true value. The accuracy of the measurement may be further degraded by noise/exogenous perturbations. A sensor’s accuracy and performance are improved by reconstructing the true input signal of the sensor from the distorted measurement polluted by a corruption signal or exogenous inputs using Sliding mode and Higher-order sliding mode observer (SMO/HOSMO). The proposed technique is used to reconstruct/estimate a sensor’s true signal, thereby improving the transient response and driving the estimation steady state error to zero in finite time. The proposed SMO algorithm is based on a novel dynamically extended equivalent injection term. In the absence of the measurement corruption term, the sensor dynamics are fully compensated, and the measured signal is exactly reconstructed/estimated in finite time. When the dynamic sensor is perturbed, and the measurement is corrupted by the exogenous signals, the true input signal reconstruction error is estimated. The reconstruction technique also involves the design of a dynamic filter for the proper estimation of the input true signal. The case studies on Planar metal-polymer composite sensor and its simulation results illustrate the efficiency of the proposed techniques to improve the dynamic sensors’ accuracy, performance, and precision.
Recommended Citation
Jayasheelareddy, Rajesh Rayala, "Accuracy improvement of dynamic sensors measured input reconstruction using sliding mode observers" (2022). Dissertations. 242.
https://louis.uah.edu/uah-dissertations/242