Adaptive model reference control method for real-time hybrid simulation. (1st October 2019)
- Record Type:
- Journal Article
- Title:
- Adaptive model reference control method for real-time hybrid simulation. (1st October 2019)
- Main Title:
- Adaptive model reference control method for real-time hybrid simulation
- Authors:
- Najafi, Amirali
Spencer, Billie F. - Abstract:
- Highlights: Real-time hybrid simulation (RTHS) is an alternative to shake table testing. Stability of RTHS loop is dependent on appropriate compensation of actuator dynamics. An adaptive model reference controller (aMRC) is presented for RTHS applications. The aMRC enhances actuator tracking even in the presence of modeling uncertainties. RTHS and reference structure performances match closely because of the aMRC. Abstract: The real-time hybrid simulation (RTHS) methodology is an experimental technique involving substructuring of a full-scale experiment into numerical and experimental partitions. It offers a cost-effective solution and is highly practical in confined laboratory settings. Successful implementation of RTHS is dependent on successful tracking control and robustness of the hybrid simulation loop. This paper addresses the benchmark problem in RTHS, which intends to assess available actuator tracking controllers and other advanced computational frameworks for successful RTHS implementation. Most existing control algorithms tend to instability when faced with challenges of plant uncertainty and nonlinearity. Stability has been at odds with excellent tracking, where controllers with rigorous tracking have had poor stability performance and robust controllers have had poor tracking performance. This paper introduces an Adaptive Model Reference Control (aMRC) method for displacement tracking of actuators, which offers an excellent tracking ability and maintainsHighlights: Real-time hybrid simulation (RTHS) is an alternative to shake table testing. Stability of RTHS loop is dependent on appropriate compensation of actuator dynamics. An adaptive model reference controller (aMRC) is presented for RTHS applications. The aMRC enhances actuator tracking even in the presence of modeling uncertainties. RTHS and reference structure performances match closely because of the aMRC. Abstract: The real-time hybrid simulation (RTHS) methodology is an experimental technique involving substructuring of a full-scale experiment into numerical and experimental partitions. It offers a cost-effective solution and is highly practical in confined laboratory settings. Successful implementation of RTHS is dependent on successful tracking control and robustness of the hybrid simulation loop. This paper addresses the benchmark problem in RTHS, which intends to assess available actuator tracking controllers and other advanced computational frameworks for successful RTHS implementation. Most existing control algorithms tend to instability when faced with challenges of plant uncertainty and nonlinearity. Stability has been at odds with excellent tracking, where controllers with rigorous tracking have had poor stability performance and robust controllers have had poor tracking performance. This paper introduces an Adaptive Model Reference Control (aMRC) method for displacement tracking of actuators, which offers an excellent tracking ability and maintains robustness under unmodeled dynamics and uncertainties. The proposed controller is composed of feedforward and feedback links, a reference model, and an adaptation law. The tracking and robustness performance of the proposed algorithm are evaluated through a numerical RTHS of the three-story steel frame building described in the benchmark problem statement. The benchmark problem defines different mass and damping configurations while partitioning the structure. Additionally, the experimental substructure is made uncertain by modeling several actuator and stiffness parameters probabilistically, per the benchmark problem. The performance of the proposed controller is compared to several commonly employed control techniques and assessed using the evaluation criteria described in the benchmark problem statement. The results show that the proposed aMRC algorithm tracks the desired reference signal well while maintaining robustness. … (more)
- Is Part Of:
- Mechanical systems and signal processing. Volume 132(2019)
- Journal:
- Mechanical systems and signal processing
- Issue:
- Volume 132(2019)
- Issue Display:
- Volume 132, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 132
- Issue:
- 2019
- Issue Sort Value:
- 2019-0132-2019-0000
- Page Start:
- 183
- Page End:
- 193
- Publication Date:
- 2019-10-01
- Subjects:
- Actuator -- Robust -- Adaptive -- Control -- Real-time -- Hybrid simulation
Structural dynamics -- Periodicals
Vibration -- Periodicals
Constructions -- Dynamique -- Périodiques
Vibration -- Périodiques
Structural dynamics
Vibration
Periodicals
621 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08883270 ↗
http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0888-3270;screen=info;ECOIP ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ymssp.2019.06.023 ↗
- Languages:
- English
- ISSNs:
- 0888-3270
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5419.760000
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