scholarly journals Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

2021 ◽  
Author(s):  
Mustefa Jibril
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Vertical Plane ◽  
Integrated Design ◽  
Adaptive Fuzzy ◽  
Quadrotor Uav

Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.

scholarly journals Fuzzy swarm trajectory tracking control of unmanned aerial vehicle

2020 ◽  
Vol 7 (4) ◽  
pp. 435-447 ◽  
Author(s):  
Boumediene Selma ◽  
Samira Chouraqui ◽  
Hassane Abouaïssa
Keyword(s):  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Fuzzy Inference ◽  
Control Method ◽  
Tracking Error ◽  
Vertical Plane ◽  
Pso Algorithm ◽  
Trajectory Tracking Control ◽  
Inference System ◽  
Quadrotor Uav

Abstract Accurate and precise trajectory tracking is crucial for unmanned aerial vehicles (UAVs) to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the robust adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) algorithm. The ANFIS-PSO controller is implemented to govern the behavior of three degrees of freedom quadrotor UAV. The ANFIS controller allows controlling the movement of UAV to track a given trajectory in a 2D vertical plane. The PSO algorithm provides an automatic adjustment of the ANFIS parameters to reduce tracking error and improve the quality of the controller. The results showed perfect behavior for the control law to control a UAV trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with ANFIS and PID control methods.

Self Tuning Based Adaptive Fuzzy Logic Controller in Lab view for Sterilizing Equipments

2014 ◽  
Vol 3 (2) ◽  
pp. 84
Author(s):  
P. J. Ragu
Keyword(s):  
Fuzzy Logic ◽  
Temperature Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Lab View ◽  
Adaptive Fuzzy Logic ◽  
Self Tuning ◽  
Input Variables ◽  
Temperature Errors

In this paper, temperature monitoring of sterilizing equipment system was established with the help of fuzzy and self tuning Adaptive fuzzy logic controller designed in Lab VIEW software. It combines the advantages of both fuzzy logic and self tuning Adaptive fuzzy logic controller. The implementation attempts to rectify the errors between the measured value and the set point which helps to achieve efficient temperature control. The Adaptive fuzzy controller uses defined rules to control the system based on the current values of input variables and temperature errors. The simulation results presented in order to evaluate the proposed method. The result shows that self tuning  Adaptive fuzzy logic controller was tolerant to disturbance and the temperature control is most accurate.

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

2014 ◽  
Vol 573 ◽  
pp. 155-160
Author(s):  
A. Pandian ◽  
R. Dhanasekaran
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Constant Speed ◽  
Three Phase

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

Intelligent Control System Design for a Teleoperated Endoscopic Surgical Robot

2015 ◽  
Vol 789-790 ◽  
pp. 693-699
Author(s):  
Alaa Khalifa ◽  
Ahmed Ramadan
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
System Design ◽  
Trajectory Tracking ◽  
Parallel Manipulator ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control System Design ◽  
Matlab Simulink

This paper concerns with the control system design for a teleoperated endoscopic surgical manipulator system that uses PHANTOM Omni haptic device as the master and a 4-DOF parallel manipulator (2-PUU_2-PUS) as the slave. PID control algorithm was used to achieve the trajectory tracking, but the error in each actuated joint reached 0.6 mm which is not satisfactory in surgical application. The design of a control algorithm for achieving high trajectory tracking is needed. Simulation on the virtual prototype of the 4-DOF parallel manipulator has been achieved by combining MATLAB/Simulink with ADAMS. Fuzzy logic controller is designed and tested using the interface between ADAMS and MATLAB/Simulink. Signal constraint block adjusted the controller parameters for each actuated prismatic joint to eliminate the overshoot in most of position responses. The simulation results illustrate that the fuzzy logic control algorithm can achieve high trajectory tracking. Also, they show that the fuzzy controller has reduced the error by approximately 50 percent.

scholarly journals Adaptive Fuzzy Controller Design for Solar And Wind Based Hybrid System

2018 ◽  
Vol 7 (2.24) ◽  
pp. 283 ◽  
Author(s):  
M Rathaiah ◽  
P Ram Kishore Kumar Reddy ◽  
P Sujatha
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Hybrid System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic

Renewable Energy Resources plays an active role in standing against   global warming and reduce the use of conventional energy sources. Hybrid systems formed by combining the renewable energy sources are efficient relatively. The intent of this paper is to furnish endurable power for frontier and far-off places with hybrid-system of architecture. The intended system embodying DFIG and solar PV based wind turbine. In solar systems, control mechanism is essential for improving the performance. This paper proposes a method of incremental conductance approach based MPPT Adaptive Fuzzy Logic Controller for grid connected PV system which is composed of a boost converter and a three phase inverter. Adaptive Fuzzy Logic Controller provides fast response and better %THD compared to Fuzzy and PI controllers. In solar system, MPPT will magnify solar output power value. The DFIG has two controllers Grid-Side Control (GSC) and Rotor-Side Control (RSC). The rated rotor speed and DC-link voltage are regulated by RSC and GSC through PI, Fuzzy Logic Controller and AFLC strategies. By using simulation studies performed by three control strategies, %THD analysis is carried out.  

scholarly journals ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Manuel Braz César ◽  
Rui Carneiro Barros
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Magnetorheological Dampers ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Degrees Of Freedom

Abstract In this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS. Fuzzy logic based controllers are capable to deal with non-linear or uncertain systems, which make them particularly well suited for civil engineering applications. The main objective is to develop a semi-active control system with a MR damper to reduce the response of a three degrees-of-freedom (DOFs) building structure. The control system is designed using ANFIS to optimize the fuzzy inference rule of a simple fuzzy logic controller. The results show that the proposed semi-active neuro-fuzzy based controller is effective in reducing the response of structural system.

scholarly journals Social spider optimization algorithm for tuning parameters in PD-like Interval Type-2 Fuzzy Logic Controller applied to a parallel robot

2021 ◽  
Vol 54 (3-4) ◽  
pp. 303-323
Author(s):  
Amjad J Humaidi ◽  
Huda T Najem ◽  
Ayad Q Al-Dujaili ◽  
Daniel A Pereira ◽  
Ibraheem Kasim Ibraheem ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Fuzzy Logic Controller ◽  
Optimization Technique ◽  
Parallel Robot ◽  
Design Parameters ◽  
Social Spider ◽  
Social Spider Optimization ◽  
Interval Type

This paper presents control design based on an Interval Type-2 Fuzzy Logic (IT2FL) for the trajectory tracking of 3-RRR (3-Revolute-Revolute-Revolute) planar parallel robot. The design of Type-1 Fuzzy Logic Controller (T1FLC) is also considered for the purpose of comparison with the IT2FLC in terms of robustness and trajectory tracking characteristics. The scaling factors in the output and input of T1FL and IT2FL controllers play a vital role in improving the performance of the closed-loop system. However, using trial-and-error procedure for tuning these design parameters is exhaustive and hence an optimization technique is applied to achieve their optimal values and to reach an improved performance. In this study, Social Spider Optimization (SSO) algorithm is proposed as a useful tool to tune the parameters of proportional-derivative (PD) versions of both IT2FLC and T1FLC. Two scenarios, based on two square desired trajectories (with and without disturbance), have been tested to evaluate the tracking performance and robustness characteristics of proposed controllers. The effectiveness of controllers have been verified via numerical simulations based on MATLAB/SIMULINK programming software, which showed the superior of IT2FLC in terms of robustness and tracking errors.

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