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Multi-Objective Pareto Robust Design of PID Controllers for Variable Compression Ratio Engines Using Genetic Algorithms

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Modern automobile engines must satisfy the challenging and often conflicting goals of minimizing exhaust emissions, providing increased fuel economy and satisfying driver performance requirements over a wide range of operating conditions. An innovative mechanical design approach to achieve these goals has been the development of variable compression ratio (VCR) engines. A challenge with this new engine design is that the compression ratio has a direct influence on the output torque. This is a problem because the engine driver can feel it as a jerk in the movement. Therefore, in order to fully take the advantage of benefits of this engine design it is necessary to have some sort of torque control that can keep a constant torque regardless of changes in compression ratio. In this work a control-oriented engine model is developed to represent a variable compression ratio engine over a range of operating conditions. The model is validated with some available experimental data. Based on the mode, a robust PID controller is optimally designed to control the output torque for the step changes of compression ratio in the presence of parametric uncertainties.
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VCR Engine; Torque Modeling; Robust Control; Multi-Objective Optimization

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