Abstract
The theory of algorithm for improving bacterial feed is considered one of the important theories in advanced research and has been widely accepted for a global improvement algorithm to solve problems of control in improvement research in non-linear systems, which have become among the interests of researchers in this field .In our work, a new method for design of a bacteria foraging algorithm principle based on Proportional-integral-derivative controller (PID) for three degree of freedom (3DoF) helicopter system. This paper presents a method to stabilize pitch, roll and travel angle of the helicopter system using optimization technique based on bacterial foraging (BF) algorithm is used to tune the fractional order PID controller parameters by reducing the objective performance parameters. Transient and constant case responses are found to be appropriate. The result reveals that BF provides a good synthesis algorithm. In addition, BF-FOPID works better than BF-PID controller for the 3DoF helicopter model.
Highlights
INTRODUCTIONThe goal is to force an electric vehicles (EVs)'s tuning of the noninteger fuzzy Proportional-integral-derivative controller (PID) controller coefficient is speed to follow a desirable reference for both (structured and accomplished through a modified black hole optimization unstructured) uncertainties.The second order EV simulation algorithm
The Takagi - Sugeno (T-S) fuzzy system was linear dynamics and unstable open rings and high proposed by [8] to find the contribution factor of variable coupling between the control channels
A new multiproposed system, the optimum values of the wind turbine objective stochastic optimisation is used for the online contribution factor proportional to the load are obtained based adjustment of the parameters of MOFFOPID controller to on the particle Swarm Optimization (PSO) algorithm without assess its efficiency
Summary
The goal is to force an EV's tuning of the noninteger fuzzy PID controller coefficient is speed to follow a desirable reference for both (structured and accomplished through a modified black hole optimization unstructured) uncertainties.The second order EV simulation algorithm. The helicopter has a special design and because of this design possesses a complex flight attribute and the dynamic characteristic which somewhat difficult to explain [1] These characteristics differ among the aircraft due to a difference in the flight condition like the angles of attack, inclination, climbing, as well as the height of the plane .etc. When a small number of her participants involved in the appropriate space These rare qualities make the (BFOA) high level of the rest of the systems in terms of efficiency and more than this is a suitable tool as a system to improve control systems [19, 20]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
