A Predictive Control Algorithm for an Anti-Lock Braking System

Author(s):  
Sohel Anwar ◽  
Behrouz Ashrafi
2020 ◽  
Author(s):  
Yongtao Zhao ◽  
Yiyong Yang ◽  
Xiuheng Wu ◽  
Xingjun Tao

Abstract Accurate pressure control and fast dynamic response are vital to the pneumatic electric braking system (PEBS) for that commercial vehicles require higher regulation precision of braking force on four wheels when braking force distribution is carried out under some conditions. Due to the lagging information acquisition, most feedback-based control algorithms are difficult to further improve the dynamic response of PEBS. Meanwhile, feedforward-based control algorithms like predictive control perform well in improving dynamic performance. but because of the large amount of computation and complexity of this kind of control algorithm, it cannot be applied in real-time on single-chip microcomputer, and it is still in the stage of theoretical research at present. To address this issue and for the sake of engineering reliability, this article presents a logic threshold control scheme combining analogous model predictive control (AMPC) and proportional control. In addition, an experimental device for real-time measuring PEBS multi-dynamic parameters is built. After correcting the key parameters, the precise model is determined and the influence of switching solenoid valve on its dynamic response characteristics is studied. For the control scheme, numerical and physical validation are executed to demonstrate the feasibility of the strategy and for the performance of the controller design. The experimental results show that the dynamic model of PEBS can accurately reflect its pressure characteristics. Furthermore, under different air source pressures, the designed controller can stably control the pressure output of PEBS and ensure that the error is within 8KPa. Compared with the traditional control algorithm, the rapidity is improved by 32.5%.


2016 ◽  
Vol 49 (7) ◽  
pp. 1079-1084 ◽  
Author(s):  
Anca Maxim ◽  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Corneliu Lazar ◽  
Robin De Keyser

2013 ◽  
Vol 433-435 ◽  
pp. 1091-1098
Author(s):  
Wei Bo Yu ◽  
Cui Yuan Feng ◽  
Ting Ting Yang ◽  
Hong Jun Li

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.


2008 ◽  
Vol 41 (2) ◽  
pp. 2099-2104 ◽  
Author(s):  
A. Jacquet ◽  
Y. Chamaillard ◽  
M. Basset ◽  
G. Gissinger ◽  
D. Frank ◽  
...  

Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.


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