Dynamic intelligent control of composite buildings by using M-TMD and evolutionary algorithm

Yahui Meng,Z.Y. Chen,Ruei-Yuan Wang,Sheng-Hsiang Peng,Yaoke Yang,Timothy Chen 국제구조공학회 2022 Steel and Composite Structures, An International J Vol.42 No.5

The article deals with the possibilities of vibration stimulation. Based on the stability analysis, a multi-scale approach with a modified whole-building model is implemented. The motion equation is configured for a controlled bridge with a MDOF (multiple dynamic degrees of freedom) Tuned Mass Damper (M-TMD) system, and a combination of welding, excitation, and control effects is used with its advanced packages and commercial software submodel. Because the design of high-performance and efficient structural systems has been of interest to practical engineers, systematic methods of structural and functional synthesis of control systems must be used in many applications. The smart method can be stabilized by properly controlling the high frequency injection limits. The simulation results illustrate that the multiple modeling method used is consistent with the accuracy and high computational efficiency. The M-TMD system, even with moderate reductions in critical pressure, can significantly suppress overall feedback on an unregulated design.

Intelligent algorithm and optimum design of fuzzy theory for structural control

Ruei-Yuan Wang,Yahui Meng,Timothy Chen,Z.Y. Chen 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.5

The optimal design of structural composite materials is a research topic that attracts the attention of lots researchers. For many more thirty years, there has been increasing interest in the applications in all kinds of topics, which means taking advantage of fuzzy set theory, fuzzy analysis, and fuzzy control for designing high-performance and efficient structural systems is a fundamental concern for engineers, and many applications require the use of a systems approach to combine structural and active control systems. Therefore, an intelligent method can be designed based on the mitigation method, and by establishing the stable of the closed-loop fuzzy mitigation system, the behavior of the closed-loop fuzzy mitigation system can be accurately predicted. In this article, the intelligent algorithm and optimum design of fuzzy theory for structural control has been provided and demonstrated effective and efficient in practical engineering issues.

Fuzzy neural network controller of interconnected method for civil structures

Chen, Z.Y.,Meng, Yahui,Wang, Ruei-yuan,Chen, Timothy Techno-Press 2022 Advances in concrete construction Vol.13 No.5

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

Smart structural control and analysis for earthquake excited building with evolutionary design

Z.Y. Chen,Ruei-yuan Wang,Yahui Meng,Qiuli Fu,Timothy Chen 국제구조공학회 2021 Structural Engineering and Mechanics, An Int'l Jou Vol.79 No.2

In recent years, with the maximization of control design and efficiency, and the improvement of economy and energy efficiency, building technology and control in the theory have attracted the attention of lots researchers. By trying various control theorems, many numerical methods have been investigated in the literature to achieve this target, but all these numerical methods are difficult to work out the problem correctly. This paper puts forward a potentially feasible evolutionary bat algorithm (EB) method for active control of earthquake-induced vibration in building structures. Based disturbance observer based control and S surface combined with the robust adaptive control scheme for solving optimization problems proposed, an important contribution in the control law is what the configuration control in the present study should not require known uncertainty limits and the disturbance is eliminated. A simulation case study was proposed to illustrate the possibility of implementing an apparent learning method in ANN to effectively control structural vibration under the influence of systematic motion under earthquake citations. The proposed learning numerical methods does not need to develop a mathematical model of structural dynamics or train another neural network to approximate the actual structural response to be performed.

Composite components damage tracking and dynamic structural behaviour with AI algorithm

Z.Y. Chen,Sheng-Hsiang Peng,Yahui Meng,Ruei-Yuan Wang,Qiuli Fu,Timothy Chen 국제구조공학회 2022 Steel and Composite Structures, An International J Vol.42 No.2

This study discusses a hypothetical method for tracking the propagation damage of Carbon Reinforced Fiber Plastic (CRFP) components underneath vibration fatigue. The High Cycle Fatigue (HCF) behavior of composite materials was generally not as severe as this of admixture alloys. Each fissure initiation in metal alloys may quickly lead to the opposite. The HCF behavior of composite materials is usually an extended state of continuous degradation between resin and fibers. The increase is that any layer-to-layer contact conditions during delamination opening will cause a dynamic complex response, which may be non-linear and dependent on temperature. Usually resulted from major deformations, it could be properly surveyed by a non-contact investigation system. Here, this article discusses the scanning laser application of that vibrometer to track the propagation damage of CRFP components underneath fatigue vibration loading. Thus, the study purpose is to demonstrate that the investigation method can implement systematically a series of hypothetical means and dynamic characteristics. The application of the relaxation method based on numerical simulation in the Artificial Intelligence (AI) Evolved Bat (EB) strategy to reduce the dynamic response is proved by numerical simulation. Thermal imaging cameras are also measurement parts of the chain and provide information in qualitative about the temperature location of the evolution and hot spots of damage.

Smart modified repetitive-control design for nonlinear structure with tuned mass damper

Z.Y. Chen,Ruei-Yuan Wang,Yahui Meng,Timothy Chen 국제구조공학회 2023 Steel and Composite Structures, An International J Vol.46 No.1

A new intelligent adaptive control scheme was proposed that combines observer disturbance-based adaptive control and fuzzy adaptive control for a composite structure with a mass-adjustable damper. The most important advantage is that the control structures do not need to know the uncertainty limits and the interference effect is eliminated. Three adjustable parameters in LMI are used to control the gain of the 2D fuzzy control. Binary performance indices with weighted matrices are constructed to separately evaluate validation and training performance using the revalidation learning function. Determining the appropriate weight matrix balances control and learning efficiency and prevents large gains in control. It is proved that the stability of the control system can be ensured by a linear matrix theory of equality based on Lyapunov's theory. Simulation results show that the multilevel simulation approach combines accuracy with high computational efficiency. The M-TMD system, by slightly reducing critical joint load amplitudes, can significantly improve the overall response of an uncontrolled structure.

A novel smart criterion of grey-prediction control for practical applications

Ruei-Yuan Wang,Z.Y. Chen,Yahui Meng,Timothy Chen 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.1

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

Stochastic intelligent GA controller design for active TMD shear building

Z.Y. Chen,Sheng-Hsiang Peng,Ruei-Yuan Wang,Yahui Meng,Qiuli Fu,Timothy Chen 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.81 No.1

The problem of optimal stochastic GA control of the system with uncertain parameters and unsure noise covariates is studied. First, without knowing the explicit form of the dynamic system, the open-loop determinism problem with path optimization is solved. Next, Gaussian linear quadratic controllers (LQG) are designed for linear systems that depend on the nominal path. A robust genetic neural network (NN) fuzzy controller is synthesized, which consists of a Kalman filter and an optimal controller to assure the asymptotic stability of the discrete control system. A simulation is performed to prove the suitability and performance of the recommended algorithm. The results indicated that the recommended method is a feasible method to improve the performance of active tuned mass damper (ATMD) shear buildings under random earthquake disturbances.