Tabela A z publikacjami w czasopismach wyróżnionych w Journal Citation Reports (JCR) 
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Afiliacja IPPT PAN

1.Pisarski D., Konowrocki R., Jankowski Ł., Scalable distributed optimal control of vibrating modular structures, STRUCTURAL CONTROL AND HEALTH MONITORING, ISSN: 1545-2255, DOI: 10.1002/stc.2502, pp.1-21, 2020
Pisarski D., Konowrocki R., Jankowski Ł., Scalable distributed optimal control of vibrating modular structures, STRUCTURAL CONTROL AND HEALTH MONITORING, ISSN: 1545-2255, DOI: 10.1002/stc.2502, pp.1-21, 2020

Abstract:
A scalable optimal control method for structural vibration mitigation is studied. The method relies on a structure's partitioning that leads to a set of dynamically interconnected subsystems. Each subsystem is operated with an individual subcontroller that collects the local state information and collaborates with the neighboring subcontrollers to estimate a short time prediction of the interconnecting forces defining the subsystem's boundary conditions. Using the extended model that represents the subsystem's dynamics together with the evolution of its boundary conditions, each subcontroller computes the control decision based on the solution to a finite‐time horizon optimal control problem. In order to cope with the changes in the boundary conditions, the optimal solution is computed repetitively according to the receding horizon scheme. The method is validated numerically for a cantilever structure equipped with actively controlled electromagnetic actuators and subjected to a variety of initial condition scenarios. The performance of the designed controller is tested by comparisons to the centralized and isolated decentralized controllers. The introduced system partitioning and distributed controller allow performing parallel computing which makes the method fully scalable and applicable to large‐scale structures. The computational complexity of the designed distributed control is studied for different settings in the modeling of the subsystem's boundary conditions.

Keywords:
active control, distributed control, modular structure, scalable optimization, stabilization

(140p.)
2.Zhang Q., Hou J., Jankowski Ł., Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses, SENSORS, ISSN: 1424-8220, DOI: 10.3390/s20020394, Vol.20, No.2, pp.394-1-394-23, 2020
Zhang Q., Hou J., Jankowski Ł., Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses, SENSORS, ISSN: 1424-8220, DOI: 10.3390/s20020394, Vol.20, No.2, pp.394-1-394-23, 2020

Abstract:
Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.

Keywords:
structural health monitoring, damage identification, vehicle bump, additional virtual mass, bridge

(100p.)