Dennis Assanis

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SUMMARY Hydraulic hybrid propulsion and energy storage components demonstrate characteristics that are very different from their electric counterparts, thus requiring unique control strategies. This paper presents a methodology for developing a power management strategy tailored specifically to a parallel Hydraulic Hybrid Vehicle (HHV) configured for a(More)
Keywords: Neural networks Nonlinear system identification HCCI engine modeling Multi-layer perceptron Radial basis network Principal component analysis a b s t r a c t Homogeneous charge compression ignition (HCCI) is a futuristic combustion technology that operates with high efficiency and reduced emissions. HCCI combustion is characterized by complex(More)
Extreme Learning Machine (ELM) is a promising learning scheme for nonlinear classification and regression problems and has shown its effectiveness in the machine learning literature. ELM represents a class of generalized single hidden layer feed-forward networks (SLFNs) whose hidden layer parameters are assigned randomly resulting in an extremely fast(More)
Homogeneous charge compression ignition (HCCI) is a futuristic automotive engine technology that can significantly improve fuel economy and reduce emissions. HCCI engine operation is constrained by combustion instabilities, such as knock, ringing, misfires, high-variability combustion, and so on, and it becomes important to identify the operating envelope(More)
—The past couple of years have seen a significant increase in powertrain electrification to increase fuel displacement. Car manufacturers have been focusing on various powertrain configurations (e.g., parallel, series, power-split) and applications (e.g., Hybrid Electric Vehicles [HEVs], Plug-in HEVs [PHEVs]). In parallel, numerous engine technologies offer(More)
— Extreme Learning Machine (ELM) is an emerging learning paradigm for nonlinear regression problems and has shown its effectiveness in the machine learning community. An important feature of ELM is that the learning speed is extremely fast thanks to its random projection preprocessing step. This feature is taken advantage of in designing an online parameter(More)
—Homogeneous charge compression ignition (HCCI) is a futuristic combustion technology that operates with a high fuel efficiency and reduced emissions. HCCI combustion is characterized by complex nonlinear dynamics which necessitates a model based control approach for automotive application. HCCI engine control is a nonlinear, multi-input multi-output(More)
Keywords: Online learning Extreme learning machine System identification Lyapunov stability Engine control Operating envelope a b s t r a c t We propose and develop SG-ELM, a stable online learning algorithm based on stochastic gradients and Extreme Learning Machines (ELM). We propose SG-ELM particularly for systems that are required to be stable during(More)
—In this article, a stochastic gradient based online learning algorithm for Extreme Learning Machines (ELM) is developed (SG-ELM). A stability criterion based on Lyapunov approach is used to prove both asymptotic stability of estimation error and stability in the estimated parameters suitable for identification of nonlinear dynamic systems. The developed(More)