This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers more realistic, the testing signals have been applied by a user
through a joystick interfaced to the computer. The results obtained indicated a general superiority in
performance for the Fuzzy PID controller over the PID controller used in this work. This conclusion
is based by the following figures: lesser ISA for the roll, pitch, and yaw
consequently, lesser IAE for the roll, pitch, and yaw consequently,
lesser rise time and settling time for the roll and pitch consequently, and
lesser settling time for the yaw. Moreover, the FPID gave zero overshoot versus , ,
and in the PID case for the roll, pitch, and yaw consequently. Both controllers gave zero steady
state error with close rise times for the yaw. This superiority of the FPID controller is gained as the
fuzzy part of it continuously and online adapts the parameters of the PID part.
In this paper, an ecological model with stage-structure in prey population, fear, anti-predator and harvesting are suggested. Lotka-Volterra and Holling type II functional responses have been assumed to describe the feeding processes . The local and global stability of steady points of this model are established. Finally, the global dynamics are studied numerically to investigate the influence of the parameters on the solutions of the system, especially the effect of fear and anti-predation.
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This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics
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The research included five sections containing the first section on the introduction of the research and its importance and was addressed to the importance of the game of gymnastic and skilled parallel effectiveness and the importance of learning, but the problem of research that there is a difference in learning this skill and difficulty in learning may be one of the most important reasons are fear and fear of falling and injury, And a lack of sense of the movement of the movement is one of the obstacles in the completion of the skill and the goal of research to design a device that helps in learning the skill of descending Almtor facing with half a cycle according to the typical locomotor track on the parallel device of the technical men'
... Show MoreThe purpose of this paper is to introduce and study the concepts of fuzzy generalized open sets, fuzzy generalized closed sets, generalized continuous fuzzy proper functions and prove results about these concepts.
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