A novel observer design for simultaneous estimation of vehicle steering angle and sideslip angle
Both steering angle and sideslip angle are important states for vehicle handling and stability control. Instead of directly measuring these angles, indirect estimation of these states will provide a cost-effective way for the implementation of vehicle control systems. In the past, model-based methods have been proposed to estimate the sideslip angle with the measured steering angle. In this paper, a novel observer design is presented for simultaneous estimation of vehicle steering angle and sideslip angle so that the estimation of sideslip angle does not require the measurement of steering angle and the estimate of steering angle can also be used for other purposes, such as automatic steering control, steering system fault diagnosis, and driving performance monitoring. To enable this observer design, the Takagi–Sugeno (T–S) fuzzy modeling technique is applied to represent the vehicle lateral dynamics model with nonlinear Dugoff tyre model and time-varying vehicle speed. A T-S observer is then designed to simultaneously estimate the steering angle and sideslip angle with the measurements of yaw rate and vehicle speed, and is designed to be robust against parameter uncertainties and unknown inputs. The conditions for designing such an observer are derived in terms of linear matrix inequalities (LMIs). Experimental results are used to validate the effectiveness of the proposed approach. The results show that the designed observer can effectively estimate steering angle and sideslip angle despite the variation of vehicle longitudinal speed.
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