CFHBA-PID Algorithm: Dual-Loop PID Balancing Robot Attitude Control Algorithm Based on Complementary Factor and Honey Badger Algorithm

Lin, Jianan; Zheng, Rongjia; Zhang, Yirong; Li, Wei; Luo, Kaiqing

doi:10.3390/s22124492

Cited by 13 publications

(4 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ITAE error criterion is selected as the fitness function of the improved optimization algorithm [32], and the standard form is as follows:…”

Section: Improvement Of Algorithmmentioning

confidence: 99%

Research on Synchronous Control of Active Disturbance Rejection Position of Multiple Hydraulic Cylinders of Digging-Anchor-Support Robot

Xiangxiang

et al. 2023

Sensors

View full text Add to dashboard Cite

In order to solve the problems of nonlinearity, uncertainty and coupling of multi-hydraulic cylinder group platform of a digging-anchor-support robot, as well as the lack of synchronization control accuracy of hydraulic synchronous motors, an improved Automatic Disturbance Rejection Controller-Improved Particle Swarm Optimization (ADRC-IPSO) position synchronization control method is proposed. The mathematical model of a multi-hydraulic cylinder group platform of a digging-anchor-support robot is established, the compression factor is used to replace the inertia weight, and the traditional Particle Swarm Optimization (PSO) algorithm is improved by using the genetic algorithm theory to improve the optimization range and convergence rate of the algorithm, and the parameters of the Active Disturbance Rejection Controller (ADRC) were adjusted online. The simulation results verify the effectiveness of the improved ADRC-IPSO control method. The experimental results show that, compared with the traditional ADRC, ADRC-PSO and PID controller, the improved ADRC-IPSO has better position tracking performance and shorter adjusting time, and its step signal synchronization error is controlled within 5.0 mm, and the adjusting time is less than 2.55 s, indicating that the designed controller has better synchronization control effect.

show abstract

“…ITAE error criterion is selected as the fitness function of the improved optimization algorithm [32], and the standard form is as follows:…”

Section: Improvement Of Algorithmmentioning

confidence: 99%

Research on Synchronous Control of Active Disturbance Rejection Position of Multiple Hydraulic Cylinders of Digging-Anchor-Support Robot

Xiangxiang

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Moreover, the SMC controller boasts a straightforward structure with a low computational burden and easy implementation [25]. In this research, instead of utilizing cascaded PID [26], the SMC controller will be employed to construct a cascaded dual-loop SMC controller.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Robust Flight Control of Logistic Unmanned Aerial Vehicles Using a Time-Delay Estimation Technique

Ma,

Yu,

et al. 2024

Drones

View full text Add to dashboard Cite

This paper proposes a cascaded dual closed-loop control strategy that incorporates time delay estimation and sliding mode control (SMC) to address the issue of uncertain disturbances in logistic unmanned aerial vehicles (UAVs) caused by ground effects, crosswind disturbances, and payloads. The control strategy comprises a position loop and an attitude loop. The position loop, which functions as the outer loop, employs a proportional–integral–derivative (PID) sliding mode surface to eliminate steady-state error through an integral component. Conversely, the attitude loop, serving as the inner loop, utilizes a fast nonsingular terminal sliding mode approach to achieve finite-time convergence and ensure a quick system response. The time-delay estimation technique is employed for the online estimation and real-time compensation of unknown disturbances, while SMC is used to enhance the robustness of the control system. The combination of time-delay estimation and SMC offers complementary advantages. The stability of the system is proven using Lyapunov theory. Hardware-in-the-loop simulation and flight tests demonstrate that the control law can achieve a smooth and continuous output. The proposed control strategy can be effectively applied in complex scenarios, such as hovering, crash recovery, and high maneuverability flying, with significant practicality in engineering applications.

show abstract

“…The most popular methods are proportional-integral-derivative (PID) [22]- [24] and linear quadratic regulator (LQR) schemes [25]. Nevertheless, a notable downside of the PID control algorithm for controlling the TWSBR is the difficulty of parameter tuning [26], [27]. Although there are many software tools available to aid the optimization of the PID parameters, the resulting control law may not be desirable for the TWSBR which can be easily driven to the instability region.…”

Section: Introductionmentioning

confidence: 99%

Self-balancing robot: modeling and comparative analysis between PID and linear quadratic regulator

Lau

Ahmad

Goh

2023

IJRES

View full text Add to dashboard Cite

<p>A two-wheeled self-balancing robot (TWSBR) is an underactuated system that is inherently nonlinear and unstable. While many control methods have been introduced to enhance the performance, there is no unique solution when it comes to hardware implementation as the robot’s stability is highly dependent on accuracy of sensors and robustness of the electronic control systems. In this study, a TWSBR that is controlled by an embedded NI myRIO-1900 board with LabVIEW-based control scheme is developed. We compare the performance between proportional-integral-derivative (PID) and linear quadratic regulator (LQR) schemes which are designed based on the TWSBR’s model that is constructed from Newtonian principles. A hybrid PID-LQR scheme is then proposed to compensate for the individual components’ limitations. Experimental results demonstrate the PID is more effective at regulating the tilt angle of the robot in the presence of external disturbances, but it necessitates a higher velocity to sustain its equilibrium. The LQR on the other hand outperforms PID in terms of maximum initial tilt angle. By combining both schemes, significant improvements can be observed, such as an increase in maximum initial tilt angle and a reduction in settling time.</p>

show abstract

CFHBA-PID Algorithm: Dual-Loop PID Balancing Robot Attitude Control Algorithm Based on Complementary Factor and Honey Badger Algorithm

Cited by 13 publications

References 28 publications

Research on Synchronous Control of Active Disturbance Rejection Position of Multiple Hydraulic Cylinders of Digging-Anchor-Support Robot

Research on Synchronous Control of Active Disturbance Rejection Position of Multiple Hydraulic Cylinders of Digging-Anchor-Support Robot

Finite-Time Robust Flight Control of Logistic Unmanned Aerial Vehicles Using a Time-Delay Estimation Technique

Self-balancing robot: modeling and comparative analysis between PID and linear quadratic regulator

Contact Info

Product

Resources

About