FPGA based angular stabilization of a quadcopter

MACRo 2015 ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 79-86 ◽  
Author(s):  
Szabolcs Hajdu ◽  
Sándor Tihamér Brassai ◽  
Iuliu Szekely
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Fast Method ◽  
Pid Algorithm ◽  
Principal Axes ◽  
Sensor Configuration ◽  
Path Calculation

AbstractThis paper presents an FPGA based method for stabilization of a quadcopter around the principal axes pitch, roll, and yaw using IMU sensors for angular estimation and the PID algorithm for control. The goal was to solve the problem in hardware level providing a fast method for stabilization. Using an FPGA circuit parallel with a microprocessor the control of the quadcopter becomes simpler the microprocessor can handle other tasks like area mapping or path calculation parallel with the stabilization hardware implemented on the FPGA. Sensor configuration and calibration was implemented on the FPGA along with the PID controller. The implemented circuit was tested in real time on the quadcopter.

scholarly journals Magnetorheological Elastomer Precision Platform Control Using OFFO-PID Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ying-Qing Guo ◽  
Jie Zhang ◽  
Dong-Qing He ◽  
Jin-Bao Li
Keyword(s):  
Real Time ◽  
Fractional Order ◽  
Pid Controller ◽  
Vibration Isolation ◽  
Dynamic Responses ◽  
Magnetorheological Elastomer ◽  
Controlled System ◽  
Pid Algorithm ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

The magnetorheological elastomer (MRE) is a kind of smart material, which is often processed as vibration isolation and mitigation devices to realize the vibration control of the controlled system. The key to the effective isolation of vibration and shock absorption is how to accurately and in real time determine the magnitude of the applied magnetic field according to the motion state of the controlled system. In this paper, an optimal fuzzy fractional-order PID (OFFO-PID) algorithm is proposed to realize the vibration isolation and mitigation control of the precision platform with MRE devices. In the algorithm, the particle swarm optimization algorithm is used to optimize initial values of the fractional-order PID controller, and the fuzzy algorithm is used to update parameters of the fractional-order PID controller in real time, and the fractional-order PID controller is used to produce the control currents of the MRE devices. Numerical analysis for a platform with the MRE device is carried out to validate the effectiveness of the algorithm. Results show that the OFFO-PID algorithm can effectively reduce the dynamic responses of the precision platform system. Also, compared with the fuzzy fractional-order PID algorithm and the traditional PID algorithm, the OFFO-PID algorithm is better.

Experiments of iterative learning control system using particle swarm optimization by new bounded constraints on velocity and positioning

2014 ◽  
Vol 31 (2) ◽  
pp. 250-266 ◽  
Author(s):  
Yi-Cheng Huang ◽  
Ying-Hao Li
Keyword(s):  
Particle Swarm Optimization ◽  
Real Time ◽  
Iterative Learning Control ◽  
Pid Controller ◽  
Learning Control ◽  
Iterative Learning ◽  
Experimental Results ◽  
Swarm Optimization ◽  
Content Type ◽  
Pid Algorithm

Purpose – This paper utilizes the improved particle swarm optimization (IPSO) with bounded constraints technique on velocity and positioning for adjusting the gains of a proportional-integral-derivative (PID) and iterative learning control (ILC) controllers. The purpose of this paper is to achieve precision motion through bettering control by this technique. Design/methodology/approach – Actual platform positioning must avoid the occurrence of a large control action signal, undesirable overshooting, and preventing out of the maximum position limit. Several in-house experiments observation, the PSO mechanism is sometimes out of the optimal solution in updating velocity and updating position of particles, the system may become unstable in real-time applications. The proposed IPSO with new bounded constraints technique shows a great ability to stabilize nonminimum phase and heavily oscillatory systems based on new bounded constraints on velocity and positioning in PSO algorithm is evaluated on one axis of linear synchronous motor with a PC-based real-time ILC. Findings – Simulations and experiment results show that the proposed controller can reduce the error significantly after two learning iterations. The developed method using bounded constraints technique provides valuable programming tools to practicing engineers. Originality/value – The proposed IPSO-ILC-PID controller overcomes the shortcomings of conventional ILC-PID controller with fixed gains. Simulation and experimental results show that the proposed IPSO-ILC-PID algorithm exhibits great speed convergence and robustness. Experimental results confirm that the proposed IPSO-ILC-PID algorithm is effective and achieves better control in real-time precision positioning.

Real time position control of electrohydraulic system using PID controller

2021 ◽  
Author(s):  
Ashok Kumar Kumawat ◽  
Renu Kumawat ◽  
Manish Rawat ◽  
Raja Rout
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Position Control ◽  
Electrohydraulic System ◽  
Time Position

scholarly journals A Fast Method for Real-Time Chance-Constrained Decision With Application to Power Systems

2017 ◽  
Vol 1 (1) ◽  
pp. 152-157 ◽  
Author(s):  
Saverio Bolognani ◽  
Elena Arcari ◽  
Florian Dorfler
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Fast Method

scholarly journals Real Time Level Control of Conical Tank and Comparison of Fuzzy and Classical Pid Controller

2015 ◽  
Vol 8 (S2) ◽  
pp. 40 ◽  
Author(s):  
C. Dinesh ◽  
V. V. Manikanta ◽  
H. S. Rohini ◽  
K. R. Prabhu
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Level Control ◽  
Time Level
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