Article
Computer Science, Information Systems
Yanxin Nie, Yiding Hua, Minglu Zhang, Xiaojun Zhang
Summary: This paper proposes an autonomous vehicle trajectory tracking system that considers road friction. It improves upon traditional recursive least squares (RLS) method to accurately identify the friction coefficient. The identified results are used in the model predictive controller (MPC) to enhance tire slip angle constraints and achieve excellent tracking performance for the intelligent vehicle.
Article
Engineering, Mechanical
Antai Li, Datong Qin
Summary: This study proposes an adaptive control strategy for shifting in dual clutch transmission (DCT), which estimates the dynamic friction coefficient of a wet clutch and designs optimal shift reference curves. The results show that this control strategy can achieve good shift quality and adapt to changes in the dynamic friction coefficient caused by clutch abrasion and temperature variations.
MECHANISM AND MACHINE THEORY
(2022)
Article
Automation & Control Systems
Jian Pan, Sunde Liu, Jun Shu, Xiangkui Wan
Summary: This paper proposes a hierarchical least squares algorithm for parameter identification problems of a Volterra nonlinear system. By decomposing the Volterra system into three subsystems with a smaller number of parameters and estimating the parameters of each subsystem separately, the proposed algorithm overcomes the excessive calculation amount of the Volterra systems. The calculation analysis shows that the proposed algorithm has lower computational cost compared to the recursive least squares algorithm, and simulation results demonstrate its effectiveness in identifying Volterra systems.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Soumaya Marzougui, Saida Bedoui, Asma Atitallah, Kamel Abderrahim
Summary: This paper proposes a new estimation method for discrete fractional-order Wiener systems, which can simultaneously estimate unknown parameters, unknown fractional orders, and inaccessible states. By minimizing the non-convex and nonlinear criterion, the model parameters are identified using recursive least squares, the fractional orders are determined using the Levenberg-Marquardt algorithm, and the immeasurable states are estimated using the extended Luenberger observer.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Po Li, Ying He, Jingrui Zhang
Summary: This paper presents a real-time detection method for harmonic extraction that is able to handle sudden fluctuations in amplitude, phase, and frequency of the fundamental wave. The method utilizes the Least Squares method with forgetting factor to extract the phase and frequency of the fundamental wave, and then uses this information to design a linear time-varying observer for the extraction of DC bias and harmonics. The proposed method is shown to be robust and accurate in various scenarios such as distorted power grid signals, white noise, inter-harmonics, and high-order harmonics.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Automation & Control Systems
Yelong Yu, Xiaoyan Huang, Zhaokai Li, Min Wu, Tingna Shi, Yanfei Cao, Geng Yang, Feng Niu
Summary: This article introduces a novel online full parameter estimation method for permanent magnet synchronous motors (PMSMs). By utilizing the recursive least squares algorithm in the alpha-beta frame, the proposed method can estimate all motor parameters simultaneously. Simulation and experimental results demonstrate the superiority of the proposed method in terms of convergence rate, computational cost, and accuracy compared to the traditional method in the d-q frame.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Mechanical
Xinghao Du, Jinhao Meng, Kailong Liu, Yingmin Zhang, Shunli Wang, Jichang Peng, Tianqi Liu
Summary: This paper proposes a co-estimation framework utilizing the advantages of both recursive least squares (RLS) and recursive total least squares (RTLS) for a higher parameter identification performance of the battery equivalent circuit model (ECM). RLS quickly converges by updating the parameters along the gradient of the cost function, while RTLS is applied to attenuate the noise effect once the parameters have converged. Both simulation and experimental results show that the proposed method has good accuracy, a fast convergence rate, and robustness against noise corruption.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2023)
Article
Computer Science, Information Systems
Igor Skrjanc
Summary: This paper proposes a new approach for online identification of interval fuzzy models, which evolves model structures, adjusts parameters, and calculates upper and lower bounds simultaneously. The method shows great potential in applications such as online monitoring, fault detection, and control of dynamic systems. It is characterized by the integration of structural and parametric uncertainties into the fuzzy interval models.
INFORMATION SCIENCES
(2021)
Article
Thermodynamics
Muyao Wu, Li Wang, Ji Wu
Summary: This paper proposes a SOH estimation method for lithium-ion power batteries, which utilizes the FFRTLS and temperature correction. The method effectively addresses SOC estimation errors and terminal current measurement noise, while also correcting the influence of ambient temperature. Experimental results demonstrate the effectiveness of the proposed method, with evaluation indexes showing high accuracy of the SOH estimation results.
Letter
Engineering, Aerospace
Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Wael M. Bazzi, Saeid Sanei
Summary: An adaptive estimation method for optimal combination weights in partial-diffusion Kalman filtering is proposed, along with mean convergence and stability analysis. Simulation results confirm superior performance compared to existing combiners, particularly benefiting sensor networks with limited accessible power.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Optics
Yong -Mei Li, Hai -Ling Liu, Shi-Jie Pan, Su-Juan Qin, Fei Gao, Dong-Xu Sun, Qiao-Yan Wen
Summary: This paper proposes a complete quantum algorithm for the k-medoids algorithm, which utilizes quantum subroutines to improve the speed of cluster assignment and center update. Compared to existing algorithms, our quantum k-medoids algorithm achieves a polynomial speedup in large data sets.
Article
Engineering, Mechanical
Ning Xu, Feng Ding
Summary: This paper proposes an identification method for time-varying systems by modeling the time-varying parameter as an autoregressive process and estimating the autoregressive coefficients using a recursive identification method. A parameter separation scheme is designed to enhance computational efficiency. The convergence property and upper bound of the parameter estimation error are analyzed, and simulation results demonstrate the effectiveness of the proposed method.
NONLINEAR DYNAMICS
(2023)
Review
Engineering, Mechanical
Randall J. Allemang, Rohit S. Patwardhan, Murali M. Kolluri, Allyn W. Phillips
Summary: This paper outlines various FRF estimation techniques and compares algorithms that compute FRF using different methods. It also discusses inconsistencies in some conditioned coherence metrics and provides corrected interpretations.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Mathematics, Applied
Baolei Wei, Naiming Xie
Summary: This study investigates the parameter estimation of grey system models from noisy observations, and finds that nonlinear least squares has multiple advantages over the conventional integral matching method in terms of accuracy and robustness.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Computer Science, Information Systems
Goran Andonovski, Edwin Lughofer, Igor Skrjanc
Summary: This paper introduces a new approach to neuro-fuzzy model identification using a filtered recursive least squares method and an incrementally evolving Gaussian clustering method. The method shows potential in identifying nonlinear dynamic models and has been tested on a real heat exchanger plant. The results of the experiments demonstrate that the proposed method is easy to implement, can perform necessary calculations online, and generates meaningful models.
