| GAUSSIAN PROCESS REGRESSION FEEDFORWARD CONTROLLER FOR DIESEL ENGINE AIRPATH |
| Volkan Aran1, Mustafa Unel2 |
1Ford OTOSAN
2Sabanci University |
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| ABSTRACT |
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Gaussian Process Regression (GPR) provides emerging modeling opportunities for diesel engine control. Recent serial production hardwares increase online calculation capabilities of the engine control units. This paper presents a GPR modeling for feedforward part of the diesel engine airpath controller. A variable geotmetry turbine (VGT) and an exhaust gas recirculation (EGR) valve outer loop controllers are developed. The GPR feedforward models are trained with a series of mapping data with physically related inputs instead of speed and torque utilized in conventional control schemes. A physical model-free and calibratable controller structure is proposed for hardware flexibility. Furthermore, a discrete time sliding mode controller (SMC) is utilized as a feedback controller. Feedforward modeling and the subsequent airpath controller (SMC+GPR) are implemented on the physical diesel engine model and the performance of the proposed controller is compared with a conventional PID controller with table based feedforward. |
| Key Words:
Gaussian process regression, Feedforward control, Discrete time sliding mode control, Airpath control |
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