controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy REINFORCEMENT LEARNING AND OPTIMAL CONTROL METHODS FOR UNCERTAIN NONLINEAR SYSTEMS By Shubhendu Bhasin August 2011 Chair: Warren E. Dixon Major: Mechanical Engineering Notions of optimal behavior expressed in natural systems led research...

Neuromodulation is central to the adaptation and robustness of animal nervous systems. This paper explores classical paradigm indirect adaptive control design neuromodulatory controllers in conductance-based neuronal models. The maximal conductance parameters shown provide a methodology aligned with concepts neuromodulation physiology impedance robotics.

The paper presents the possibility of management fan performance in dependence on CO2 concentration. A mathematical calculation is made from prediction electric energy consumption for a variant control algorithm. most advantageous algorithm programmed into actual system, and its power shown graph. Finally, saving adaptive compared to classical over time. To program algorithm, mass balance equat...