MPC-based high-speed trajectory tracking for 4WIS robot

Liu, Xinxin; Wang, Wei; Li, Xuelong; Liu, Fusheng; He, Zhihang; Yao, Yonggang; Ruan, Huaping; Zhang, Tong

doi:10.1016/j.isatra.2021.05.018

Cited by 41 publications

(15 citation statements)

References 15 publications

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“…For the Koopman high-dimensional model with disturbance (23), the control output should contain the output of the undisturbed nominal system and disturbance compensation value, and the control variable 𝒖(𝑘) can be expressed as:…”

Section: Optimization Problemmentioning

confidence: 99%

Emergency supplies transportation robot trajectory tracking control based on Koopman and improved event-triggered model predictive control

Zhang

Tang

Zhang³

et al. 2023

Preprint

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In the emergency rescue and disposal of social public emergencies, supply transportation effectively provides a strong supply foundation and realistic conditions. The trajectory tracking control of emergency supplies transportation robot is the key technology to ensure the timeliness of transportation. In this paper, the emergency supplies transportation robot is taken as the research object, based on Koopman operator theory, combined with radial basis function (RBF) neural network disturbance observer and adaptive prediction horizon event-triggered model predictive control (APET-MPC) algorithm to investigate the purely data-driven trajectory tracking control problem of emergency supplies transportation robot when the model parameters and models are unknown. Firstly, the Koopman operator is used to establish a high-dimensional linear model of the robot. Secondly, the RBF neural network disturbance observer is designed to estimate the disturbance during the robot operation and compensate it to the controller. Thirdly, APET-MPC is used to optimize the trajectory tracking control of the emergency supplies transportation robot to reduce computational complexity. Finally, the performance of the proposed trajectory tracking controller is verified by Carsim/ Simulink joint simulation. The simulation results show that the model established by Koopman operator theory can achieve the high accuracy approximation of the robot. Compared with the MPC trajectory tracking controller, the APET-MPC trajectory tracking controller based on RBF neural network disturbance observer (RBF-APET-MPC) improves the tracking accuracy of the robot and reduces the total triggering times of the system by more than 50%.

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Section: Optimization Problemmentioning

confidence: 99%

Emergency supplies transportation robot trajectory tracking control based on Koopman and improved event-triggered model predictive control

Zhang

Tang

Zhang³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…First, we need to discretize the equation of state. By using the forward Euler method to discretize equation ( 5) at time k (Liu et al, 2022), we can get the following:…”

Section: Predictive Modementioning

confidence: 99%

“…First, we need to discretize the equation of state. By using the forward Euler method to discretize equation (5) at time k (Liu et al , 2022), we can get the following: where A¯=E+TA, B¯true(ktrue)=TB(k), E is the identity matrix and T is the system control cycle duration.…”

Section: Model Predictive Controlmentioning

confidence: 99%

Bounding gait control of a parallel quadruped robot

Hao,

Wei,

Qiao

et al. 2023

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Purpose The computing power of the legged robot is not enough to perform high-frequency updates for the full-body model predictive control (MPC) of the robot, which is a common problem encountered in the gait research of the legged robot. The purpose of this paper is to propose a high-frequency MPC control method for the bounding gait of a parallel quadruped robot. Design/methodology/approach According to the bounding gait characteristics of the robot, the quadruped robot model is simplified to an equivalent plane bipedal model. Under the biped robot model, the forces between the robot’s feet and the ground are calculated by MPC. Then, the authors apply a proportional differential controller to distribute these forces to the four feet of the quadruped robot. The robot video can be seen at www.bilibili.com/video/BV1je4y1S7Rn. Findings To verify the feasibility of the controller, a prototype was made, and the controller was deployed on the actual prototype and then fully analyzed through experiments. Experiments show that the update frequency of MPC could be stabilized at 500 Hz while the robot was running in the bounding gait stably and efficiently. Originality/value This paper proposes a high-frequency MPC controller under the simplified model, which has a higher working efficiency and more stable control performance.

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“…The proposed controller was verified through a simulation and then evaluated in a real heavy-duty vehicle [ 23 ]. Liu et al, proposed an MPC algorithm with dynamic constraints by combining feedforward control as a method of tracking the path of a four-wheeled independent steering robot composed of a steering and driving motor, considering the operation delay of the steering motor [ 24 ]. Jeong et al, proposed an algorithm that tracks paths based on yaw rates and generates yaw moments to distribute them to four wheels based on weighted pseudo-inverse-based control allocation (WPCA) for improved path tracking performance in four-wheel independent steering and driving systems [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Development of a Particle Filter-Based Path Tracking Algorithm of Autonomous Trucks with a Single Steering and Driving Module Using a Monocular Camera

Kim

Jang

et al. 2023

Sensors

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Recently, in various fields, research into the path tracking of autonomous vehicles and automated guided vehicles has been conducted to improve worker safety, convenience, and work efficiency. For path tracking of various systems applied to autonomous driving technology, it is necessary to recognize the surrounding environment, determine technology accordingly, and develop control methods. Various sensors and artificial-intelligence-based perception methods have limitations in that they must learn a large amount of data. Therefore, a particle-filter-based path tracking algorithm using a monocular camera was used for the recognition of target RGB. The path tracking errors were calculated and a linear-quadratic-regulator-based desired steering angle were derived. The autonomous trucks were steered and driven using a pulse-width-modulation-based steering and driving motor. Based on an autonomous truck with a single steering and driving module, it was verified that the path tracking could be used in three evaluation scenarios. To compare the LQR-based path tracking control performance proposed in this paper, an elliptical path tracking scenario using a conventional sliding mode control with robust control performance was performed. The results show that the RMS of the lateral preview error of the SMC was approximately 18% larger than that of the LQR-based method.

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MPC-based high-speed trajectory tracking for 4WIS robot

Cited by 41 publications

References 15 publications

Emergency supplies transportation robot trajectory tracking control based on Koopman and improved event-triggered model predictive control

Emergency supplies transportation robot trajectory tracking control based on Koopman and improved event-triggered model predictive control

Bounding gait control of a parallel quadruped robot

Development of a Particle Filter-Based Path Tracking Algorithm of Autonomous Trucks with a Single Steering and Driving Module Using a Monocular Camera

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