Motion control of robot based on a new integral separated PID

Meng, Xiangzhong; Kou, Lei; Yuan, Qiangqiang; Pi, Yiming; Ke, Wende

doi:10.1504/ijwmc.2016.081160

Cited by 4 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conventional Proportional-Integral-Derivative (PID) control and the improved control algorithms based on the PID, for example, the fuzzy PID, were proposed for the path tracking control of the mobile robots. 9,10 The active disturbance rejection control was developed to estimate and compensate for the effect of slip to improve the path tracking performance of the autonomous ground vehicles and robots. 11 The experiments, which compare the model predictive control with the conventional Proportional Derivative (PD) control, were carried out for the path tracking of the mobile robot.…”

Section: Path Tracking Methods For Mobile Robotsmentioning

confidence: 99%

Linear Quadratic Regulator Method in Vision-Based Laser Beam Tracking for a Mobile Target Robot

Ling¹,

Wu²,

Zhou³

et al. 2020

Robotica

View full text Add to dashboard Cite

SUMMARY This paper proposes a novel laser beam tracking mechanism for a mobile target robot that is used in shooting ranges. Compared with other traditional tracking mechanisms and modules, the proposed laser beam tracking mechanism is more flexible and low cost in use. The mechanical design and the working principle of the tracking module are illustrated, and the complete control system of the mobile target robot is introduced in detail. The tracking control includes two main steps: localizing the mobile target robot with regards to the position of the laser beam and tracking the laser beam by the linear quadratic regulator (LQR). First of all, the state function of the control system is built for this tracking system; second, the control law is deduced according to the discretized state function; lastly, the stability of the control method is proved by the Lyapunov theory. The experimental results demonstrate that the Hue, Saturation, Value feature-extracting method is robust and is qualified to be used for localization in the laser beam tracking control. It is verified through experiments that the LQR method is of better performance than the conventional Proportional Derivative control in the aspect of converge time, lateral error control, and distance error control.

show abstract

Section: Path Tracking Methods For Mobile Robotsmentioning

confidence: 99%

Linear Quadratic Regulator Method in Vision-Based Laser Beam Tracking for a Mobile Target Robot

Ling¹,

Wu²,

Zhou³

et al. 2020

Robotica

View full text Add to dashboard Cite

show abstract

“…The network's regression performance is evaluated by utilizing the testing set after reducing the training error onto convergence. The parameter regression formula based on the fully connected neural network is demonstrated in Equation (20).…”

Section: Hidden Layersmentioning

confidence: 99%

“…Although this method is easy to implement, its anti-interference ability is poor and affects control outcomes adversely. To address this problem, this paper proposes using the integral-separated PID approach to realize actual acceleration tracking of desired acceleration [ 20 ]. This method avoids system overshoot and oscillation problems, thus enhancing the response speed and accuracy of the actuator layer.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Cruise System Based on Fuzzy MPC and Machine Learning State Observer

Guo

Wang

Liang

et al. 2023

Sensors

View full text Add to dashboard Cite

Under the trend of vehicle intelligentization, many electrical control functions and control methods have been proposed to improve vehicle comfort and safety, among which the Adaptive Cruise Control (ACC) system is a typical example. However, the tracking performance, comfort and control robustness of the ACC system need more attention under uncertain environments and changing motion states. Therefore, this paper proposes a hierarchical control strategy, including a dynamic normal wheel load observer, a Fuzzy Model Predictive Controller and an integral-separate PID executive layer controller. Firstly, a deep learning-based dynamic normal wheel load observer is added to the perception layer of the conventional ACC system and the observer output is used as a prerequisite for brake torque allocation. Secondly, a Fuzzy Model Predictive Control (fuzzy-MPC) method is adopted in the ACC system controller design, which establishes performance indicators, including tracking performance and comfort, as objective functions, dynamically adjusts their weights and determines constraint conditions based on safety indicators to adapt to continuously changing driving scenarios. Finally, the executive controller adopts the integral-separate PID method to follow the vehicle’s longitudinal motion commands, thus improving the system’s response speed and execution accuracy. A rule-based ABS control method was also developed to further improve the driving safety of vehicles under different road conditions. The proposed strategy has been simulated and validated in different typical driving scenarios and the results show that the proposed method provides better tracking accuracy and stability than traditional techniques.

show abstract

Sliding Mode Control Based on Dynamic Model for Transport Vehicle

Xiu

Wang

2018

IEEE Access

View full text Add to dashboard Cite

Motion control of robot based on a new integral separated PID

Cited by 4 publications

References 5 publications

Linear Quadratic Regulator Method in Vision-Based Laser Beam Tracking for a Mobile Target Robot

Linear Quadratic Regulator Method in Vision-Based Laser Beam Tracking for a Mobile Target Robot

Adaptive Cruise System Based on Fuzzy MPC and Machine Learning State Observer

Sliding Mode Control Based on Dynamic Model for Transport Vehicle

Contact Info

Product

Resources

About