Design And Experimental Validation Of A Lateral LPV Control Of Autonomous Vehicles

Abstract

This paper presents a multi-scenario full-range speed lateral automated vehicle controller. A speed-dependent LPV model is designed to deal with two different situations: 1) vehicle tracking capabilities to follow a pre-defined trajectory; and 2) vehicle response to sudden reference changes as occur either when activating the automated system for the first time or when performing a lane-change. The proposed solution is based on the Linear Parameter Varying (LPV) control approach, where an output-feedback dynamical controller is designed based on the Linear Matrix Inequalities (LMIs). The control synthesis is carried out using the Linear Fractional Transformation approach, to reduce the conservatism, combined with the H∞ control problem. Simulation results show the tracking performance and the smoothness of the control inputs which provides a comfortable riding. Finally, the algorithm has been implemented on a robotized Renault ZOE and validates on test tracks, providing encouraging results.

Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles

“…This work has proposed a new YK-based method to: 1)Design several gain-scheduled controllers based on interpolation of previously designed LTI controllers at the vertices of the polytopic region; 2)Interpolate between them to obtain various performances. An external signal vector is introduced to the parameter region, which can be used to incorporate any ad-hoc FIGURE 11 Experimental results physically-based interpolation, without adding any conservatism to the design problem. As a result, the closed-loop quadratic stability is guaranteed under arbitrary interpolating signal and arbitrary parameter-variations.…”

“…LPV control design methods have been examined with successful control applications on autonomous vehicles, see for instance 10 , 11 , 12 and references therein. Nonetheless, it is today admitted that designing a single LPV controller for a large number of parameters, and/or for a wide range of variations of parameters may be conservative 13 .…”

Multi‐variable and multi‐objective gain‐scheduled control based on Youla‐Kucera parameterization: Application to autonomous vehicles

“…Recent works have been investigated in the theory and application of LPV as shown in the books, [11][12][13] and surveys. 6,14 LPV control design methods have been examined with successful control applications on autonomous vehicles, see for instance 10,[15][16][17][18] and references therein. Nonetheless, it is today admitted that designing a single LPV controller for a large number of parameters, and/or for a wide range of variations of parameters may be conservative.…”

“…A main motivation behind considering an interpolation scheme between multiple LPV controllers is the application to autonomous vehicles. Several studies have involved the LPV control approaches to solve the lateral tracking problem over the full speed-range (speed as the varying parameter), such as LPV/LFT 15 and grid-based LPV. 16,38 However, it is not sufficient to achieve several tracking performances (e.g., smooth and aggressive).…”

Real-Time Look-Ahead Distance Optimization for Smooth and Robust Steering Control of Autonomous Vehicles

“…The lateral control scheme usually contains two main components [16], [25]: 1) A feedforward term which concerns the reference trajectory by considering the road curvature and vehicle speed (see Fig. 1).…”