scholarly journals Application of Interactive Multiple Model Adaptive Five-Degree Cubature Kalman Algorithm Based on Fuzzy Logic in Target Tracking

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 767
Author(s):  
Jian Wan ◽  
Peiwen Ren ◽  
Qiang Guo
Keyword(s):  
Fuzzy Logic ◽  
Simulation Analysis ◽  
Model Simulation ◽  
Multiple Model ◽  
Fuzzy Logic Algorithm ◽  
Error Covariance ◽  
Speed Tracking ◽  
Model Probability ◽  
Interactive Multiple Model ◽  
Tracking Model

Aiming at the shortcomings of low precision, hysteresis, and poor robustness of the general interactive multimodel algorithm in the “snake-like” maneuver tracking of anti-ship missiles, an interactive multimodel adaptive five-degree cubature Kalman algorithm based on fuzzy logic (FLIMM5ACKF) is proposed. The algorithm mainly includes adaptive five-degree cubature Kalman algorithm (A5CKF) and fuzzy logic algorithm (FL). A5CKF uses the Sage–Husa noise estimation principle to propose a state error covariance adaptive five-degree cubature Kalman algorithm to improve the performance of state estimation. Then, the fuzzy logic algorithm (FL) is added to the model probability update module to control the model probability update module. Finally, by setting the same tracking model simulation analysis, the algorithm has better convergence speed, tracking effect and robustness than the interactive multimodel cubature Kalman algorithm (IMMCKF), the interactive multimodel five-degree cubature Kalman algorithm (IMM5CKF) and the interactive multimodel adaptive five-degree cubature Kalman (IMMA5CKF).

scholarly journals TRANSPORT OF RESUSPENDED DREDGED SEDIMENT NEAR CORAL REEFS AT APRA HARBOR, GUAM

2012 ◽  
Vol 1 (33) ◽  
pp. 99
Author(s):  
Tahirih Lackey ◽  
Joseph Gailani ◽  
Sung-Chan Kim ◽  
David King ◽  
Deborah Shafer
Keyword(s):  
Coral Reef ◽  
Coral Reefs ◽  
Model Simulation ◽  
Selection Process ◽  
A Priori ◽  
Sediment Concentration ◽  
Exposure Level ◽  
Multiple Model ◽  
Model Studies ◽  
Tracking Model

Model studies have been conducted to investigate the potential coral reef exposure from proposed dredging associated with development of a new deepwater wharf in outer Apra Harbor, Guam. The Particle Tracking Model (PTM) was applied to quantify the exposure of coral reefs to material suspended by the dredging operations at proposed sites. Key PTM features include the flexible capability of continuous multiple releases of sediment parcels, control of parcel/substrate interaction, and the ability to track vast numbers of parcels efficiently. This flexibility has allowed for model simulation of the combined effects of sediment release from clamshell dredging, of chiseling to fracture limestone blocks, of silt curtains, and of flocculation. Because the rate of material released into the water column by some of the processes is not well understood or a priori known, the modeling protocol was to bracket parameters within reasonable ranges to produce a suite of potential results from multiple model runs. Data analysis results include mapping the time histories and the maximum values of suspended sediment concentration and deposition rate. Following exposure modeling, the next phase of the analysis has been an ecological assessment to translate the PTM exposure level predictions into predicted amounts of coral reef damage. The level of potential coral reef impact will be an important component of the final selection process for the new deepwater berthing site.

scholarly journals Adaptive Tracking Method of Distorted Voltage Using IMM Algorithm under Grid Frequency Fluctuation Conditions

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7944
Author(s):  
Haoyao Nie ◽  
Xiaohua Nie
Keyword(s):  
Tracking Error ◽  
Sine Wave ◽  
Set Covering ◽  
Frequency Fluctuation ◽  
Detection Accuracy ◽  
Multiple Model ◽  
Fixed Frequency ◽  
Frequency Detection ◽  
Interactive Multiple Model ◽  
Tracking Model

This paper newly proposes an interactive multiple model (IMM) algorithm to adaptively track distorted AC voltage with the grid frequency fluctuation. The usual tracking methods are Kalman filter (KF) algorithm with a fixed frequency and KF algorithm with frequency identifier. The KF algorithm with a fixed frequency has a larger covariance parameter to guarantee the tracking robustness. However, it has a large tracking error. The KF algorithm with frequency identifier overly depends on the accuracy and stability of frequency identifier. The advantage of the proposed method is that it is decoupled from frequency detection and does not depend on frequency detection accuracy. First, the orthogonal vector dynamic (OVD) tracking model of the sine wave is established. Then, a model set covering the grid frequency fluctuation range is formed, and a new OVD-IMM tracking algorithm is proposed in combination with IMM algorithm. In the end, the effectiveness and accuracy of the proposed OVD-IMM algorithm are verified through simulations and experiments.

Optimal model-free fuzzy logic control for autonomous unmanned aerial vehicle

2021 ◽  
pp. 095441002110253
Author(s):  
Hossam E Glida ◽  
Latifa Abdou ◽  
Abdelghani Chelihi ◽  
Chouki Sentouh ◽  
Gabriele Perozzi
Keyword(s):  
Fuzzy Logic ◽  
Unmanned Aerial Vehicle ◽  
Fuzzy Logic Control ◽  
Estimation Error ◽  
Design Parameters ◽  
Multiple Model ◽  
Optimal Model ◽  
Model Free ◽  
Logic Control ◽  
Aerial Vehicle

This article deals with the issue of designing a flight tracking controller for an unmanned aerial vehicle type of quadrotor based on an optimal model-free fuzzy logic control approach. The main design objective is to perform an automatic flight trajectory tracking under multiple model uncertainties related to the knowledge of the nonlinear dynamics of the system. The optimal control is also addressed taking into consideration unknown external disturbances. To achieve this goal, we propose a new optimal model-free fuzzy logic–based decentralized control strategy where the influence of the interconnection term between the subsystems is minimized. A model-free controller is firstly designed to achieve the convergence of the tracking error. For this purpose, an adaptive estimator is proposed to ensure the approximation of the nonlinear dynamic functions of the quadrotor. The fuzzy logic compensator is then introduced to deal with the estimation error. Moreover, the optimization problem to select the optimal design parameters of the proposed controller is solved using the bat algorithm. Finally, a numerical validation based on the Parrot drone platform is conducted to demonstrate the effectiveness of the proposed control method with various flying scenarios.

scholarly journals A fuzzy logic algorithm derived mechatronic concept prototype for crop damage avoidance during eco-friendly eradication of intra-row weeds

2020 ◽  
Vol 4 ◽  
pp. 116-126
Author(s):  
Satya Prakash Kumar ◽  
V.K. Tewari ◽  
Abhilash K. Chandel ◽  
C.R. Mehta ◽  
Brajesh Nare ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Crop Damage ◽  
Fuzzy Logic Algorithm ◽  
Damage Avoidance
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