Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models

Jonker, Jonathan; Zheng, Peng; Aravkin, Aleksandr Y.

doi:10.1109/tac.2020.3042438

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…The design of the identification algorithm is the most critical. There are many mature research identification algorithms, such as genetic algorithm identification [8], maximum likelihood estimation identification [9], least square method identification [10,11]. Due to the dynamic coupling of different joints, the identification parameters are not independent.…”

Section: Introductionmentioning

confidence: 99%

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Zhang

2022

Robotica

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Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual’s judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control.

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Section: Introductionmentioning

confidence: 99%

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Zhang

2022

Robotica

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Identification of Pulse Discharge Parameters in Water for Reservoir Resonance Transform Device

Kang

Shao

Gao

2022

J. Phys.: Conf. Ser.

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The reservoir resonance transform device is applied to unconventional shale gas stimulation. To achieve the purpose of resonance stimulation, the discharge frequency is dynamically corresponding to the natural frequency of the reservoir. However, the discharge parameters under the same conditions differ in the resonance process. It is hard to analyze the real-time change of reservoir frequency precisely. Therefore, the identification of pulse discharge parameters in water is extremely important. In this paper, an equivalent circuit model of pulse discharge in water is established to analyze the time-varying resistance. The Kalman filter makes the discrete resistance data continuous and reduces the interference caused by the random discharge. Meanwhile, the data error analysis is carried out. The results show that the variance of pulse discharge resistance in water based on the Kalman filter is less than 0.528 compared with the experiment value, so the identified resistance obtained by this method can be used in the study of resonant discharge in the same frequency.

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Learning Nonlinear Dynamics Using Kalman Smoothing

Stevens-Haas,

Bhangale,

Nathan Kutz

et al. 2024

IEEE Access

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Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models

Cited by 3 publications

References 14 publications

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Identification of Pulse Discharge Parameters in Water for Reservoir Resonance Transform Device

Learning Nonlinear Dynamics Using Kalman Smoothing

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