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Linear parameter varying representat...

Carter, Lance Huntington.

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Linear parameter varying representations for nonlinear control design.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Linear parameter varying representations for nonlinear control design./
Author:	Carter, Lance Huntington.
Description:	89 p.
Notes:	Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3387.
Contained By:	Dissertation Abstracts International60-07B.
Subject:	Engineering, Aerospace. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9936985
ISBN:	0599382996

Linear parameter varying representations for nonlinear control design.
Carter, Lance Huntington.

Linear parameter varying representations for nonlinear control design. - 89 p.

Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3387.

Thesis (Ph.D.)--The University of Texas at Austin, 1998.

Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an <italic>a priori </italic> unknown but measurable exogenous parameter.

ISBN: 0599382996Subjects--Topical Terms:

1018395
Engineering, Aerospace.

Linear parameter varying representations for nonlinear control design.
LDR:03155nam 2200313 a 45 001 929632
005 20110427
008 110427s1998 eng d
020 $a 0599382996
035 $a (UnM)AAI9936985
035 $a AAI9936985
040 $a UnM $c UnM
100 1 $a Carter, Lance Huntington. $3 1253119
245 1 0 $a Linear parameter varying representations for nonlinear control design.
300 $a 89 p.
500 $a Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3387.
500 $a Supervisor: Jeff S. Shamma.
502 $a Thesis (Ph.D.)--The University of Texas at Austin, 1998.
520 $a Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an <italic>a priori </italic> unknown but measurable exogenous parameter.
520 $a A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as “exogenous” parameters. These are actually endogenous variables, so such a plant is called “quasi-LPV.” Once in quasi-LPV form, a family of robust controllers using μ synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients.
520 $a Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control.
520 $a LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that neglects a subset of possible parameter trajectories. A computational algorithm is constructed for this suboptimal solution applied to a class of linear non-quadratic cost functions.
590 $a School code: 0227.
650 4 $a Engineering, Aerospace. $3 1018395
650 4 $a Engineering, Automotive. $3 1018477
690 $a 0538
690 $a 0540
710 2 0 $a The University of Texas at Austin. $3 718984
773 0 $t Dissertation Abstracts International $g 60-07B.
790 $a 0227
790 1 0 $a Shamma, Jeff S., $e advisor
791 $a Ph.D.
792 $a 1998
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9936985