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Design of Optimal Strictly Positive Real Controllers Using Numerical Optimization for the Control of Large Flexible Space StructuresForbes, James Richard 30 July 2008 (has links)
The design of optimal strictly positive real (SPR) compensators using numerical optimization
is considered. The plants to be controlled are linear and nonlinear flexible manipulators.
For the design of SISO and MIMO linear SPR controllers, the optimization
objective function is defined by reformulating the H2-optimal control problem subject
to the constraint that the controllers must be SPR. Various controller parameterizations
using transfer functions/matrices and state-space equations are considered. Depending
on the controller form, constraints are enforced (i) using simple inequalities guaranteeing
SPRness, (ii) in the frequency domain, or (iii) by implementing the Kalman-Yakubovich-
Popov lemma. The design of a gain-scheduled SPR controller using numerical optimization
is also considered. Using a family of linear SPR controllers, the time dependent
scheduling signals are parameterized, and the objective function of the optimizer seeks
to find the form of the scheduling signals which minimizes the manipulator tip tracking
error while minimizing the control effort.
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2 |
Design of Optimal Strictly Positive Real Controllers Using Numerical Optimization for the Control of Large Flexible Space StructuresForbes, James Richard 30 July 2008 (has links)
The design of optimal strictly positive real (SPR) compensators using numerical optimization
is considered. The plants to be controlled are linear and nonlinear flexible manipulators.
For the design of SISO and MIMO linear SPR controllers, the optimization
objective function is defined by reformulating the H2-optimal control problem subject
to the constraint that the controllers must be SPR. Various controller parameterizations
using transfer functions/matrices and state-space equations are considered. Depending
on the controller form, constraints are enforced (i) using simple inequalities guaranteeing
SPRness, (ii) in the frequency domain, or (iii) by implementing the Kalman-Yakubovich-
Popov lemma. The design of a gain-scheduled SPR controller using numerical optimization
is also considered. Using a family of linear SPR controllers, the time dependent
scheduling signals are parameterized, and the objective function of the optimizer seeks
to find the form of the scheduling signals which minimizes the manipulator tip tracking
error while minimizing the control effort.
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