Nonlinear intelligent control systems subjected to earthquakes by fuzzy tracking theory

Timothy Chen,Y.M. Meng,Z.Y. Chen,Ruei-Yuan Wang 국제구조공학회 2024 Smart Structures and Systems, An International Jou Vol.33 No.4

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.

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.

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

Z.Y. Chen,Ruei-Yuan Wang,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.

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.

LDI NN auxiliary modeling and control design for nonlinear systems

Z.Y. Chen,Ruei-Yuan Wang,Rong Jiang,Timothy Chen 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.5

This study investigates an effective approach to stabilize nonlinear systems. To ensure the asymptotic nonlinear stability in nonlinear discrete-time systems, the present study presents controller for an EBA (Evolved Bat Algorithm) NN (fuzzy neural network) in the algorithm. In fuzzy evolved NN modeling, the auxiliary circuit with high frequency LDI (linear differential inclusions) and NN model representation is developed for the nonlinear arbitrary dynamics. An example is utilized to demonstrate the system more robust compared with traditional control systems.

Grey algorithmic control and identification for dynamic coupling composite structures

Z.Y. Chen,Ruei-Yuan Wang,Yahui Meng,Timothy Chen 국제구조공학회 2023 Steel and Composite Structures, An International J Vol.49 No.4

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

GWO-based fuzzy modeling for nonlinear composite systems

Z.Y. Chen,Yahui Meng,Ruei-Yuan Wang,Timothy Chen 국제구조공학회 2023 Steel and Composite Structures, An International J Vol.47 No.4

The goal of this work is to create a new and improved GWO (Grey Wolf Optimizer), the so-called Robot GWO (RGWO), for dynamic and static target tracking involving multiple robots in unknown environmental conditions. From applying ourselves with the Gray Wolf Optimization Algorithm (GWO) and how it works, as the name suggests, it is a nature-inspired metaheuristic based on the behavior of wolf packs. Like other nature-inspired metaheuristics such as genetic algorithms and firefly algorithms, we explore the search space to find the optimal solution. The results also show that the improved optimal control method can provide superior power characteristics even when operating conditions and design parameters are changed.

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.

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.

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.