Minimum-time open-loop and closed-loop optimal guidance with GA-PSO and neural fuzzy for Samarai MAV flight

Samani, Mohammad Reza Ghatreh; Tafreshi, Mona; Shafieenejad, Iman; Nikkhah, Amir Ali

doi:10.1109/maes.2015.7119822

Cited by 13 publications

(8 citation statements)

References 18 publications

(20 reference statements)

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“…D is the sub-matrix associated with uncontrollable transitions association matrix [7] .If it is,it does not need to be processed,otherwise, go to step 3.…”

Section: Constraint Conversion Methodsmentioning

confidence: 99%

A Fault Diagnosis Method Based on CFPN Model

Fan¹,

Xu²,

Chai³

2016

Proceedings of the 2016 Joint International Information Technology, Mechanical and Electronic Engineering

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Abstract. In traditional FPN model,the matrix operations are too excessive and it does not meet the requirements of real-time in fault diagnosis system.The paper has improved the FPN model and proposed a CFPN(Controlled Fuzzy Petri Net) modeling method.This method has added controlled place in FPN and improved the design method of control arc of the control place.The method is based on the principle of p-and it enables to simplify the logic of FPN fault diagnosis.That can reduce the matrix computation in FPN fault diagnosis reasoning to improve the efficiency of fault diagnosis.This paper has applied the method in the distillation column fault diagnosis system and verified the applicability and effectiveness of fault diagnosis method based on CFPN model.

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“…D is the sub-matrix associated with uncontrollable transitions association matrix [7] .If it is,it does not need to be processed,otherwise, go to step 3.…”

Section: Constraint Conversion Methodsmentioning

confidence: 99%

A Fault Diagnosis Method Based on CFPN Model

Fan¹,

Xu²,

Chai³

2016

Proceedings of the 2016 Joint International Information Technology, Mechanical and Electronic Engineering

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“…can be obtained by ultrasonic which was integrated in the optical flow sensor. Angular velocity , , and can be obtained by gyroscope; and can be substituted by (2) and (3). Therefore, the translational velocity T c of the MAV under the camera coordinate system can be estimated, and the MAV velocity under geographic coordinate system can be calculated through coordinate transformational matrix C n c .…”

Section: The Model Of Opticalmentioning

confidence: 99%

“…Recently, the autonomous operating unmanned aerial vehicle (MAV) is becoming popular in military and civilian applications [1][2][3], such as aerial surveillance, cargo delivery, search and rescue, and remote sensing and mapping. A reliable navigation system is very important for safely operating the MAV.…”

Section: Introductionmentioning

confidence: 99%

Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment

et al. 2016

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The drift of inertial navigation system (INS) will lead to large navigation error when a low-cost INS is used in microaerial vehicles (MAV). To overcome the above problem, an INS/optical flow/magnetometer integrated navigation scheme is proposed for GPS-denied environment in this paper. The scheme, which is based on extended Kalman filter, combines INS and optical flow information to estimate the velocity and position of MAV. The gyro, accelerator, and magnetometer information are fused together to estimate the MAV attitude when the MAV is at static state or uniformly moving state; and the gyro only is used to estimate the MAV attitude when the MAV is accelerating or decelerating. The MAV flight data is used to verify the proposed integrated navigation scheme, and the verification results show that the proposed scheme can effectively reduce the errors of navigation parameters and improve navigation precision.

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“…The traditional evolutionary algorithm are BP and PSO algorithm,but BP algorithm has complex iterated function and a large error [7] .PSO algorithm need not to take derivative of error cost function,shorten the solution time and avoid the error generated by derivation.But the standard PSO algorithm prone to 'premature' phenomenon.So it is necessary to improve the standard PSO to improve the accuracy and efficiency of the algorithm.…”

Section: Optimization Algorithm Of Error Cost Functionmentioning

confidence: 99%

A FPN Parameter Optimization Method Based on CDEDPSO

Fan¹,

Xu²

2016

Proceedings of the 2016 International Symposium on Advances in Electrical, Electronics and Computer Engineering

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Abstract. For the uncertain change characteristics of transition matrix parameters in complex FPN system,this paper presents a parameters optimization algorithm based on CDEDPSO.This article focuses on the weight, threshold and certainty of FPN optimized model and these parameters are analyzed, improved and simulated simultaneously.This method implements dynamic programming and self-learning of uncertain characterization parameters in FPN.Finally, in this paper, the method is applied to a FPN model and the feasibility and effectiveness of this method has been verified. IntroductionThe transition matrix in FPN model is a collection of trigger condition parameters and the biggest drawback is the poor self-learning ability for the uncertain parameters.The changes feature of uncertain parameters are reflected in these areas:the determination of weight, threshold, certainty and other parameters.Therefore,Consider how to deal with and improve uncertain parameters of FPN to optimize FPN uncertain knowledge representation model,enhance the dynamic programming and self-learning ability of FPN and improve the efficiency and accuracy of FPN model has became an important research topic

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Minimum-time open-loop and closed-loop optimal guidance with GA-PSO and neural fuzzy for Samarai MAV flight

Cited by 13 publications

References 18 publications

A Fault Diagnosis Method Based on CFPN Model

A Fault Diagnosis Method Based on CFPN Model

Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment

A FPN Parameter Optimization Method Based on CDEDPSO

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