Robust Time-Varying Kalman State Estimators with Uncertain Noise Variances
Wenjuan Qi,
Zunbing Sheng
Issue:
Volume 3, Issue 6, November 2018
Pages:
113-128
Received:
7 September 2018
Accepted:
19 September 2018
Published:
4 January 2019
DOI:
10.11648/j.mcs.20180306.11
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Views:
Abstract: This paper addresses the design of robust Kalman estimators (filter, predictor and smoother) for the time-varying system with uncertain noise variances. According to the unbiased linear minimum variance (ULMV) optimal estimation rule, the robust time-varying Kalman estimators are presented. Specially, two robust Kalman smoothing algorithms are presented by the augmented and non-augmented state approaches, respectively. They have the robustness in the sense that their actual estimation error variances are guaranteed to have a minimal upper bound for all admissible uncertainties of noise variances. Their robustness is proved by the Lyapunov equation approach, and their robust accuracy relations are proved. The corresponding steady-state robust Kalman estimators are also presented for the time-invariant system, and the convergence in a realization between the time-varying and steady-state robust Kalman estimators is proved by the dynamic error system analysis (DESA) method and the dynamic variance error system analysis (DVESA) method. A simulation example is given to verify the robustness and robust accuracy relations.
Abstract: This paper addresses the design of robust Kalman estimators (filter, predictor and smoother) for the time-varying system with uncertain noise variances. According to the unbiased linear minimum variance (ULMV) optimal estimation rule, the robust time-varying Kalman estimators are presented. Specially, two robust Kalman smoothing algorithms are pres...
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The Relationship of Delivery Frequency with the Cost and Resource Operational Efficiency: A Case Study of Jingdong Logistics
Jianbang Du,
Yeliang Sun,
Huanyu Ren
Issue:
Volume 3, Issue 6, November 2018
Pages:
129-140
Received:
24 October 2018
Accepted:
13 November 2018
Published:
4 January 2019
DOI:
10.11648/j.mcs.20180306.12
Downloads:
Views:
Abstract: Under drastic competition, major express companies have increased their daily delivery frequency to improve customer satisfaction and market share. The inverse relationship of frequency with cost and operational efficiency becomes the key to the decision of delivery frequency. This paper uses JD Logistics as an example to quantitatively analyze the relationship mentioned above. The results show that: (1) The cost and resources operational efficiency are closely related to the order splitting ratio under the same delivery frequency; (2) The delivery frequency has different effects on the operational efficiency of the resources in different links. (3) Through the proper splitting and loading of orders, staff scheduling, and area adjustment of delivery station, the optimal delivery frequency can be achieved under the balance of cost and resource operational efficiency. In order to reduce the operating costs of logistics enterprises on the basis of ensuring service levels, one should first properly allocate the amount of orders and splitting ratios to achieve an economic increase in the delivery frequency. In addition, it is important for the logistics enterprises to consider the constraints such as delivery resources and consumer satisfaction to achieve the appropriate decision of delivery frequency. What’s more, it is also crucial to reasonably arrange vehicle loading, staff scheduling and distribution station leasing for the logistics enterprises.
Abstract: Under drastic competition, major express companies have increased their daily delivery frequency to improve customer satisfaction and market share. The inverse relationship of frequency with cost and operational efficiency becomes the key to the decision of delivery frequency. This paper uses JD Logistics as an example to quantitatively analyze the...
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