This paper provides valuable guidelines on the selection of dynamic vehicle models for control algorithm development, design optimization and linear stability analysis for multi-trailer articulated heavy vehicles with active safety systems. The validation of yaw-plane and yaw-roll models of a tractor-two-semitrailer combination using the TruckSim software package is presented in this paper. A linear four-degree-of-freedom yaw-plane model and a linear seven-degree-of-freedom yaw-roll model of the vehicle were generated, compared and evaluated. The linear models of the multi-trailer articulated heavy vehicle yield numerical simulation results which are validated by comparing with those obtained from the corresponding non-linear TruckSim model. This paper also includes eigenvalue and frequency-response analysis of the linear models to estimate the unstable motion modes and to predict the unique dynamic features of the multi-trailer articulated heavy vehicle in the frequency domain. A benchmark investigation of the models was performed to examine the fidelity, the complexity and the applicability of the linear models.

This paper presents a design synthesis framework for directional performance optimization of multi-trailer articulated heavy vehicles with trailer lateral dynamic control systems, e.g. active trailer steering, trailer differential braking, active roll control or the coordination of the three systems. In order to demonstrate the effectiveness of the proposed framework, it was applied to the design optimization of a multi-trailer articulated heavy vehicle with an active trailer steering controller. In the design, a set of lateral stability measures is originally defined, and the design problem under simulated test manoeuvres is implemented using a parallel computing technique. It is illustrated that the proposed framework and the performance measures can be used to identify effectively the desired variables and to predict reliably the performance envelopes of multi-trailer articulated heavy vehicles with active safety systems by considering the concept of driver-adaptive-vehicle design.

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Sliding mode control (SMC) has gained a wide acceptance in recent years due to its simplicity and robustness. Discrete-time sliding mode control (DSMC) is advantageous over its continuous-time counterparts due to the development in digital signal processing. However, little attention has been paid to the application of DSMC to the design of active suspensions. In this research, DSMC-based active suspensions are designed using both the SMC theory and a genetic algorithm (GA) to improve the ride quality and handling performance with the full states observed by a discrete-time Kalman filter. The extensive computation demand levied by the GA is handled by using the parallel computation technique. The proposed optimization-based SMC approach simplifies the design process and improves the overall performance of the controlled system.

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This paper examines the robustness of different controllers for active steering systems (ASSs) of articulated heavy vehicles (AHVs) in terms of the directional performance. Controllers based on the linear quadratic regulator (LQR) technique were designed for ASSs. The success of the LQR-based controllers is dependent on the accuracy of linear models for AHVs. When designing ASS controllers, linearisation of the AHV models is usually necessary; this results in model inaccuracy and un-modelled dynamics, and the robustness of the LQR-based controllers may be degraded. ASSs for AHVs are assessed in the time-domain, which may lead to an incomplete performance evaluation. This paper assesses the robustness of the ASS controllers designed with the techniques of sliding mode control (SMC), nonlinear sliding mode control (NSMC), and mu-synthesis (MS). The ASS controllers are evaluated using numerical simulation in terms of the trade-off between the manoeuvrability and the lateral stability at high speeds.

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