Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization
This research work is focused on the nonlinear modeling and control of a hydrostatic thrust bearing. In the proposed work, a mathematical model is formulated for a hydrostatic thrust bearing system that includes the effects of uncertainties, unmodelled dynamics, and nonlinearities. Depending on the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/8/903 |
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| author | Waheed Ur Rehman Wakeel Khan Nasim Ullah M. D. Shahariar Chowdhury Kuaanan Techato Muhammad Haneef |
| author_facet | Waheed Ur Rehman Wakeel Khan Nasim Ullah M. D. Shahariar Chowdhury Kuaanan Techato Muhammad Haneef |
| author_sort | Waheed Ur Rehman |
| collection | DOAJ |
| description | This research work is focused on the nonlinear modeling and control of a hydrostatic thrust bearing. In the proposed work, a mathematical model is formulated for a hydrostatic thrust bearing system that includes the effects of uncertainties, unmodelled dynamics, and nonlinearities. Depending on the type of inputs, the mathematical model is divided into three subsystems. Each subsystem has the same output, i.e., fluid film thickness with different types of input, i.e., viscosity, supply pressure, and recess pressure. An extended state observer is proposed to estimate the unavailable states. A backstepping control technique is presented to achieve the desired tracking performance and stabilize the closed-loop dynamics. The proposed control technique is based on the Lyapunov stability theorem. Moreover, particle swarm optimization is used to search for the best tuning parameters for the backstepping controller and extended state observer. The effectiveness of the proposed method is verified using numerical simulations. |
| first_indexed | 2024-03-10T12:12:17Z |
| format | Article |
| id | doaj.art-293a1411c8f44ddaba8836c8082c91d9 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T12:12:17Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-293a1411c8f44ddaba8836c8082c91d92023-11-21T16:08:27ZengMDPI AGMathematics2227-73902021-04-019890310.3390/math9080903Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable OptimizationWaheed Ur Rehman0Wakeel Khan1Nasim Ullah2M. D. Shahariar Chowdhury3Kuaanan Techato4Muhammad Haneef5College of Mechanical Engineering and Applied Electronics Technologies, Beijing University Technology, Beijing 100124, ChinaDepartment of Electrical Engineering, Foundation University Islamabad, Islamabad 44000, PakistanDepartment of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaFaculty of Environmental Management, Prince of Songkla University, Hat Yai 90110, ThailandFaculty of Environmental Management, Prince of Songkla University, Hat Yai 90110, ThailandDepartment of Electrical Engineering, Foundation University Islamabad, Islamabad 44000, PakistanThis research work is focused on the nonlinear modeling and control of a hydrostatic thrust bearing. In the proposed work, a mathematical model is formulated for a hydrostatic thrust bearing system that includes the effects of uncertainties, unmodelled dynamics, and nonlinearities. Depending on the type of inputs, the mathematical model is divided into three subsystems. Each subsystem has the same output, i.e., fluid film thickness with different types of input, i.e., viscosity, supply pressure, and recess pressure. An extended state observer is proposed to estimate the unavailable states. A backstepping control technique is presented to achieve the desired tracking performance and stabilize the closed-loop dynamics. The proposed control technique is based on the Lyapunov stability theorem. Moreover, particle swarm optimization is used to search for the best tuning parameters for the backstepping controller and extended state observer. The effectiveness of the proposed method is verified using numerical simulations.https://www.mdpi.com/2227-7390/9/8/903multivariable optimizationnumerical modelinghydrostatic thrust bearingmembrane restrictorservo control systemsbackstepping control |
| spellingShingle | Waheed Ur Rehman Wakeel Khan Nasim Ullah M. D. Shahariar Chowdhury Kuaanan Techato Muhammad Haneef Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization Mathematics multivariable optimization numerical modeling hydrostatic thrust bearing membrane restrictor servo control systems backstepping control |
| title | Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization |
| title_full | Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization |
| title_fullStr | Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization |
| title_full_unstemmed | Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization |
| title_short | Nonlinear Control of Hydrostatic Thrust Bearing Using Multivariable Optimization |
| title_sort | nonlinear control of hydrostatic thrust bearing using multivariable optimization |
| topic | multivariable optimization numerical modeling hydrostatic thrust bearing membrane restrictor servo control systems backstepping control |
| url | https://www.mdpi.com/2227-7390/9/8/903 |
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