Multi-objective Optimization and Intelligent Fuzzy Control of Structural Vibration Control

Multi-objective Optimization and Intelligent Fuzzy Control of Structural Vibration Control
　　Being a kind of active and effective countermeasure against undesirable excitations such as seismic or strong wind, structural vibration control technology is one of the hotspots in the research field of civil engineering. Considering some existing problems in theoretical study and practical application of structural control system, the work in this study mainly consists of three parts: the first part deals with multi-objective optimization of control system based on linear matrix inequality (LMI) technique and evolutionary algorithm, including optimization design of controller and integrated optimization design of controllers and actuators; the second part focuses on the intelligent vibration control strategies for nonlinear structure, in which adaptive fuzzy logic control and intelligent fault tolerant control (FTC) are proposed; finally, based on application of vibration control system for important engineering structure, numerical analysis and experimental study are conducted to demonstrate the effectiveness and superiority of those methodologies.The main contents of this dissertation are listed as follows:1. To Strong magnets improving the traditional design method of controller, in which the parameters of controller are determined by repeated calculation, multi-objective variance control is investigated for structural vibration control based on the LMI optimization technique and variance control theory.
　　The stationary filtered white noise-controlled structure-controller is simulated using extended state space model, in which the influence of external exciting is taken into account. The general expression of linear matrix inequalities (LMIs) are deduced to satisfy the closed-loop poles and the steady variance responses of structure and control force with certain constraints assigned in advance. LMI Toolbox of MATALB is employed for solving those LMIs to get the state feedback and output feedback controller. Simulation results demonstrate the effectiveness of the proposed method.2. Based on the LMI optimization technique and robust control theory, the robust H2/H∞control strategy is investigated to cope with the uncertainty of dynamic characteristic of the structure, in which the uncertainty is taken into account in advance. In the process of controller design, uncertain parameters of structure are introduced into perturbation matrix, meanwhile, both the H disturbance suppression and the optimal H2 performances of the closed-loop control system are satisfied simultaneously for all allowable uncertainties. To solve the proposed multi-objective optimization problem, LMIs are also deduced based on the LMI optimization technique. Simulation results show that the performance of the proposed controller is of strong robustness.
　　3. Aimed at the disadvantage of http://www.chinamagnets.biz/ traditional optimization method, such that the placement and controller are optimized sequentially, single objective is considered, a new integrated design and multi-objective optimization method for active control system based on a pareto genetic algorithms and random vibration theory is proposed, in which both the controller and actuator allocation can be optimized simultaneously. Random seismic excitation is simulated by the stationary filtered white noise, and then the root-mean square (RMS) quantities of structural responses and active control forces are obtained by solving the Lyapunov equation in the state space. LQG algorithm is employed herein. Minimization of the maximal RMS displacement and acceleration which are normalized by the uncontrolled counterparts, together with minimizing the sum of RMS control force of actuators, have been used as the three objective functions for multi-objective optimization. The effects of structural parameters and excitation characteristic are considered in the multi-objective optimization procedure, and number-based zoning control method is also proposed for determining the number of actuators. Numerical simulation results show that the proposed integrated design and optimization method is simple, efficient and practical, and of good universality.4. Based on adaptive control theory and intelligent fuzzy control, variable universe adaptive fuzzy control (VUAFLC) algorithm is put forward to improve the performance of traditional FLC, and the adaptive law of output universes is developed based on Lyapunov function method. Benchmark structural control problem for a seismically excited highway bridge is used as a numerical example to demonstrate the effectiveness and robustness of the proposed method. Furthermore, VUAFLC is integrated with clipped-optimal control algorithm for semi-active control system with MR damper. Results show that MR damper can achieve almost the same control performance as active control system, which promises a good prospect of popularization and application of semi-active MR dampers.
　　5. An intelligent fault tolerant control (FTC) strategy is investigated for MR semi-active control system with sensor failure. Performance and effectiveness of the control system are protected in case of sensor failure. Based on the adaptive neuro fuzzy inference system (ANFIS), sensor failure can be on-line detected and switching control strategy of determining the commanded voltage for MR dampers is proposed. When sensor is healthy, voltage determined by FLC will be applied to the corresponding MR damper. On the other hand, if sensor has failed and will be detected using ANFIS, switch is activated and passive-on voltage will be applied to MR damper. Numerical simulations are carried out to demonstrate the effectiveness of the proposed method, and some useful conclusions are also obtained.6. On the background of application of HMD control system for important engineering structure, HMD control system model base on permanent magnet synchronous linear motor (PMSLM) for http://www.chinamagnets.biz/ experimental study is designed and manufactured to verify the effectiveness of the control system and the proposed control strategies mentioned above, while the uncertainty of mass of TMD is taken into account to demonstrate the robustness of the proposed control strategies. Based on lots of test for AMD and shaking table test, the reasonable theoretical model have been established and some control strategies have been designed, including LQG, robust H2/H∞, FLC, VUAFLC and ANFIS control. Finally, experimental verification studies are conducted to test the performance of the proposed HMD control system and control strategies, and comparative analysis of control strategies is also discussed, which provides a foundation for engineering application of HMD control system.