Research On Intelligent Vibration Control And Optimization Of High-Rise Building

The intelligent control problems of a high-rise building with the elastic and the elastoplastic properties were studied in this thesis. To solve the problems, convergence of several algorithms was discussed, which include discrete instantaneous optimal control algorithm and optimal control algorithm based on instantaneous optimal and iterative learning control for linear elastic system, the iterative learning control and its convergence for the elastic-plastic system. In addition, the effects of the soil-structure interaction on the response of structure caused, the P_Δ effect and the optimization on the positions of the active controllers are discussedResearches have been done are as follows:1. Two discrete instantaneous optimal control algorithms named the first order approximate discrete instantaneous optimal control algorithm and the discrete instantaneous optimal control algorithm were derived from instantaneous optimal control algorithm. The stability of the control system has been proved by using the Lyapunov second method. The Lyapunov first method was deployed in the process of numerical analysis to verify stability of the controlled system. Results indicate that the discrete instantaneous optimal control algorithms have better control effects on a specific high-rise building model undergoing the given input seismic waves. And the discrete instantaneous optimal control algorithm shows a better control effect.2. A new intelligent control algorithm was proposed based on the classical instantaneous optimal control algorithm and the iterative learning intelligent control algorithm. The new intelligent algorithm is designed for both linear elastic discrete and linear elastic continuous system. It regards difference between responses of the systems and the desired responses as feedbacks. Quadratic form is considered as the objective function. Control signals are modified by the iterative learning control algorithm so that control effects can be improved. The sufficient condition was proposed under which the new control algorithm is convergent. Results of numerical analysis implies that, compared with the instantaneous optimal control algorithm, obvious improvement in response control of high-rise building undergoing seismic load can be observed when the new control algorithm is deployed. The control effect of acceleration responses is not as strong as expected because the acceleration responses are not considered as feedbacks of the system.3. The iterative learning control tactics for the high-rise building with the elastoplastic properties was proposed based on iterative learning control algorithm and its sufficient condition of convergence has been derived. Results of numerical analysis indicate that the iterative learning control algorithm has better control effect, especially for the displacement peak responses and displacements of the residual deformations.4. Equivalent stiffness of the foundation in both vertical direction and lateral direction was derived based on stress and displacement solution of arbitrary position in elastic half space and foundation-stress form when vertical and lateral concentrated loads were applied. By considering the damp of the foundation as the radiation damping, numerical simulation was carried out to analyze the effects of different foundation stiffness on the responses of the high-rise building with the elastic properties and the elastoplastic properties. Results of numerical analysis indicate that the soil-structure interaction has an effect on the seismic responses. What’s more, the soil structure interaction has much more influence on the responses, and has no obvious regularity for the controlled system with the elastoplastic characteristic.5. The dynamical models with P_Δ effect were established for the elastic and elastoplastic high-rise structures. Results of numerical analysis indicate that when the P_Δ effect is considered, the seismic wave with the lower frequency component part has negative influence on the response of the high-rise structure.6. Based on the genetic algorithm, an improved genetic algorithm was proposed, which takes into account the scale transformation of the target function and the individual migration mechanism to improve the convergence of the algorithm and prevent it from premature convergence of the algorithm. The improved genetic algorithm was used to carry out the optimization on the positions of the active controllers in the building. The responses of three cases were compared, which include uncontrolled structure, the structure with controllers in every floor, and the structure with a small amount of controllers (5 floors). One can find that the control effect of the structure with a small amount of controllers (5 floors) set in special floors, which is optimized by the improved genetic algorithm, is close to or even better than one of the structure with controllers in every floor.