Abstract
Automotive engine control has been continuously improved due to the strong demands from the society and the market since introducing electronic controls but not always following control theories. Therefore, it is not easy for researchers from academia and even engineers from the automotive industry to grasp the whole aspect of engine control. To encounter the issue, important features of engine control are extracted and generalized from the standpoint of control engineering. Comparisons of the control and model predictive control (MPC) showed an outstanding performance of the control generalized from engine controls and how to apply MPC in the framework.
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Akira OHATA graduated from Tokyo Institute of Technology in 1973, and directly joined Toyota Motor Corporation. He was involved in exhaust gas emission control, variable intake system, HEV control, vehicle controls, model-based development (MBD), and the education of advanced control theory at Toyota. He had the standardization activity of software dependability assurance of consumer devices in Object Management Group (OMG). He was a senior general manager of Toyota Motor Corporation, a research fellow of Information Technology Agency (IPA) under the Ministry of Economy, Trade, and Industry. He retired from Toyota and joined TECHNOVA as a senior adviser. He received the most outstanding paper award in convergence 2004, technical contribution award from JSAE in 2009, and others in 2012, 2015, and 2016.
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Ohata, A. Comparison of generalized engine control and MPC based on maximum principle. Control Theory Technol. 15, 150–157 (2017). https://doi.org/10.1007/s11768-017-7002-4
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DOI: https://doi.org/10.1007/s11768-017-7002-4