Time Optimal Control for a Class of Common Random Disturbances

1970 ◽  
Vol 92 (2) ◽  
pp. 197-203
Author(s):  
R. Oldenburger ◽  
N. P. Smith

This paper concerns the time optimal control of a system variable where the controlling input is bounded, as is usually the case, and the system is subject to arbitrary disturbances. An arbitrary disturbance is made up of uncontrollable portions followed by controllable sections. In industrial practice controllers are sized, as for example as to power, to fit the system so that the disturbances encountered are primarily made up of uncontrollable sections followed by controllable portions of sufficient duration for the controller to bring the system to equilibrium. The control designer wishes to have optimal control for any disturbance made up of such an uncontrollable portion followed by a sufficiently long controllable section. Here this problem is solved with the aid of the maximum principle for the class of second order systems which describe almost all governor-engine applications to first approximation accuracy. Previous attempts to solve this problem involved assuming statistical properties of the disturbance thus severely restricting the class of applications. Here only those statistical properties required to implement optimal control are determined. A single control function is derived which suffices to yield optimal trajectories.

Author(s):  
Ivan Matychyn ◽  
Viktoriia Onyshchenko

AbstractThe problem of time-optimal control of linear systems with fractional dynamics is treated in the paper from the convex-analytic standpoint. A linear system of fractional differential equations involving Riemann- Liouville derivatives is considered. A method to construct a control function that brings trajectory of the system to the terminal state in the shortest time is proposed in terms of attainability sets and their support functions


1991 ◽  
Vol 113 (3) ◽  
pp. 363-370 ◽  
Author(s):  
W. S. Newman ◽  
K. Souccar

A technique is presented for controlling second-order, nonlinear systems using a combination of bang-bang time-optimal control, sliding-mode control, and feedback linearization. Within the control loop, a state space evaluation of the system classifies the instantaneous dynamics into one of three regions, and one of three corresponding control algorithms is invoked. Using a prescribed generation of desirable sliding surfaces, the resulting combined controller produces nearly time-optimal performance. The combination controller is provably stable in the presence of model uncertainty. Experimental data are presented for the control of a General Electric GP132 industrial robot. The method is shown to achieve nearly time-optimal motion that is robust to modeling uncertainties. Representative transients compare favorably to bang-bang control and PD control.


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