AUTOMATIC GUIDANCE OF FARM VEHICLES IN PRESENCE OF SLIDING EFFECTS

High-precision autofarming is rapidly becoming a reality with the requirements of agricultural applications. Lots of research works have been focused on the automatic guidance control of farm vehicles, satisfactory results have been reported under the assumption that vehicles move without sliding. Realistic paths that farm vehicles can track successfully include not only rows but also arcs and curves. But unfortunately the pure rolling constraints are not always satisfied especially in agriculture applications where the working conditions are rough and not expectable. A possible solution would be to close the feedback loop using exteroceptive sensor measurements. Thanks to GPS and attitude sensors, vehicle positions and velocities can be obtained by absolute coordinates measurements regardless of sliding. Hence the aim of this work is to design anti-sliding controllers for all-terrain autonomous farm vehicles relying on GPS measurements. A kinematic model which exactly integrates uncertain sliding effects is created in path frame based on geometric and velocity constraints. Through linearization, sliding appears as additive unknown variables to the ideal kinematic model, which provides a good research basis for following controller design. A threedimensional dynamic model is constructed with Newton’s laws. Sliding effects are introduced in the form of tire slip angles. Uncertainties of sliding effects are described by cornering stiffness coefficients which depend on contact conditions between tires and grounds. In order to ensure GPS-based controllers are applicable in presence of sliding, it is also proven that all the information necessary to controller design is available by either GPS measurements or reconstruction. Thanks to the kinematic model in which sliding effects are integrated as additive disturbances, robust control theories are utilized. By transforming the vehicle-oriented kinematic model into a perturbed chained system, a sliding mode controller, which is robust not only to the sliding effects but also to the input noise, is designed with the help of the natural algebraic structure of chained systems. Simulation results show that the proposed sliding mode controller can guarantee high path-following accuracy even in the presence of sliding. Alternatively sliding can be regarded as unknown model parameters. Based on backstepping methods a stepwise procedure is proposed to design an adaptive controller in which time-invariant sliding effects are learned and compensated by parameter adaptations. It is theoretically proven that for the farm vehicles subject to time-invariant sliding, the lateral deviation can be stabilized near zero and the orientation errors converge into a neighborhood near the origin. To be more robust to disturbances including external noises and unmodeled time-varying sliding components, the adaptive controller is refined by integrating Variable Structure Controllers (VSC) or projection mappings. Simulation results show that the proposed robust adaptive controllers can reject sliding effects and guarantee high lateral accuracy with about zero mean values. For automatic guidance of agriculture vehicles, lateral control is not the only duty, the problem of longitudinal-lateral control for autonomous farm vehicles in presence of sliding is also addressed. To take sliding effects into account, two variables which characterize sliding effects are introduced into the kinematic model with respect to the vehicle body frame based on geometric and velocity constrains. With linearization approximation a refined kinematic model is obtained in which sliding appears as additive unknown parameters to the ideal kinematic model. By integrating parameter adaptation technique with backstepping method, a stepwise procedure is proposed to design a robust adaptive controller in which time-invariant sliding is compensated by parameter adaptation and time-varying sliding is corrected by VSC. It is theoretically proven that for the farm vehicles subjected to sliding, the longitudinal-lateral deviations can be stabilized near zero and the orientation errors converge into a neighborhood near the origin. To be more realistic for agriculture applications, an adaptive controller with projection mapping is also proposed. Simulation results show that the proposed (robust) adaptive controllers can guarantee high longitudinal-lateral tracking accuracy regardless of sliding.