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Nonlinear Estimation and Control of Automotive Drivetrains discusses the control problems involved in automotive drivetrains, particularly in hydraulic Automatic Transmission (AT), Dual Clutch Transmission (DCT) and Automated Manual Transmission (AMT). Challenging estimation and control problems, such as driveline torque estimation and gear shift control, are addressed by applying the latest nonlinear control theories, including constructive nonlinear control (Backstepping, Input-to-State Stable) and Model Predictive Control (MPC). The estimation and control performance is improved while the calibration effort is reduced significantly. The book presents many detailed examples of design processes and thus enables the readers to understand how to successfully combine purely theoretical methodologies with actual applications in vehicles. The book is intended for researchers, PhD students, control engineers and automotive engineers. Hong Chen is a professor at the State Key Laboratory of Automotive Simulation and Control, and the Department of Control Science and Engineering at Jilin University. Bingzhao Gao is an associate professor at the State Key Laboratory of Automotive Simulation and Control at Jilin University.
Automotive Control is a rapidly developing field for both researchers and industrial practitioners. The field itself is wide ranging and includes engine control, vehicle dynamics, on-board diagnosis and vehicle control issues in intelligent vehicle highway systems.Leading researchers and industrial practitioners were able to discuss and evaluate current developments and future research directions at the first international IFAC workshop on automotive control. This publication contains the papers covering a wide range of topics presented at the workshop.
Publishes theoretical and applied original papers in dynamic systems. Theoretical papers present new theoretical developments and knowledge for controls of dynamical systems together with clear engineering motivation for the new theory. Applied papers include modeling, simulation, and corroboration of theory with emphasis on demonstrated practicality.
This book presents techniques such as the robust control and nonlinearity approximation using linear-parameter-varying (LPV) techniques. Meanwhile, the control of independently driven electric vehicles and autonomous vehicles is introduced. It covers a comprehensive literature review, robust state estimation with uncertain measurements, sideslip angle estimation with finite-frequency optimization, fault detection of vehicle steering systems, output-feedback control of in-wheel motor-driven electric vehicles, robust path following control with network-induced issues, and lateral motion control with the consideration of actuator saturation. This book is a good reference for researchers and engineers working on control of electric vehicles.