Active Front Steering Controller Design with Side Slip Angle Free Model Matching Approach
| Autor: | M. Selcuk Arslan, Mert Sever |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Matching (graph theory) State-space representation Computer science 020302 automobile design & engineering 02 engineering and technology Linear-quadratic regulator Computer Science::Robotics Magic formula Nonlinear system 020901 industrial engineering & automation 0203 mechanical engineering Computer Science::Systems and Control Control theory Convex optimization Full state feedback |
| Zdroj: | 2018 6th International Conference on Control Engineering & Information Technology (CEIT). |
| DOI: | 10.1109/ceit.2018.8751855 |
| Popis: | A side slip angle free model matching controller (MMC) is designed to improve vehicle yaw stability by active front steering. Optimization of controller gains is specified by a classical LQR problem. Additionally, LQR controller gains are structured to enable side slip angle free design. Design of an LQR having a structured controller gain is formulated as a convex optimization problem subject to linear matrix inequalities (LMIs) constraints. The proposed controller is designed with an augmented state space model including a linear bicycle model and model matching error dynamics. Superiority of the proposed controller is shown by numerically comparing with a classical full state feedback LQR. In order to obtain realistic results; a three-degrees-of-freedom nonlinear vehicle model is used. The nonlinear vehicle model is composed of lateral, yaw and longitudinal motions with the well-known Magic Formula tire model. Simulation results show that the proposed structured MMC provides very compatible performance with full state feedback LQR design. |
| Databáze: | OpenAIRE |
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