Stochastic Control of the Activated Sludge Process

1991 ◽  
Vol 24 (6) ◽  
pp. 249-255 ◽  
Author(s):  
John C. Kabouris ◽  
Aris P. Georgakakos
Keyword(s):  
Optimal Control ◽  
Activated Sludge ◽  
Time Management ◽  
Stochastic Optimal Control ◽  
Process Model ◽  
Control Method ◽  
Activated Sludge Process ◽  
Hypothetical Case ◽  
Optimal Control Method

A stochastic optimal control method is introduced and applied to the real-time management of an activated sludge process. The method includes a detailed dynamic process model and accounts for input uncertainty. The objective is to minimize the expected variations of effluent organic concentrations and is met by manipulating process flowrates. The method is applied to a hypothetical case study.

Accounting for Different Time Scales in Activated Sludge Process Control

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1381-1390 ◽  
Author(s):  
J. C. Kabouris ◽  
A. P. Georgakakos
Keyword(s):  
Optimal Control ◽  
Activated Sludge ◽  
Uncertainty Propagation ◽  
Multiple Time ◽  
Multiple Time Scale ◽  
Activated Sludge Process ◽  
Computationally Efficient ◽  
Reduced Order ◽  
Different Time Scales

A multirate approach is presented for the integration and discrete linearization of the activated sludge dynamics, that can be readily incorporated in optimal control and uncertainty propagation algorithms. This procedure fully accounts for the existence of multiple time-scale clusters in the activated sludge process and lends itself to a computationally efficient implementation. The method is verified in a computational case study involving a reduced-order version of the IAWPRC model.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

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