He, YupingRen, JingSikder, Tushita2017-09-222022-03-292017-09-222022-03-292017-07-01https://hdl.handle.net/10155/806The exponential growth in freightage and the ever-increasing traffic congestion has aided Long Combination Vehicles (LCVs) to emerge as an economical and pragmatic solution for freight transport compared to single unit vehicles. Despite their numerous merits, LCVs face certain stability challenges at high speeds and exhibit inferior maneuverability at low speeds. LCVs are especially susceptible to unstable motion modes, such as rollover, jack-knifing and trailer sway, which has escalated strong concerns regarding their safety. Therefore, it is imperative to develop safety systems with a focus on improving stability, and ensuring safety of LCVs. Active safety systems such as Active Trailer Steering (ATS), have been widely explored to overcome these stability challenges. So far, the design of ATS systems have utilised the Linear Quadratic Regulator (LQR) control technique. Although the LQR technique provides satisfactory results, it fails to control the system in presence of external disturbances such as sensor noise, parametric uncertainties, and un-modelled dynamics. This encourages the need of a robust control strategy. This research focuses on developing an ATS system for a B-train double using robust control techniques. The robust Linear Quadratic Gaussian (LQG) and the 𝜇 synthesis control techniques are employed for designing the ATS control system. The control techniques are analysed under a variety of tests by using numerical simulations. TruckSim and MATLAB/Simulink software packages are used for numerical simulations. The results suggest that the LQG control technique effectively controls the system in the presence of noise, whereas the 𝜇 synthesis control technique is able to achieve desired system performance in the presence of noise, and parametric uncertainties.enLong combination vehiclesRobust controlActive trailer steeringKalman filterMu synthesisDesign of active trailer steering systems for long combination vehicles using robust control techniquesThesis