Parameter optimization of moving horizon estimation based on hybrid intelligent algorithm

Zhang, Bo; Jiang, Aipeng; Qi, Yanying; Jiang, Jiaji; Wang, Haokun; Kong, Jundong

doi:10.1002/asjc.2949

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…With the development of industry and the increased level of automation, automated guided vehicles (AGVs), as core components of advanced logistics systems, have become popular in modern industrial logistics systems [1], due to their ability to reduce logistics transportation time, shorten the production cycle, and improve overall efficiency for the production line [2]. Recent studies reveal that an effective coordination policy, which considers objectives including efficient utilization of all AGV subsystems, respecting temporal and spatial constraints, and avoiding collisions, subject to sensing and communication limits, and changing environments, is essential in achieving the maximum transportation efficiency of the entire logistic warehousing system [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal coordination in logistics warehousing with sensing and communication limits: A distributed differential game approach

Xue,

Zhan,

Chen

et al. 2023

Asian Journal of Control

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Optimal coordination is essential for multi‐automated guided vehicle (AGV) systems, particularly in logistic transportation cases, where the system task completion time needs to be minimized, with the guarantee of safe operation. This is because an optimal coordination strategy (OCS), if achieved, can significantly improve the transportation system's efficiency. In this paper, to deal with the dynamic interaction process among AGVs, and sensing and communication range limits, we formulate the optimal coordination problem into a distributed differential game (DDG) framework, where individual AGVs only use information communicated from nearby AGVs to design their optimal operation trajectories. This helps to significantly reduce the computational and communication requirements for the multi‐AGV logistic transportation systems. Targeting operation safety and working efficiency requirements, we incorporate collision avoidance and trajectory optimization objectives into the proposed framework. It is shown that local OCS, obtained by solving the DDG problem for each AGV, will converge to the global Nash equilibrium, which represents the most efficient operating condition for the entire logistic transportation system. Finally, the efficacy of the proposed method is demonstrated, based on simulations and experiments, benchmarked with existing logistic warehousing planning and differential game methods. Compared with conventional methods, the proposed framework successfully helps reduce the task completion time by up to 16%.

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Section: Introductionmentioning

confidence: 99%

Optimal coordination in logistics warehousing with sensing and communication limits: A distributed differential game approach

Xue,

Zhan,

Chen

et al. 2023

Asian Journal of Control

View full text Add to dashboard Cite

show abstract

Simultaneous robust model predictive control and state estimation for nonlinear systems with state‐ and input‐dependent uncertainties

Badfar,

Safavi

2024

Asian Journal of Control

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The convergence and stability of uncertain nonlinear systems is a challenging problem in the nonlinear control area. Besides, in many practical cases, all states are not measurable and are affected by measurement noise. Based on this motivation, the first objective of this paper is to design a novel output feedback robust model predictive control approach for nonlinear systems with state‐ and input‐dependent uncertainties and measurement noise. This approach combines state estimation and robust model predictive control (MPC) into one min–max optimization and by solving the optimization, these two tasks are performed simultaneously. The studied nonlinear system comprises a linear part, a nonlinear part, and a function that denotes the state‐ and input‐dependent uncertainties. Therefore, the other objective is to reduce the computational complexity; thus, the system's nonlinear term and the aforementioned uncertainties are converted into additional disturbances. Subsequently, the optimization problem becomes a quadratic form, which leads to global convergence with the appropriate selection of objective function weights. Besides, this paper explores the convergence of the closed‐loop system states and the sufficient synthesis conditions to guarantee input‐to‐state stability. The implementation on a numerical example and a CSTR process demonstrate the applicability and reliability of the proposed approach.

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Parameter optimization of moving horizon estimation based on hybrid intelligent algorithm

Cited by 2 publications

References 32 publications

Optimal coordination in logistics warehousing with sensing and communication limits: A distributed differential game approach

Optimal coordination in logistics warehousing with sensing and communication limits: A distributed differential game approach

Simultaneous robust model predictive control and state estimation for nonlinear systems with state‐ and input‐dependent uncertainties

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