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Path Following Control of Automated Guided Vehicle Based on Model Predictive Control with State Classification Model and Smooth Transition Strategy

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Abstract

Path following control of the automatic guided vehicle (AGV) for material handling in the plant requires a smooth and high-precision continuous attitude adjustment. However, there are many difficulties in designing the controller, such as actuator saturation, parameter selection, and the influence of deviations relations. In this paper, an improved model predictive control SCMPC-ST with a state classification model (SCM) and a smooth transition (ST) strategy is proposed to address these problems. First, based on the deviations relations and the actuator saturation, the SCM is designed to divide the pose states of AGV into three stages. With clearly objective functions and boundary constraints, SCM allows the pose states can be transferred sequentially, which avoids the problem of parameter selection. Second, use the analytical method to resolve SCM to directly obtain the desired control law, which provides excellent performance in real-time. Finally, the smooth transition strategy is built to adjust the control law at the transition step and overshoot step to ensure the stability of the control process. Simulation results show that by focusing on adjusting the deviations relations, SCMPC-ST can make AGV eliminate all deviations continuously and smoothly while maintaining high accuracy.

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Abbreviations

e α :

angular deviation

e d :

displacement deviation

V R :

the right wheel speed

V L :

the left wheel speed

D w :

the distance between the two drive wheels

Δv :

the differential speed

V c :

linear velocity

ω c :

angular velocity

T :

unit sampling time

R a :

rotation radius

E(k):

pose states at step k

S 1 :

deviating stage

S 1a, S 1b, S 1c :

three cases of S1

S 2 :

approaching stage

S 2a, S 2b :

two cases of S2

S 3 :

terminal stage

K 12 :

transition step from S1 to S2

K 23 :

transition step from S2 to S3

K 0 :

overshoot step

N b :

total control steps in S3

N lim :

control step threshold in S3

Δa min, Δa max :

the acceleration constraints of the actuator

Δv*(k):

desired control output

\({\rm{\Delta}}\widetilde{v}\left({\rm{k}} \right)\) :

modified control output

λ :

trial weight

\({\rm{\Delta}}\widehat{v}\left({\rm{k}} \right)\) :

actual control output

k p :

proportional coefficient of PID controller

k i :

integral coefficient of PID controller

k d :

differential coefficient of PID controller

β :

integral separation threshold of PID controller

e f :

the deviation used in PID controller

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Acknowledgement

This work is supported by the Fundamental Research Funds for the Central Universities (NO. 2020RC15).

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Authors and Affiliations

  1. Automation School, Beijing University of Posts and Telecommunication, Beijing, 100876, China

    Xun Weng, Jingtian Zhang & Ying Ma

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  1. Xun Weng
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  2. Jingtian Zhang
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Correspondence to Jingtian Zhang.

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Weng, X., Zhang, J. & Ma, Y. Path Following Control of Automated Guided Vehicle Based on Model Predictive Control with State Classification Model and Smooth Transition Strategy. Int.J Automot. Technol. 22, 677–686 (2021). https://doi.org/10.1007/s12239-021-0063-x

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