Anh-Tu Nguyen

Driver-Automation Cooperative Approach for Shared Steering Control Under Multiple System Constraints: Design and Experiments

This paper addresses the shared lateral control between a human driver and a lane keeping assist system of intelligent vehicles for both lane keeping and obstacle avoidance. This control issue is very challenging in todays automotive industry due to the human–machine interaction involved in the control design. In this paper, we propose a new approach to consider such an interaction via a fictive driver activity parameter introduced into the road–vehicle system. Hence, the steering assistance actions can be computed according to the drivers real-time behaviors. The Takagi–Sugeno fuzzy control approach is proposed to deal with the time-varying driver activity parameter and vehicle speed. Especially, the concept of robust invariant set is exploited using Lyapunov arguments to handle theoretically both system state and control input limitations. Considering these system constraints in the control design procedure aims to improve the drivers safety and comfort. Experimental tests with a human driver and an advanced interactive dynamic driving simulator are conducted to show the effectiveness of the proposed method.

Fuzzy steering control for autonomous vehicles under actuator saturation: Design and experiments

Abstract This paper presents a new control method for autonomous vehicles. The design goal is to perform the automatic lane keeping under multiple system constraints, namely actuator saturation of the steering system, roads with unknown curvature and uncertain lateral wind force. Such system constraints are explicitly taken into account in the control design procedure. To achieve this goal, we propose a new constrained Takagi–Sugeno fuzzy model-based control method using fuzzy Lyapunov control framework. The resulting non-parallel distributed compensation controller is able to handle not only various system constraints but also a large variation range of vehicle speed. In particular, Taylor’s approximation method is exploited to reduce not only the numerical complexity for real-time implementation but also the conservatism of the results. The design conditions are strictly expressed in terms of linear matrix inequalities which can be efficiently solved with available numerical solvers. The effectiveness of the proposed control method is demonstrated through both simulation and hardware experiments with various driving scenarios.

An augmented system approach for LMI-based control design of constrained Takagi-Sugeno fuzzy systems

In this paper, we address the control design of a class of constrained Takagi-Sugeno fuzzy systems. These systems are subject to both control input and state constraints. Sufficient design conditions are derived via a judicious use of an equivalent augmentation form of the closed-loop system together with a new parameter-dependent Lyapunov function. The control input nonlinearity is dealt with via a generalized sector condition. These instrumental control tools allow reducing significantly the conservatism of the results while keeping a simple control structure with a low level of numerical complexity. In particular, it has been shown that in many cases the new method can provide better results (in terms of conservatism reduction) than some recent works developed in non-quadratic Lyapunov framework. Several numerical examples are given to illustrate the effectiveness of the proposed method.

Online adaptation of the authority level for shared lateral control of driver steering assist system using dynamic output feedback controller

This paper is devoted to the development of a shared lateral control strategy for a Driver Steering Assist System (DSAS) that can share the authority with the driver. Up to now, this control issue is still an open research subject in automotive industry due to the complex interactions according to different driving situations between the Human (driver) and the Machine (DSAS). In this work, such interactions are handled by introducing into the vehicle system a fictive time-varying term representing the driver activity. In this way, the actions of the DSAS are computed in function of the driver behaviors (actions and intentions). Using Takagi-Sugeno control technique in the framework of Lyapunov stability theorem, the designed controller is able to handle a large range of variation of vehicle longitudinal speed. Moreover, the proposed controller requires only measured output signals for the design procedure and implementation. The effectiveness of the proposed method is demonstrated with different driving scenarios.

Feedback Linearization-Based Control Approach for Air System of a Turbocharged SI Engine: Toward a Fuel-Optimal Strategy

Combining turbocharging with downsizing has now become a key technique for automotive engine to improve its performance as fuel economy and drivability. The technology potential is fully exploited only with an efficient air path management system. In this context, the present work addresses a novel control design based on feedback linearization for the turbocharged air system of a SI engine. Two control strategies have been investigated for this complex system: drivability optimization and fuel reduction. The effectiveness of the proposed approach is evaluated via an advanced engine simulator.