Award Date

1-1-2007

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical and Computer Engineering

First Committee Member

Sahjendra N. Singh

Number of Pages

103

Abstract

Autonomous underwater vehicles (AUVs) are used for numerous applications in the deep sea, such as hydrographic survey, sea bed mining and oceanographic mapping, etc. Presently, significant amount of effort, is being made in developing biorobotic AUVs (BAUVs) with biologically inspired control surfaces. However, the dynamics of AUVs and BAUVs are highly nonlinear and the hydrodynamic coefficients are not precisely known. As such the development of nonlinear and adaptive control systems is of considerable importance; We consider the suboptimal dive plane control of AUVs using the state-dependent Riccati equation (SDRE) technique. This method provides effective means of designing nonlinear control systems for minimum as well as nonminimum phase AUV models. Moreover, hard control constraints are included in the design process; We also attempt to design adaptive control systems for BAUVs using biologically-inspired pectoral-like fins. The fins are assumed to be oscillating harmonically with a combined linear (sway) and angular (yaw) motion. The bias (mean) angle of the angular motion of the fin is used as a control input. Using discrete-time state variable representation of the BAUV, adaptive sampled-data control systems for the trajectory control are derived using state feedback as well as output feedback. We develop direct as well as indirect adaptive control systems for BAUVs. The advantage of the indirect adaptive law lies in its applicability to minimum as well as nonminimum phase systems. Simulation results are presented to evaluate the performance of each control system.

Keywords

Adaptive; Autonomous; Control; Fin; Nonlinear; Pectoral; Suboptimal; Underwater; Vehicle

Controlled Subject

Electrical engineering; Ocean engineering

File Format

pdf

File Size

2723.84 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/b8qv-dfn6


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