Path control method for intelligent harvesting robot considering time delay and environmental constraints

Abstract

The invention discloses a path control method for an intelligent harvesting robot considering time delay and environmental constraints, and belongs to the technical field of unmanned assisted driving in modern agriculture. The invention includes the following steps: establishing a dynamic model, a kinematic model, a harvester-ground force model of the steering system of the harvester, and constructing a control system model considering input delay and external disturbance, and taking the comprehensive error as a state variable; The performance function is set to constrain the state variable, and the constrained variable is converted into an unconstrained variable through the error conversion function; for the two cases of constant input delay and time-varying input delay, the construction based on constant delay and time-varying input delay are constructed respectively. The saturation compensation variable of the time delay estimate is designed, and the corresponding control input is designed based on the backstepping method and Lyapunov stability theorem. This method can effectively constrain the tracking error and compensate the influence of the input delay on the tracking system, so as to improve the automatic driving and navigation effect of the harvester.

Description

technical field [0001] The invention belongs to the technical field of unmanned assisted driving in modern agriculture, and in particular relates to a path control method for an intelligent harvesting robot considering time delay and environmental constraints. Background technique [0002] The assisted driving system of the harvester is affected by the control signal transmission and the execution of the steering mechanism, which will cause time lag, reduce the stability and dynamic performance of the control system, affect the control accuracy and work efficiency of the assisted driving system of the harvester, and limit agricultural production efficiency and even Damage the harvester. At present, the tracking control methods used for harvesters mainly include PID control, pure tracking control, fuzzy control, model predictive control, etc., or through the joint design of two or more methods to optimize parameters and enhance robustness. The previous algorithms do not cons...

AI Technical Summary

Problems solved by technology

The previous algorithms did not consider the influence of time lag on the path tracking control system, while the model predictive control has a predictive function, that is, it can predict the future control input in advance according to the current control input of the system and past historical information. Compensate for the lag of the harvester to a certain extent, but the computational cost required to calculate the optimal value is relatively high

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