Genetic Algorithm Based Optimum Semi-Active Control of Building Frames Using Limited Number of Magneto-Rheological Dampers and Sensors

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Vishisht Bhaiya ◽  
S. D. Bharti ◽  
M. K. Shrimali ◽  
T. K. Datta
Keyword(s):  
Genetic Algorithm ◽  
Active Control ◽  
Optimization Problem ◽  
Numerical Study ◽  
Accurate Estimation ◽  
Computationally Efficient ◽  
Linear Quadratic ◽  
Building Frames ◽  
Mr Dampers ◽  
Magneto Rheological

Optimum semi-active control with a limited number of magneto-rheological (MR) dampers and measurement sensors has certain requirements. Most important of them is the accurate estimation of control forces developed in the MR dampers from the observations made in the structure. Therefore, the observation strategy should form an integral part of the optimization problem. The existing literature on the subject does not address this issue properly. The paper presents a computationally efficient optimization scheme for semi-active control of partially observed building frames using a limited number of MR dampers and sensors for earthquakes. The control scheme duly incorporates the locations of measurement sensors as variables into the genetic algorithm (GA) based optimization problem. A ten-storied building frame is taken as an illustrative example. The optimum control strategy utilizes two well-known control laws, namely, the linear quadratic Gaussian (LQG) with clipped optimal control and the bang-bang control to find the time histories of voltage to be applied to the MR dampers. The results of the numerical study show that the proposed scheme of sensor placement provides the optimum reduction of response with more computational efficiency. Second, optimal locations of sensors vary with the response quantities to be controlled, the nature of earthquake, and the control algorithm. Third, optimal locations of MR dampers are invariant of the response quantities to be controlled and the nature of earthquake.

A genetic algorithm–based design approach for smart base isolation systems

2017 ◽  
Vol 29 (7) ◽  
pp. 1315-1332 ◽  
Author(s):  
Mohtasham Mohebbi ◽  
Hamed Dadkhah ◽  
Hamed Rasouli Dabbagh
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Base Isolation ◽  
Design Procedure ◽  
Design Parameters ◽  
Linear Quadratic ◽  
Isolation System ◽  
Isolation Systems ◽  
Magneto Rheological ◽  
Smart Base Isolation

This article presents a new approach for designing effective smart base isolation systems composed of a low-damping linear base isolation and a semi-active magneto-rheological damper. The method is based on transforming the design procedure of the hybrid base isolation system into a constrained optimization problem. The magneto-rheological damper command voltages have been determined using H2/linear quadratic Gaussian and clipped-optimal control algorithms. Through a sensitivity analysis to identify the effective design parameters, base isolation and control algorithm parameters have been taken as design variables and optimally determined using genetic algorithm. To restrict increases in floor accelerations, the objective function of the optimization problem has been defined as minimizing the maximum base drift while putting specific constraint on the acceleration response. For illustration, the proposed method has been applied to design a semi-active hybrid isolation system for a four-story shear building under earthquake excitation. The results of numerical simulations show the effectiveness, simplicity, and capability of the proposed method. Furthermore, it has been shown that using the proposed method, the acceleration of the isolated structure can also be incorporated into design process and practically controlled with a slight sacrifice of control effectiveness in reducing the base drift.

scholarly journals Numerical Study on Nonlinear Semiactive Control of Steel-Concrete Hybrid Structures Using MR Dampers

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Long-He Xu ◽  
Zhong-Xian Li ◽  
Yang Lv
Keyword(s):  
Active Control ◽  
Numerical Study ◽  
Material Model ◽  
Relative Displacement ◽  
Hybrid Structure ◽  
Semiactive Control ◽  
Building Structures ◽  
Seismic Safety ◽  
Analysis And Design ◽  
Mr Dampers

Controlling the damage process, avoiding the global collapse, and increasing the seismic safety of the super high-rise building structures are of great significance to the casualties’ reduction and seismic losses mitigation. In this paper, a semiactive control platform based on magnetorheological (MR) dampers comprising the Bouc-Wen model, the semi-active control law, and the shear wall damage criteria and steel damage material model is developed in LS-DYNA program, based on the data transferring between the main program and the control platform; it can realize the purpose of integrated modeling, analysis, and design of the nonlinear semi-active control system. The nonlinear seismic control effectiveness is verified by the numerical example of a 15-story steel-concrete hybrid structure; the results indicate that the control platform and the numerical method are stable and fast, the relative displacement, shear force, and damage of the steel-concrete structure are largely reduced using the optimal designed MR dampers, and the deformations and shear forces of the concrete tube and frame are better consorted by the control devices.

New genetic algorithm for structural active control by considering the effect of time delay

2020 ◽  
pp. 107754632093346
Author(s):  
Ali Banaei ◽  
Javad Alamatian
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Active Control ◽  
Control Method ◽  
Control Process ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
The Common ◽  
New Generation ◽  
Active Control Method

This study focuses on a new active control method by improving specification of a well-known intelligent numerical search method, that is the genetic algorithm. The proposed scheme modifies the specifications of the common genetic algorithm by using two strategies. First, a new constrained objective function is proposed. Then, a procedure is designed for evaluating and reducing time delay in control process. These procedures lead to a new generation of the genetic algorithm, which is more reliable. For verifying the efficiency of the proposed method, vibrations of several structures are controlled, and results are compared with other well-known methods such as the common genetic algorithm, linear quadratic regulator, and equivalent critical damping. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with other methods.

An Optimization Framework for The Design of Cable Harness Layouts in Planar Interconnected Systems

2021 ◽  
pp. 1-29
Author(s):  
Nafiseh Masoudi ◽  
Georges Fadel
Keyword(s):  
Genetic Algorithm ◽  
Complex Systems ◽  
Geometric Structure ◽  
Optimization Problem ◽  
Interconnected Systems ◽  
Test Cases ◽  
Computationally Efficient ◽  
Cable Harness ◽  
Multiobjective Genetic Algorithm ◽  
Optimization Framework

Abstract The components of complex systems such as automobiles or ships communicate via connectors, including wires, hoses, or pipes whose weight could substantially increase the total weight of the system. Hence, it is of paramount importance to lay out these connectors such that their overall weight is minimized. In this paper, a computationally efficient approach is proposed to optimize the layout of flexible connectors (e.g., cable harnesses) by minimizing their overall length while maximizing their common length. The approach provides a framework to mathematically model the cable harness layout optimization problem. A Multiobjective Genetic Algorithm (MOGA) solver is then applied to solve the optimization problem, which outputs a set of non-dominated solutions to the bi-objective problem. Finally, the effects of the workspace’s geometric structure on the optimal layouts of cable harnesses are discussed using test cases. The overarching objective of this study is to provide insight for designers of cable harnesses when deciding on the final layout of connectors considering issues such as accessibility to and maintainability of these connectors.

Semi-Active Control for Benchmark Building Using Innovative TMD with MRE Isolators

2020 ◽  
Vol 20 (06) ◽  
pp. 2040009
Author(s):  
Xinchun Guan ◽  
Jingcai Zhang ◽  
Hui Li ◽  
Jinping Ou
Keyword(s):  
Active Control ◽  
Control Strategies ◽  
Variable Stiffness ◽  
Control Device ◽  
Structural Vibration ◽  
Control Force ◽  
Linear Quadratic ◽  
Structure System ◽  
Magneto Rheological ◽  
Active Damper

Tuned Mass Damper (TMD) with magneto-rheological elastomer isolators (MRE-TMD) is a novel control device for suppressing structural vibration caused by earthquakes. It is a nonlinear hybrid vibration absorber and the stiffness & damping can be controlled by changing the current of isolators’ coil. Using MRE-TMD as an adaptive frequency TMD to mitigate vibration and treating it as only a passive damper is the focus of most nowadays researches. In this paper, semi-active control theory is introduced to the MRE-TMD-structure system which means that the control force can be obtained through variable stiffness & damping technology, and MRE-TMD is a semi-active damper instead of a passive one. A control system sketch, as well as principles and control strategies of a semi-active MRE-TMD-structure system for vibration control is designed. An improved limited sliding (ILSL) algorithm based on linear quadratic optimal theory is also introduced. Numeric simulations of a five-story benchmark building model equipped with semi-active MRE-TMD subjected to several benchmark earthquake records are conducted to investigate the control performance of the proposed semi-active MRE-TMD. Control force characteristics of the structural MRE-TMD systems are also evaluated. The results indicate that semi-active MRE-TMD can provide control force to the system and it shows superior ability to suppress the structural vibrations of comparing to the passive MRE-TMD.

Optimal Weighting Matrices Design for LQR Controller Based on Genetic Algorithm and PSO

2012 ◽  
Vol 433-440 ◽  
pp. 7546-7553 ◽  
Author(s):  
S. Amir Ghoreishi ◽  
Mohammad Ali Nekoui
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Closed Loop ◽  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Speed Of Response ◽  
Lqr Controller ◽  
Optimal Weighting

In this paper, considering some important indices such as closed-loop pole locations, speed of response and combining them into an objective function an optimization problem is defined in order to select the weighting matrices in Linear Quadratic Regulator (LQR) controller. To solve this optimization problem the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized and compared. The proposed method is applied to rotational inverted pendulum. Simulation results show the relative superiority of PSO over GA.

scholarly journals Vibration Control Method of an Electromagnetic Isolation System Based on LQR and Coevolutionary NGA

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Lei Zhang ◽  
Xiangtao Zhuan
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Active Control ◽  
Vibration Isolation ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
State Equation ◽  
Linear Quadratic ◽  
Isolation System ◽  
Vibration Isolation System

An electromagnetic isolation system can dynamically adjust the output characteristic parameters of the system in real time through the active control strategy, which has strong adaptability to the external environment. In order to control the electromagnetic vibration isolation system effectively, an active control method is presented based on the linear quadratic regulator (LQR) approach and the coevolutionary niche genetic algorithm (NGA). In this paper, the dynamical equation and state equation of the electromagnetic isolation system are built, which include the nonlinear relationship between electromagnetic force and coil current and gap. The LQR approach is employed to maintain a steady state of an isolated object on the vibration isolation system. Meanwhile, a coevolutionary niche genetic algorithm is put forward to optimize the parameters in Q and R matrices. Simulation and experimental results demonstrate that the electromagnetic isolation system with the LQR approach and coevolutionary NGA can effectively isolate the vibration and maintain a steady state for an isolated object in comparison with the passive isolation system.

Genetic algorithm-based multi-objective design of optimal discrete sliding mode approach for trajectory tracking of nonlinear systems

2019 ◽  
Vol 233 (15) ◽  
pp. 5237-5252
Author(s):  
Anouar Benamor ◽  
Wafa Boukadida ◽  
Hassani Messaoud
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Nonlinear Systems ◽  
Optimization Problem ◽  
Sliding Mode ◽  
Tracking Error ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Multi Objective ◽  
Highly Nonlinear

In this paper, a novel multi-objective design of optimal control for robotic manipulators is considered. Generally, robots are known by their highly nonlinearities, unmodeled dynamics, and uncertainties. In order to design an optimal control law, based on the linear quadratic regulator, the robotic system is described as a linear time varying model. The compensation of both disturbances and uncertainties is ensured by the integral sliding mode control. The problem of deciding the optimal configuration of the linear quadratic regulator controller is considered as an optimization problem, which can be solved by the application of genetic algorithm. The main contribution of this paper is to consider a multi-objective optimization problem, which aims to minimize not only the chattering phenomenon but also other control performances including the rise time, the settling-time, the steady-state error and the overshoot. For that, a novel dynamically aggregated objective function is proposed. As a result, a set of nondominated optimal solutions are provided to the designer and then he selects the most preferable alternative. To demonstrate the efficacy and to show complete performance of the new controller, two nonlinear systems are treated in this paper: firstly, a selective compliance assembly robot arm robot is considered. The results show that the manipulator tracing performance is considerably improved with the proposed control scheme. Secondly, the proposed genetic algorithm-based linear quadratic regulator control strategy is applied for pitch and yaw axes control of two-degrees-of-freedom laboratory helicopter workstation, which is a highly nonlinear and unstable system. Experimental results substantiate that the weights optimized using genetic algorithm, result in not only reduced tracking error but also improved tracking response with reduced oscillations.

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