چكيده به لاتين
Abstract:
Most of the control systems are nonlinear and include so many uncertainties, which makes obtaining
a precise mathematic model very difficult. Inordinate number of controlling methods have been
introduced for overcomming this issue, with ”adaptive fuzzy sliding mode controller(AFSMC)”
being the most successful nonlinear method among all. In this dissertation, this method is designed
for controlling a nonlinear multi input-multi output system with an asymmetric gain matrice, with
some of its state variables not being directly connected to the input. Based on fuzzy system and rubost
controller combination, a direct adaptive fuzzy sliding mode controller algorithm is proposed
which is appropirate for applying on nonlinear and unknown systems. Fuzzy system is used to estimate
ideal sliding mode controller, and rubost controller is designed to counteract uncertainties
such as fuzzy estimation error and external disturbances. This method is developed for applying it
on MIMO systems which input does not explicitly appear in some subsystems. Furthermore; in order
to attain a more desired performance and consider interactions between subsystems in a MIMO
system, the AFSMC method has been refined by employing a series of normalization factors for the
output of fuzzy system. Pitch plane dynamics of a supercavitating underwater vehicle is considered
as a case study for our proposed controller assessment. System of equations of these vehicles has an
asymmetric gain matrice, and some of the state variables are not directly affected by input, which
is a desired condition for this dissertation. By using supercavitating phenomenon, which envelopes
the vehicle like a gaseuos bubble the drag force acting from water on the vehicle body is so reduced
that leads to substantive increase in its velocity. This supercavity possesses complex and nonlinear
dynamics with strong memory effects (delay) that cause major challenges against stability, maneuverability,
and control to the system, which evidently indicates the importance of an appropriate
control strategy selection. Hense; the proposed controller is applied on this vehicle -as a suitable
and challenging system- and the simulation results are studied.
Keywords: adaptive fuzzy sliding mode controller, AFSMC, High-speed supercavitating underwater
vehicle, HSSUV
