SYSTEM DESIGNING FOR A SMALL-SCALE AUTONOMOUS HELICOPTER

2006 ◽  
Vol 03 (04) ◽  
pp. 359-367 ◽  
Author(s):  
WENBING CHEN ◽  
MING LIU ◽  
YUNJIAN GE
Keyword(s):  
Pid Controller ◽  
Low Cost ◽  
Model Identification ◽  
Small Scale ◽  
Fuzzy Pid ◽  
Camera System ◽  
Fuzzy Pid Controller ◽  
Binocular Stereo ◽  
Model Helicopter ◽  
Autonomous Helicopter

This paper presents the design of a relative low-cost and more compatible autonomous helicopter system using HIROBO 50 scale as an experimental platform. Because of the limit of helicopter payload, we choose the MP2128 Autopilot and a number of sensors to build the system and the weight of instrumentation is about 500 g, much less than the payload capability of model helicopter. Thus it is feasible to design the binocular stereo-camera system to achieve full autonomous flight and the whole weight (include power) of instrumentation is about 1500 g. After getting the model of the helicopter using the subspace model identification (SMI) algorithms, we present the structure of fuzzy PID controller.

Positioning Control of Ball Screw System Driven by DC Motor

2015 ◽  
Vol 761 ◽  
pp. 142-147
Author(s):  
Shin Horng Chong ◽  
Ting Tze Ter ◽  
Vasanthan Sakthivelu
Keyword(s):  
Pid Controller ◽  
Low Cost ◽  
Mechanical Efficiency ◽  
Dc Motor ◽  
Ball Screw ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Positioning Control ◽  
Fuzzy Pid Controller ◽  
Point To Point

This paper presents the comparison of positioning control between conventional PID controller and fuzzy PID controller. The controllers are applying into the ball screw system driven by DC motor to observe and analyze the change of the positioning output responses. The DC motor is used because it is easy to setup and control, has precise rotation and most importantly is low cost. As for ball screw mechanism itself, has smooth motion, not easy to wear out and high mechanical efficiency. The problem is arise when the used of conventional PID controller in the ball screw system driven by DC motor shows less adaptability to the changes of system parameter. Therefore, the objective of this project is to design an adaptive fuzzy PID controller to overcome the limitation of conventional PID controller. The performances between the conventional PID controller and fuzzy PID controller will be compared in order to validate the robustness of the fuzzy PID controller. So this project is to compare the robustness of two proposed controllers by comparing the results of ball screw table position when the parameter mass of load is set to vary. The experiment is started with designing the algorithms of fuzzy PID control and conventional PID controller, then the designed algorithm is applied onto the experimental that has been setup. The performances especially the transient response and steady state error between the controllers will be collected and compared by conducting the point to point positioning, tracking and variation of load weight experiments.

scholarly journals The fuzzy-PID based-pitch angle controller for small-scale wind turbine

2020 ◽  
Vol 11 (1) ◽  
pp. 135
Author(s):  
Quang-Vi Ngo ◽  
Chai Yi ◽  
Trong-Thang Nguyen
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Small Scale ◽  
Fuzzy Pid ◽  
Proportional Integral Derivative ◽  
Fuzzy Pid Controller

<p>This paper aims to design the pitch angle control based on proportional–integral–derivative (PID) controller combined with fuzzy logic for small-scale wind turbine systems. In this control system, the pitch angle is controlled by the PID controller with their parameter is tuned by the fuzzy logic controller. This control system can compensate for the nonlinear characteristic of the pitch angle and wind speed. A comparison between the fuzzy-PID-controller with the conventional PID controller is carried out. The effectiveness of the method is determined by the simulation results of a small wind turbine using a permanent magnet generator (PMSG).</p>

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

Core power control of a space nuclear reactor based on a nonlinear model and fuzzy-PID controller

2021 ◽  
pp. 103564
Author(s):  
Wenjie Zeng ◽  
Qingfeng Jiang ◽  
Yinuo Liu ◽  
Shoujun Yan ◽  
Guangchun Zhang ◽  
...  
Keyword(s):  
Power Control ◽  
Nonlinear Model ◽  
Pid Controller ◽  
Nuclear Reactor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

Simulation Analysis of Electro-Pneumatic Proportional Fuzzy-PID Control System Based on AMESim/Simulink

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Simulation Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Proportional Control ◽  
Fuzzy Pid Controller ◽  
Design Requirements ◽  
Set Up

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.

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