A complete formulation of non-linear model-based stable predictive control strategy

2001 ◽  
Author(s):  
G. Prasad ◽  
G.W. Irwin ◽  
E. Swidenbank ◽  
B. W. Hogg
Keyword(s):  
Linear Model ◽  
Predictive Control ◽  
Control Strategy ◽  
Model Based ◽  
Complete Formulation ◽  
Non Linear

Non-linear model based predictive control

1999 ◽  
Vol 72 (10) ◽  
pp. 919-928 ◽  
Author(s):  
B. Kouvaritakis ◽  
M. Cannon ◽  
J. A. Rossiter
Keyword(s):  
Linear Model ◽  
Predictive Control ◽  
Model Based ◽  
Non Linear

scholarly journals Central Non-Linear Model-Based Predictive Vehicle Dynamics Control

2021 ◽  
Vol 11 (10) ◽  
pp. 4687
Author(s):  
Philipp Maximilian Sieberg ◽  
Dieter Schramm
Keyword(s):  
Control Systems ◽  
Linear Model ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
Influence Factor ◽  
Ride Comfort ◽  
Automated Driving ◽  
Model Based ◽  
Non Linear ◽  
Vehicle Dynamics Control

Considering automated driving, vehicle dynamics control systems are also a crucial aspect. Vehicle dynamics control systems serve as an important influence factor on safety and ride comfort. By reducing the driver’s responsibility through partially or fully automated driving functions, the occupants’ perception of safety and ride comfort changes. Both aspects are focused even more and have to be enhanced. In general, research on vehicle dynamics control systems is a field that has already been well researched. With regard to the mentioned aspects, however, a central control structure features sufficient potential by exploiting synergies. Furthermore, a predictive mode of operation can contribute to achieve these objectives, since the vehicle can act in a predictive manner instead of merely reacting. Consequently, this contribution presents a central predictive control system by means of a non-linear model-based predictive control algorithm. In this context, roll, self-steering and pitch behavior are considered as control objectives. The active roll stabilization demonstrates an excellent control quality with a root mean squared error of 7.6953×10−3 rad averaged over both validation maneuvers. Compared to a vehicle utilizing a conventional control approach combined with a skyhook damping, pitching movements are reduced by 19.75%. Furthermore, an understeering behavior is maintained, which corresponds to the self-steering behavior of the passive vehicle. In general, the central predictive control, thus, increases both ride comfort and safety in a holistic way.

Non-linear model-based predictive control of gasoline engine air-fuel ratio

1998 ◽  
Vol 20 (2) ◽  
pp. 103-112 ◽  
Author(s):  
B. Lennox ◽  
G.A. Montague ◽  
A.M. Frith ◽  
A.J. Beaumont
Keyword(s):  
Linear Model ◽  
Predictive Control ◽  
Gasoline Engine ◽  
Fuel Ratio ◽  
Model Based ◽  
Non Linear

scholarly journals Modified Volterra model-based non-linear model predictive control of IC engines with real-time simulations

2016 ◽  
Vol 39 (2) ◽  
pp. 208-223 ◽  
Author(s):  
Yiran Shi ◽  
Ding-Li Yu ◽  
Yantao Tian ◽  
Yaowu Shi
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Linear Model ◽  
Predictive Control ◽  
Fuel Injection ◽  
Volterra Model ◽  
Ic Engine ◽  
Model Based ◽  
Significant Difference ◽  
Non Linear

Modelling of non-linear dynamics of an air manifold and fuel injection in an internal combustion (IC) engine is investigated in this paper using the Volterra series model. Volterra model-based non-linear model predictive control (NMPC) is then developed to regulate the air–fuel ratio (AFR) at the stoichiometric value. Due to the significant difference between the time constants of the air manifold dynamics and fuel injection dynamics, the traditional Volterra model is unable to achieve a proper compromise between model accuracy and complexity. A novel method is therefore developed in this paper by using different sampling periods, to reduce the input terms significantly while maintaining the accuracy of the model. The developed NMPC system is applied to a widely used IC engine benchmark, the mean value engine model. The performance of the controlled engine under real-time simulation in the environment of dSPACE was evaluated. The simulation results show a significant improvement of the controlled performance compared with a feed-forward plus PI feedback control.

scholarly journals A novel non-linear model-based control strategy to improve PEMFC water management – The flatness-based approach

2015 ◽  
Vol 40 (5) ◽  
pp. 2371-2376 ◽  
Author(s):  
Cédric Damour ◽  
Michel Benne ◽  
Brigitte Grondin-Perez ◽  
Jean-Pierre Chabriat ◽  
Bruno G. Pollet
Keyword(s):  
Water Management ◽  
Linear Model ◽  
Control Strategy ◽  
Model Based Control ◽  
Model Based ◽  
Non Linear

Efficient non-linear model based predictive control

2001 ◽  
Vol 74 (4) ◽  
pp. 361-372 ◽  
Author(s):  
M. Cannon ◽  
B. Kouvaritakis ◽  
Y. I. Lee ◽  
A. C. Brooms
Keyword(s):  
Linear Model ◽  
Predictive Control ◽  
Model Based ◽  
Non Linear
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