In this paper, a dynamic mathematical model of an autonomous ground vehicle was used to analyse its transient response and to design a heading-angle controller for the vehicle. A suitable 'control-oriented model' that could accurately characterize the phenomenon of interest was used to design the controller. The efficacy of this model was evaluated by corroborating its results with experimental data. This model included the cornering stiffness of the tyres as an unknown parameter, and two approaches were attempted to estimate its value. The dynamics of the actuator were included in the analysis since the response time to steer the front wheel is of the same order as that of the heading-angle dynamics of the vehicle. The performance of two controllers (namely a classical transfer-function-based controller and an optimal linear quadratic regulator) were evaluated using the IPG: CarMaker Ò simulation platform over a range of speeds. The transfer-function-based controller was also implemented on the experimental test vehicle at low speeds (high-speed experimental implementation was not possible because of safety concerns). It was found that control gain scheduling helped to track the desired heading angles of the vehicle at various speeds. Subsequently, a lane-change manoeuvre using the test vehicle was performed to evaluate the controller further. It was found that the transfer-function-based headingangle controller could provide a comparable performance with that of the linear quadratic regulator, while keeping the sensing requirements to a minimum; thus, it was suitable for real-time implementation in an autonomous ground vehicle.
This paper deals with tracking of desired yaw rate generated by the path planner of an Autonomous Ground Vehicle (AGV) in the presence of unmodeled dynamics, changes in operating conditions and parametric uncertainties. A mathematical model considering the dynamics of the test vehicle and the steering actuator was used for controller design. The estimate of the unknown part of dynamics, called the total disturbance, obtained from the Extended State Observer (ESO) was used by Sliding Mode Controller (SMC) to compensate the actual total disturbance. It was observed that the lower bound on the SMC switching gain depends on the ratio of total disturbance estimation error and assumed known part of the system dynamics. This allows the choice of a low value of SMC switching gain, which in turn resulted in reduced chattering amplitude. Further attenuation in chattering was achieved using a saturation function.
After simulating the designed controller in MATLAB-SIMULINK environment, the controller was validated in IPG: CarMaker® simulation platform over a large operating range by changing the mass distribution of the vehicle, speed of the vehicle, cornering stiffness of the tire and terrain friction coefficient. A look-up table was formulated for the maximum achievable yaw rate at different speeds, i.e., from 5 to 20 m/s, given the maximum steering angle input considering rollover and slip threshold while the terrain friction coefficient was also varied from 0.2 to 0.8. It was observed that the designed controller was robust to changes in operating conditions, parametric uncertainties and unmodeled dynamics.
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