On the interaction of adaptive filtering, identification, and control

This paper presents relevant methods on navigation accuracy improvement of agricultural vehicle focusing on positioning accuracy and control precision. An adaptive kalman filtering, combination of Sage_Husa adaptive filtering and strong tracking kalman filtering based on strict convergence criterion, is adopted to improve filtering accuracy with strong ability of adaptive filtering and restraining filter divergence. A new variable-structure switching method to prevent PID controller from integrator windup can effectively solve the integral saturation phenomenon, which adopts a kind of adaptive adjustment rate to adjust the integral term of PID control algorithm. Finally, this paper puts the improved adaptive filtering and anti-windup variable-structure PID control technique into combination to effectively restrain interference and integral saturation, so as to achieve the purpose of improving system stability and control precision. The simulation and experiment results show that methods described above greatly enhance the capabilities of restraining filtering divergence and improving control precision.

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Autonomous navigation control based on improved adaptive filtering for agricultural robot

International Journal of Advanced Robotic Systems ◽

10.1177/1729881420925357 ◽

2020 ◽

Vol 17 (4) ◽

pp. 172988142092535

Author(s):

Weikuan Jia ◽

Yuyu Tian ◽

Huichuan Duan ◽

Rong Luo ◽

Jian Lian ◽

...

Keyword(s):

Adaptive Filtering ◽

Autonomous Navigation ◽

Dynamic Performance ◽

Variable Structure ◽

Convergence Criteria ◽

Agricultural Robots ◽

Navigation Control ◽

Navigation Accuracy ◽

And Control ◽

Agricultural Robot

Under the complex agricultural operation environment, reliable navigation system is the basic guarantee to realize the agricultural robot automated operation. This study focuses on improving navigation accuracy and control accuracy and conducts related research on autonomous navigation control of agricultural robots. This article discusses the advantages of using strict convergence criteria and combining Sage–Husa adaptive filtering with strong tracking Kalman filtering and then proposes an improved adaptive Kalman filter algorithm. The new algorithm can effectively suppress the filter divergence, improve the dynamic performance of the filter, and ensure its better filtering accuracy and strong adaptive ability to improve navigation accuracy of GPS. Further variable structure switching method is used to prevent proportional integral differential (PID) controller integral saturation phenomenon, which effectively solves the controller over-saturation problem. And combining this method with an improved adaptive filtering algorithm not only can effectively inhibit control interference but also achieve the anti-saturation effect, thereby enhancing the stability and accuracy of the control system. Finally, the simulation and experiment of the new method show that the proposed method greatly improves the ability of the filter to suppress divergence and control precision.

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