Research on Obstacle Avoidance Control Method of Multi-UAV Based on Model Predictive Control

AbstractThis paper reviews model predictive control (MPC) and its wide applications to both single and multiple autonomous ground vehicles (AGVs). On one hand, MPC is a well-established optimal control method, which uses the predicted future information to optimize the control actions while explicitly considering constraints. On the other hand, AGVs are able to make forecasts and adapt their decisions in uncertain environments. Therefore, because of the nature of MPC and the requirements of AGVs, it is intuitive to apply MPC algorithms to AGVs. AGVs are interesting not only for considering them alone, which requires centralized control approaches, but also as groups of AGVs that interact and communicate with each other and have their own controller onboard. This calls for distributed control solutions. First, a short introduction into the basic theoretical background of centralized and distributed MPC is given. Then, it comprehensively reviews MPC applications for both single and multiple AGVs. Finally, the paper highlights existing issues and future research directions, which will promote the development of MPC schemes with high performance in AGVs.

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A New Model Predictive Control Method for Eliminating Hydraulic Oscillation and Dynamic Hydraulic Imbalance in a Complex Chilled Water System

Energies ◽

10.3390/en14123608 ◽

2021 ◽

Vol 14 (12) ◽

pp. 3608

Author(s):

Yang Yuan ◽

Neng Zhu ◽

Haizhu Zhou ◽

Hai Wang

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Control Method ◽

Water System ◽

Energy Performance ◽

Effective Control ◽

New Model ◽

Chilled Water ◽

Chilled Water System ◽

Hydraulic Oscillation

To enhance the energy performance of a central air-conditioning system, an effective control method for the chilled water system is always essential. However, it is a real challenge to distribute exact cooling energy to multiple terminal units in different floors via a complex chilled water network. To mitigate hydraulic imbalance in a complex chilled water system, many throttle valves and variable-speed pumps are installed, which are usually regulated by PID-based controllers. Due to the severe hydraulic coupling among the valves and pumps, the hydraulic oscillation phenomena often occur while using those feedback-based controllers. Based on a data-calibrated water distribution model which can accurately predict the hydraulic behaviors of a chilled water system, a new Model Predictive Control (MPC) method is proposed in this study. The proposed method is validated by a real-life chilled water system in a 22-floor hotel. By the proposed method, the valves and pumps can be regulated safely without any hydraulic oscillations. Simultaneously, the hydraulic imbalance among different floors is also eliminated, which can save 23.3% electricity consumption of the pumps.

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Emergency obstacle avoidance system of driverless vehicle based on model predictive control

10.1109/icamechs54019.2021.9661515 ◽

2021 ◽

Author(s):

Zhaoxi Xie ◽

Yanfeng Wu ◽

Jianping Gao ◽

Chuanjie Song ◽

Wenjian Chai ◽

...

Keyword(s):

Model Predictive Control ◽

Obstacle Avoidance ◽

Predictive Control

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Collision prediction and avoidance for satellite ultra-close relative motion with zonotope-based reachable sets

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410018810255 ◽

2018 ◽

Vol 233 (11) ◽

pp. 3920-3937

Author(s):

Zhanpeng Xu ◽

Xiaoqian Chen ◽

Yiyong Huang ◽

Yuzhu Bai ◽

Qifeng Chen

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Control Method ◽

Reachable Sets ◽

Close Relative ◽

Worst Case ◽

Reference Orbit ◽

Robust Model Predictive Control ◽

Collision Prediction ◽

Robust Model

Collision prediction and avoidance are critical for satellite proximity operations, and the key is the treatment of satellites' motion uncertainties and shapes, especially for ultra-close autonomous systems. In this paper, the zonotope-based reachable sets are utilized to propagate the uncertainties. For satellites with slender structures (such as solar panels), their shapes are simplified as cuboids which is a special class of zonotopes, instead of the classical sphere approach. The domains in position subspace influenced by the uncertainties and shapes are determined, and the relative distance is estimated to assess the safety of satellites. Moreover, with the approximation of the domains, the worst-case uncertainties for path constraints are determined, and a robust model predictive control method is proposed to deal with the line of sight and obstacle avoidance constraints. With zonotope representations of satellites, the proposed robust model predictive control is capable of handling the shapes of the satellite and obstacle simultaneously. Numerical simulations demonstrate the effectiveness of the proposed methods with an elliptic reference orbit. 1

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