Article
Construction & Building Technology
Hao Feng, Wei Ma, Chenbo Yin, Donghui Cao
Summary: This study introduces an improved PSO algorithm for optimizing PID controller coefficients, achieving higher trajectory tracking accuracy and faster convergence by incorporating nonlinear adaptive methods and elite mutation strategies.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Automation & Control Systems
Inayet Hakki Cizmeci, Adem Alpaslan Altun
Summary: Studies have shown that hybrid models are more effective, and this study introduces an improved algorithm called ESPID, which combines a PSO-based PID control system with the ESO algorithm. The experimental results demonstrate that ESPID outperforms other algorithms in multi-modal functions, providing faster and more accurate solutions. Furthermore, ESPID algorithm has also been successfully applied to a real-life production problem, achieving significant cost reduction.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Yinyan Zhang, Shuai Li, Bin Xu
Summary: This paper focuses on the theoretical analysis of the convergence of the Beetle Antennae Search (BAS) algorithm. It proves for the first time that the BAS algorithm converges with probability 1, providing insights on its effectiveness and potential improvements. Performance testing on benchmark functions and application examples demonstrate the advantages of the BAS algorithm over others.
Article
Engineering, Electrical & Electronic
Xinyu Zheng, Xiaoyu Su
Summary: This paper proposes a sliding mode controller based on the QPSO algorithm to address nonlinearity, external disturbances, and jitter in electro-hydraulic servo systems. By establishing state space equations and sliding surfaces, using the QPSO algorithm to optimize parameters, the controller's performance and adaptability are improved.
Article
Engineering, Chemical
Jinbin Bai, Min Tian, Jiangquan Li
Summary: A control system for variable-rate fertilization of liquid fertilizer based on beetle antennae search algorithm was proposed to solve the problems of low precision and uneven flow of field liquid fertilizer applicator. The system achieved high precision and uniform flow by optimizing the parameters of PID. The control effect of the system was validated through bench test.
Article
Computer Science, Interdisciplinary Applications
Ameer Tamoor Khan, Xinwei Cao, Shuai Li
Summary: This paper presents an optimization-based control framework for trajectory planning and stable control of multiple non-linear systems. By employing a hybrid controller (BAS and PID), an optimized approach for path planning and stable control of non-linear systems is proposed. The experimental results show that the method achieves promising results on different systems.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Automation & Control Systems
Hao Feng, Qianyu Song, Shoulei Ma, Wei Ma, Chenbo Yin, Donghui Cao, Hongfu Yu
Summary: An adaptive sliding mode control method based on RBF neural networks is proposed to improve the performance of a robotic excavator. The RBF neural networks are used to approximate and compensate for model uncertainties and load disturbances in the electro-hydraulic servo system. Adaptive mechanisms are designed to adjust the connection weights of the neural networks in real time for stability, and a nonlinear term is introduced into the sliding mode to improve dynamic performance. Experimental results show that the proposed controller outperforms traditional PID and SMC controllers in terms of tracking accuracy and disturbance rejection.
Article
Computer Science, Artificial Intelligence
Qian Qian, Yi Deng, Hui Sun, Jiawen Pan, Jibin Yin, Yong Feng, Yunfa Fu, Yingna Li
Summary: The Beetle Antennae Search algorithm is a simple and parameter-limited intelligent optimization algorithm. However, it has poor performance in complex optimization problems. In this study, the algorithm is improved by enhancing its usability, promoting optimization processes, and improving efficiency. The Enhanced Beetle Antennae Search algorithm (EBAS) outperformed BAS and even several state-of-the-art swarm-based algorithms in unbiased test functions. It also demonstrated applicability in a real-world optimization problem.
Article
Chemistry, Analytical
Yaoyu Shen, Ying-Qing Guo, Xiumei Zha, Yina Wang
Summary: This paper proposes a control algorithm for the electro-hydraulic servo displacement system in real-time hybrid testing, which uses the PSO algorithm to optimize the PID parameters and the feed-forward compensation algorithm for displacement compensation. The algorithm effectively improves the accuracy and response speed of the electro-hydraulic servo displacement system and solves the problems of time lag, large error, and slow response in real-time hybrid testing.
Article
Automation & Control Systems
De-Yi Zhang, Song-Yong Liu, Yi Chen, Cong-Cong Gu
Summary: This paper presents a control scheme for the electro-hydraulic servo system using a neural direct adaptive controller and a linear extended state observer. The rationality of the reduced-order model and the stability of the proposed controller are proven. Simulation results show that the controller has excellent position tracking performance.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Ameer Hamza Khan, Xinwei Cao, Bin Xu, Shuai Li
Summary: Deep Convolutional Neural Networks (CNNs) are state-of-the-art AI models for image classification, inspired by the human brain. This paper introduces an algorithm inspired by beetle behavior that can fool CNNs by perturbing a single pixel, more efficiently than other attacking algorithms. This raises concerns about the robustness and security of AI systems.
Article
Engineering, Electrical & Electronic
C. Naveen, B. Meenakshipriya, A. Tony Thomas, S. Sathiyavathi, S. Sathishbabu
Summary: This study proposes an iterative learning controller (ILC) for regulating the servo spool valve of an electro-hydraulic servo system (EHSS). Simulation and experimental results show that the ILC outperforms traditional PID controllers in step input tracking, but is inferior in sine wave tracking and disturbance rejection.
IETE JOURNAL OF RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Xiangyuan Jiang, Zongyuan Lin, Shuai Li, Yawen Ji, Yizhong Luan, Sile Ma
Summary: Wearable wireless body sensor networks (WWBSN) benefit the dynamic attitude configuration of human-like robots, while the Beetle Antennae Search (BAS) algorithm is employed for optimal path planning and attitude configuration. The proposed BASAO mechanism enhances efficiency and accuracy through experience-oriented and self-attenuate parts.
Article
Engineering, Multidisciplinary
Zhimin Mei, Xuexin Chi, Rui Chi
Summary: This paper proposes a new hybrid method called BRA for solving the problem of logistics distribution centers' location. By embedding the beetle antennae search algorithm into the rain algorithm, the BRA improves global search ability and search precision. Experimental results show that the BRA outperforms other classical heuristics, making it an effective and competitive algorithm.
Article
Mathematics
Tian Ji, Haoran Wei, Jun Wang, Shaoqing Tian, Yi Yao, Shukai Hu
Summary: This study improves the search capabilities and robustness of industrial robotic control systems by refining the beetle antennae optimization (BAO) algorithm. Compared to traditional PID control, beetle antennae search algorithm (BAS), and adaptive weighted particle swarm optimization (PSO), the enhanced BAO algorithm shows significant advantages in reducing errors, overshoot, and adjustment time, with a 60% improvement in optimization performance. This research provides valuable insights into the practical application of the refined BAO algorithm in industrial robotic control systems.
