Sharif Digital Repository

To achieve high rate of data transfer, tape mechanisms must be able to transport the tape with a constant velocity for scanning. During this process, it is desired to make the rise time minimized without timing and data transfer errors. In this paper, three servo systems including the take-up and supply reel servos for tape tension control and capstan servo for speed control are considered. So, tape transport mechanisms can be described with a nonlinear multi-input multi-output system (MIMO). After state-space representation of the problem, feedback control is designed for tracking objective. It should be mentioned that an increase in the speed of time response of system corresponds to an... 

Active Learning Method (ALM) is a powerful fuzzy soft computing tool, developed originally in order to promote an engineering realization of human brain. This algorithm, as a macro-level brain imitation, has been inspired by some behavioral specifications of human brain and active learning ability. ALM is an adaptive recursive fuzzy learning algorithm, in which a complex Multi Input, Multi Output system can be represented as a fuzzy combination of several Single-Input, Single-Output systems. SISO systems as associative layer of algorithm capture partial spatial knowledge of sample data space, and enable a granular knowledge resolution tuning mechanism through the learning process. The... 

To achieve high rate of data transfer, tape mechanisms must be able to transport the tape with a constant velocity for scanning. During this process, it is desired to make the rise time minimized without timing and data transfer errors. In this paper, three servo systems including the take-up and supply reel servos for tape tension control and capstan servo for speed control are considered. So, tape transport mechanisms can be described with a nonlinear multi-input multi-output system (MIMO). After state-space representation of the problem, feedback control is designed for tracking objective. It should be mentioned that an increase in the speed of time response of system corresponds to an... 

A heuristic nonlinear model predictive controller is proposed, based on the gravitational search algorithm. The proposed method models a constrained nonlinear model predictive control problem in the form of a dynamic optimization and uses a set of virtual particles, moving within the search space, to find the best control sequence in an online manner. Particles affect the movement of each other through the gravitational forces. The optimality of the points, experienced by the particles, is evaluated by a cost function. This function reduces the tracking error, control effort, and control chattering. The better control sequence a particle finds, the more mass is assigned to that particle.... 

Human Brain is one of the most wonderful and complex systems which is designed for ever; A huge complex network composed of neurons as tiny biological and chemical processors which are distributed and work together as a super parallel system to do control and vital activities of human body. Brain learning simulation and hardware implementation is one of the most interesting research areas in order to make artificial brain. One of the researches in this area is Active Learning Method in brief ALM. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specification which models a complex Multi Input Multi Output System as a fuzzy combination of Single Input...