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Onboard vehicle parameter estimation is an important procedure for advanced vehicle control tasks, especially for vehicles whose payload configurations vary in day-to-day use. This study presents a newly proposed estimation method based on the Ackermann’s steering geometry (ASG) that aims to estimate multiple vehicle's center of gravity (CG) position and inertial parameters at the same time. In this method, the vehicle planar motion equations are first synthesized into a form where only the lateral force of one front wheel and longitudinal forces appear. This way, the influence of uncertainties in the tire lateral force models is greatly reduced. Then, the condition of eliminating the remaining front wheel lateral force term can be derived, which is exactly the Ackermann’s steering geometry. When the influence of lateral tire force terms are eliminated, regression technique is applied to estimate the needed vehicle parameters. Vehicle’s suspension kinematics is also considered in the processing of dynamic signals. Unlike conventional methods in estimating vehicle’s payload related parameters, the new method requires neither lateral tire force model nor accurate suspension property parameters. Simulations in CarSim®-Simulink environment verified that the proposed method is capable of estimating vehicle parameters such as CG position and inertial parameters at the same time.

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Abstract-The adaptive fault-tolerant control problem for descriptor nonlinear system is researched in this paper. Contents include the properties of Adaptive Fault-tolerant like uncertainties, state delays, and input delays using T-S fuzzy model. First, the design of the state observer to estimate system state and sensor fault is introduced. Then, the adaptive fault-tolerant control structure with the state observer is proposed when combining with the sliding model control (SMC) and the adaptive generic model control (AGMC). Finally, an adaptive fault-tolerant control structure for nonlinear descriptor system is constructed. About above results, both of theoretical analysis and illustrative examples demonstrating the feasibility and validity were proposed.Index Terms-Fault-tolerant control, T-S fuzzy, observer, sliding model control, adaptive generic model control.