Stochastic model predictive control using Laguerre function with minimum variance Kalman filter estimation

Pinheiro, Tarcisio Carlos F.; Silveira, Antonio S.

doi:10.1007/s40435-022-01029-w

“…Trajectory prediction research in China started earlier, and the traditional methods mainly focus on the trajectory prediction methods based on techniques such as rules, statistics and machine learning. For example, trajectory prediction methods based on mathematical models such as Kalman filter and particle filter are widely used in the fields of target tracking and traffic management [13][14][15][16][17] . In recent years, domestic scholars began to adopt deep learning methods for trajectory prediction research.…”

Section: Introductionmentioning

confidence: 99%

Application of Optimized Kalman Filtering in Target Tracking Based on Improved Gray Wolf Algorithm

Pang,

Wang,

Yang

2023

Preprint

1

0

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High precision is a very important index in target tracking. In order to improve the prediction accuracy of target tracking, an optimized Kalman filter approach based on improved Gray Wolf algorithm (IGWO-OKF) is proposed in this paper. Since the convergence speed of traditional Gray Wolf algorithm is slow, meanwhile, the number of gray wolves and the choice of the maximum number of iterations has a great influence on the algorithm, a nonlinear control parameter combination adjustment strategy is proposed. An improved Grey Wolf Optimization algorithm (IGWO) is formed by determining the best combination of adjustment parameters through the fastest iteration speed of the algorithm. The improved Grey Wolf Optimization algorithm (IGWO) is formed, and the process noise covariance matrix and observation noise covariance matrix in Kalman filter are optimized by IGWO. The proposed approach is applied into. The experiment results show that the proposed IGWO-OKF approach has low error, high accuracy and good prediction effect.

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“…Although some results have been achieved, they still face challenges such as complex scenarios, multi-target interactions, and uncertainty, which require further research and improvement.Trajectory prediction research in China started earlier, and the traditional methods mainly focus on the trajectory prediction methods based on techniques such as rules, statistics and machine learning. For example, trajectory prediction methods based on mathematical models such as Kalman filter and particle filter are widely used in the fields of target tracking and traffic management [13][14][15] . In recent years, domestic scholars began to adopt deep learning methods for trajectory prediction research.…”

mentioning

confidence: 99%

Application of optimized Kalman filtering in target tracking based on improved Gray Wolf algorithm

Pang,

Wang,

Yang

2024

Sci Rep

0

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High precision is a very important index in target tracking. In order to improve the prediction accuracy of target tracking, an optimized Kalman filter approach based on improved Gray Wolf algorithm (IGWO-OKF) is proposed in this paper. Since the convergence speed of traditional Gray Wolf algorithm is slow, meanwhile, the number of gray wolves and the choice of the maximum number of iterations has a great influence on the algorithm, a nonlinear control parameter combination adjustment strategy is proposed. An improved Grey Wolf Optimization algorithm (IGWO) is formed by determining the best combination of adjustment parameters through the fastest iteration speed of the algorithm. The improved Grey Wolf Optimization algorithm (IGWO) is formed, and the process noise covariance matrix and observation noise covariance matrix in Kalman filter are optimized by IGWO. The proposed approach is applied into. The experiment results show that the proposed IGWO-OKF approach has low error, high accuracy and good prediction effect.

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Deterministic equivalent of Stochastic MPC for voltage regulation of Cuk converter using Kalman filter

Shah

¹

,

Neeli

²

2023

Int. J. Dynam. Control

0

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Stochastic model predictive control using Laguerre function with minimum variance Kalman filter estimation

Cited by 3 publications

References 33 publications

Application of Optimized Kalman Filtering in Target Tracking Based on Improved Gray Wolf Algorithm

Application of Optimized Kalman Filtering in Target Tracking Based on Improved Gray Wolf Algorithm

Application of optimized Kalman filtering in target tracking based on improved Gray Wolf algorithm

Deterministic equivalent of Stochastic MPC for voltage regulation of Cuk converter using Kalman filter

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