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Position control of nonlinear hydraulic system using an improved PSO based PID controller
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Items 101–199 of 199
Wang, J., Zhang, H., Hao, P., & Deng, H. (2023) · Processes · doi:10.3390/pr11071918 · Cited by 6
Autonomous Pick-and-Place Using Excavator Based on Deep Reinforcement Learning
Ishmatuka, C., Soesanti, I., & Ataka, A. (2023) · doi:10.1109/icitee59582.2023.10317662 · Cited by 6
“This paper [6] showed that the IPSO algorithm performs more effectively than the Phase-Margin and Standard Particle Swarm Optimization methods.”
MethodInvestigation on dynamic mathematical model and control method of flue gas heat exchange system
Ma, H., Xie, Y., Song, X., Liu, Y., Luo, X., & Wang, S. (2023) · Engineering Computations · doi:10.1108/ec-11-2021-0682 · Cited by 6
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Tang, J., Li, C., Zhou, J., Wei, W., & Wu, Z. (2025) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2025.112314 · Cited by 5
Self-citationWang, X., Wang, C., Liu, Z., Kang, Y., & Wang, Z. (2025) · International Communications in Heat and Mass Transfer · doi:10.1016/j.icheatmasstransfer.2025.108777 · Cited by 5
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“…improved particle swarm optimisation (PSO) with base proportional integral derivative (PID) in nonlinear hydraulic system position control systems [15], and intelligent algorithms like fuzzy logic [16], fuzzy logic and PID for robot movement [17], and adaptive neuro fuzzy for controlling the…”
BackgroundA Flatness-Based Nonlinear Control Scheme for Wire Tension Control of Hoisting Systems
Zang, W., Shen, G., Rui, G., Li, X., Li, G., & Tang, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2943915 · Cited by 5
“A conventional proportional-integral (PI) controller can no doubt coordinate two tensions of two wire ropes [6], [7].”
BackgroundSheng, W., Peng, G., Yang, N., Kang, Y.-W., & Söffker, D. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2020.106724 · Cited by 5
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A Kind of Electro-hydraulic Servo System Cooperative Control Simulation: An Experimental Research
Gao, B., Shen, W., Dai, Y., & Wang, W. (2022) · Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) · doi:10.2174/2352096515666220331143634 · Cited by 5
Huang, W., Pan, Z., Guo, C., Cheng, M., Jia, R., Chen, Z., Zhang, J., & Bing Hong, X. U. (2025) · Fusion Engineering and Design · doi:10.1016/j.fusengdes.2025.115204 · Cited by 4
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“Secondly, this model is solved by Optimization via Simulation method (OvS), Particle Swarm Optimization (PSO) and Simulated Annealing (SA).”
MethodVision-Based Excavator Control for Pick-and-Place Operation*
Ataka, A., Aji, M. H. B., Hakim, A. L., Arfiantino, D., Nanda, A. A., Nugraha, G. K., Setyadi, A. D., Aji, A., Ageng, G., Candra, R., et al. (2023) · doi:10.1109/icitee59582.2023.10317650 · Cited by 4
“Some of the works proposing an autonomous excavator used the PID (Proportional-Integral-Derivative) control combined with optimization technique such as Improved Generation Algorithm [4] and Particle Swarm Optimization [5].”
MethodTime-Optimal Path Planning for Dual-Welding Robots Based on Intelligent Optimization Strategy
Wang, X., Tang, B., Yan, Y., & Gu, X. (2017) · Transactions on intelligent welding manufacturing · doi:10.1007/978-981-10-7043-3_3 · Cited by 4
“The third category is local search PSO algorithm based on the global optimal particle [7], such as chaos particle swarm optimization (CPSO) algorithm.”
MethodCollaborative Tracking Control Strategy for Autonomous Excavation of a Hydraulic Excavator
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“Liu et al. (2023) and Fang et al. (2011) employed PSO for PID tuning; Ye et al. (2017) and Zhang et al. (2024b) utilized it for path planning; Meng et al. (2022) and Liu et al. (2024) applied it to parameter optimization; and Zhang et al. (2025) and Bo et al. (2024) used it for scenario prediction.”
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“E R r i L dt dt K dx dt c p c c b ( ) , (2)”
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“In order to compensate for the non-linearity, existent studies have proposed various position control methods including neural networks [3, 4], PID with optimization [5, 6], nonlinear PI controllers [7], fuzzy logic [8], etc.”
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“The particle Swarm Optimization PSO algorithm is implemented in [3] to find the optimal values of the PID controller for nonlinear hydraulic systems.”
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“Note that the nonlinearity of the system is due to the flow equations (6-10).”
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“In this regard, the improved Self-Turbulent Flow (STF) controller for hydraulic system state estimation based on the EHS mathematical model is an effective solution for LOSP acquisition and monitoring [23,24].”
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“Among the evolutionary computation techniques, the PSO algorithm is popularly applied to tune the PID controller [24].”
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“The hydraulic system offers robust power support, precise control, and excellent adaptability during lateral posture adjustments, making operations in complex terrains more efficient and reliable [31, 32].”
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“Ye et al. [17] applied the IPSO algorithm for self-tuning position PID parameters in the stick system of an excavator.”
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“Transfer function of valve controlled hydraulic cylinder’s hydraulic system [11] can generally be expressed as”
BackgroundDesign of Variable Pump Displacement Controller Based on FLSMC Method
Xue, D., Chao, Z., Liu, X., Li, H., Han, S., Liu, X., Jin, Y., Ning, C., & Tan, Y. (2021) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001421580088 · Cited by 1
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Investigation of Electrohydraulic Control of A Gas Turbine Engine’s Inlet Guide Vanes
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“Introduction Electrohydraulic control valves are widely used in many of hydraulic position control applications [1-6].”
BackgroundDesigning a New Artificial Lift Method Using Computational Simulation and Evolutionary Optimization
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“Improved particle swarm optimization (PSO) algorithm was used to find the optimal PID controller gain o f a nonlinear hydraulic system [11].”
MethodDeveloping low-cost two wheels balancing scooter using proportional derivative controller
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“Studies consistently show that PSO outperforms GA in both simulation and practical applications across various systems [7].”
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“A large inertia weight w [23] is set in the early stage to enhance global exploration, and is gradually reduced in later iterations to strengthen local exploitation, while a small .”
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“Ye [11] proposed PID position control optimized by the improved particle swarm optimization algorithm for excavator valve-controlled hydraulic circuits.”
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Liu, Y.-X., Wang, J.-X., Qin, R.-J., Zhong-kai, R. E. N., Yang, J., & He, D.-P. (2026) · Journal of Iron and Steel Research International · doi:10.1007/s42243-026-01841-0
Jia, B., Zhao, J., Zhao, Z., Wang, Z., Zeng, Q., & Li, H. (2026) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2026.3701788
“Classical linear strategies, particularly proportional–integral–derivative (PID) control and its variants (e.g., gain-scheduling, fuzzy-PID), remain industry standards due to their ease of implementation [5], [6], [7], [8].”
Qiao, Y., Wu, J., Ming, Q., Zhang, H., Wang, F., & Bing Hong, X. U. (2026) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070261462201
PID-MFAILC Hybrid Speed Regulation for the Rotary Mechanism of Hydraulic Bolt Drills
Zong, L., Liang, J., Bu, X., & Zhang, Y. (2026) · IEEE Data Driven Control and Learning Systems Conference (DDCLS) · doi:10.1109/ddcls71227.2026.11610273
Du, H., Kong, W., Xu, J., Shi, J., Wei, L., & Xu, Q. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7302180
Robustness Improvement of an Electro-Hydraulic Servo System Using a Switching Fuzzy-PID Controller
Shiyi, W., Peng, X., Yujie, G., Kecheng, L., & Wei, M. (2026) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma69663.2026.11647598
“To address these issues, various advanced control methodologies have been extensively researched and integrated into electro-hydraulic technology [5].”
Position tracking control of a pressure-compensated electro-hydrostatic actuation system
Kumar, G., & Mandal, N. P. (2026) · Sadhana · doi:10.1007/s12046-026-03199-1
“Because of their low maintenance costs, high performance, and ease of use, PID controllers remain the industry standard for position control applications [43].”
Genetic Algorithm Optimized PID with Kalman Filtering for Electro-Hydraulic Servo Systems
Thang, N. H., Chuong, V. L., & Vu, T. N. L. (2026) · International Conference on Green Technology and Sustainable Development (GTSD) · doi:10.1109/gtsd70918.2026.11722424
“Methods based on PSO [8] are also popular.”
Sliding Mode Control of Electro‐Hydraulic Servo System Based on Time Delay Observer
Kim, J., Jo, H., Kim, Y., Oh, C., Kim, U., & Ri, C. S. D. R. D. (2026) · Engineering Reports · doi:10.1002/eng2.71114
Weiwei, L., Han, H., Chuiyi, L., & Jiang, Y. (2026) · Actuators · doi:10.3390/act15110564
Metadata
- Authors
- Ye, Y., Yin, C.-B., Gong, Y., & Zhou, J.-J.
- Affiliations
- Nanjing Tech University (CN)
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 83
- Pages
- 241-259
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W2462241752
- Cited by
- 199
- References
- 61
- Citations by year
- 2026: 16 · 2025: 19 · 2024: 25 · 2023: 21 · 2022: 28 · 2021: 19 · 2020: 17 · 2019: 21 · 2018: 22 · 2017: 10
- FWCI
- 16.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Mechanical Systems and Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Hydraulic and Pneumatic Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Design
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Keywords
- position control, hydraulic excavator, valve-controlled cylinder, improved particle swarm optimization, PID controller tuning, dead zone, saturation, discharge coefficient, friction, co-simulation
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