Active control of earthquake excited structures using fuzzy supervisory technique

Active structural control is a promising and effective approach to load reduction of floating wind turbines. This paper investigates use of active structural control to mitigate loads of a floating wind turbine on a barge platform. Different from the existing results, static output feedback is employed as the control law for reducing implementation complexity while a turned mass damper is considered to be installed on the platform instead of in the nacelle. To design active structural controllers, first an input-output linear design model for the wind turbine is identified from time response data, and then an advanced generalized $H_{\infty}$ method is employed for optimizing the controller gain so as to reduce wave induced loads. Through high-fidelity simulation results of the wind turbine, it is found that the designed active controllers could further reduce the main fatigue load and the generator power error, but the standard $H_{\infty}$ one is not economical and lacks enough reliability. The rationale of the generalized $H_{\infty}$ method in trading off load reduction and controller gain reduction is also discussed.

Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust control methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.

A parameter dependent Riccati equation approach is taken to analyze the stability properties of an output feedback adaptive control law design. The adaptive controller is intended to augment a nominal, fixed gain, observer based output feedback control law. Although the formulation is in the setting of model following adaptive control, the realization of the adaptive controll er does not require implementing the reference model. In this regard, the cost of implementing the adaptive controller above that of a fixed gain control law is far less than that of other methods. The error signals are shown to be uniformly ultimately bounded and an expression for the ultimate bound is provided. The control design process and theoretical results are illustrated using a model for wing-rock dynamics. Research in adaptive output feedback control of uncertain nonlinear systems is motivated by the many emerging applications that employ novel actuation devices for active control of flexible structures and fluid flows. These applications include actuators such as piezo-electric films and s ynthetic jets, which are typically nonlinearly coupled to t he plant dynamics they are intended to control. Models for these applications vary from accurate low frequency models to models that crudely approximate the true dynamics even at low frequencies. Examples of applications include active damping of flexible structures, control of aeroservoelasti c aircraft, and active control of flows. Adaptive control can be used to satisfy performance requirements in the presence of large scale parameter uncertainty, and improved safety in the event of actuator failure.

Active vibration control of large flexible space structure is a challenging topic in the system dynamics and control of spacecraft. This paper proposes a novel approach for vibration control on a large hoop truss structure, typically used as mesh satellite antenna. First, to suppress the first-order bending modal response of the hoop truss structure with an initial disturbance, a piezoelectric bending actuator with excellent bending actuation performance was carefully designed as a key component of an active vibration control system. Then, the actuating characteristics of the actuator and the dynamic equations of the active structure were analyzed and formulated based on a finite element method. In order to improve the vibration-attenuating effect of the control system, a Mamdani-type fuzzy logic algorithm was employed in a closed-loop control system. Finally, simulations and experiments were implemented to validate the effectiveness of the proposed active control approach and structure. The experimental results showed that the decay time of first-order bending modal response (around 0.34 Hz) of control system reduces by 75% compared with that of the uncontrolled system. The results demonstrate that the proposed active vibration control system has good application potential in controlling the bending modes of a large flexible spacecraft.

Real-time hybrid simulation for seismic control performance evaluation of an active inerter damper system

Dynamic aeroelastic response and active control of composite thin-walled beam structures in compressible flow

Active control of building structure using lattice probabilistic neural network (LPNN) employing the gradient descent method (GDM) for learning to increase control capability is proposed. With the lattice pattern of the state vector used as the training data, LPNN calculates the control force using only the adjacent information of input, thus, response is greatly faster. Three story building under El Centro earthquake is used to train the LPNN. Northridge earthquake is used to verify the proposed method. In the numerical simulation of the building structure control, the control results of the LPNN are compared with the uncontrolled results. The proposed LPNN algorithm can effectively reduce the response of the building structure under earthquakes.

The interest of this paper is to develop a general and systematic robust control methodology for active vibration control of flexible structures. For this purpose, first phase and gain control policies are proposed to impose qualitative frequency-dependent requirements on the controller to consider a complete set of control objectives. Then the proposed control methodology is developed by employing phase and gain control policies in the dynamic output feedback H∞ control: according to the set of control objectives, phase and gain control policies incorporate necessary weighting functions and determine them in a rational and systematic way; on the other hand, with the appropriate weighting functions efficient H∞ control algorithms can automatically realize phase and gain control policies and generate a satisfactory H∞ controller. The proposed control methodology can be used for both SISO and MIMO systems with collocated or non-collocated sensors and actuators. In this paper, it is validated on a non-collocated piezoelectric cantilever beam. Both numerical simulations and experimental results demonstrate the effectiveness of the proposed control methodology.

Through the use of active controllers, a structure can modify its behavior during dynamic loadings such as impact, wind, or earthquake loadings. Such structures with self-modification capabilities are called smart structures. The smart-structure technology will have enormous consequences in terms of preventing loss of life and damage to structure and its content specially for large structures with hundreds of members. In this paper, a computational model is presented for active control of large adaptive structures subjected to dynamic loadings such as impact, wind, and earthquake loadings. The governing differential equations of the open-loop and closed-loop systems are formulated, and a recursive approach is presented for computing the response of the structure. A robust parallel-vector algorithm is developed for the recursive solution of the response of the open-loop and closed-loop systems. The computational model is applied to active control of large bridge structures. Three different schemes are investigated for optimal placement of controllers in bridge structures. Results are presented for three types of bridge structures: single-span, multispan continuous, and curved steel-truss bridges.

Active robust vibration control of flexible structures

Due to the recent advances in microprocessors, active control of a flexible structure has become a realizable method for suppressing the vibration. Conventional modal-based method encounters difficulties in controlling a distributed parameter structure, since such a structure has an infinite number of vibration modes. To overcome this problem, active wave control has been studied in recent years. This paper presents an active wave control of an orthotropic rectangular panel by expanding the conventional active wave control method for a two-dimensional structural case. First, a transfer matrix method for a rectangular panel is introduced to describe the wave dynamics of the structure. This is followed by the derivation of feedforward control laws for absorbing reflected waves or eliminating transmitted waves. In the proposed method, the control laws are including the modal actuation scheme for uncontrolled direction. Then, from a viewpoint of numerical analyses, basic properties of the proposed method are verified. It is found that the reflected wave absorbing control enables the inactivation of all vibration modes in the controlled direction and the transmitted wave eliminating control enables the generation of an almost vibration-free state.

This paper describes the results of an active structural control experiment performed for the Advanced Control Evaluation for Structures (ACES) testbed at NASA-Marshall as part of the NASA Control-Structure Interaction Guest Investigator Program. The experimental results successfully demonstrate the effectiveness of a 'dipole' concept for line-of-sight control of a pointing system mounted on a flexible structure. The simplicity and effectiveness of a classical 'single-loop-at-a-time' approach for the active structural control design for a complex structure, such as the ACES testbed, are demonstrated.

Active control of structures is usually performed by application of additional external forces, (tendon or support action, actuator action, [2,5,6]) which vary according to a specified rule depending on the external load variation. In this paper, the concept of active structure adaptation to varying loads will be discussed by assuming that initial distortion fields ∈ 0(x,t) within a structure can be generated and varied. Such distortion fields could, for instance, be generated by temperature fields associated with proper heating or cooling of structure elements or by introducing mechanical dislocations and disclinations in truss or beam structures. For instance, shortening or elongating of bars OC and OD of a hyperstatic truss shown in Fig. 4 induces self-equilibrated stress states σ r and the associated initial strain states ∈r. These states can be used to control the total stress and strain states σ=σ r + σ l and ∈=∈ r + ∈ l of a structure where σ l, and ∈ l are the stress and strain states due to external loading. The concept of active control of civil engineering or space structures by means of distortion fields provides an additional feasible option especially in cases where quasistatic control is required, for instance in counteracting the environmental temperature changes and their effect on structure stress and displacement fields.

The main issue concerning the active control of structures and the reason for its rare application is the difficulty in reliably generating adequate control forces with a low power demand. Furthermore, the additional weight resulting from the active device needs to be kept small. In accordance with these requirements, a novel active mass damper for vibration control of structures was developed. In this study, the new damper and the possibilities of force genera- tion are presented. The application of the damper for bridge deck flutter control is demonstrated using a numerical example.

This paper studies the feasibility of self-powered active vibration control of structures with Tuned Mass Dampers (TMDs). Without consuming external energy, the proposed self-powered vibration control strategy can provide better performance than the passive TMD in mitigating the vibration of buildings induced by wind load. the vibration-dissipative element of TMD is replaced with an electromagnetic machine, which serves as actuator and harvester at the same time. First, the desired force is obtained by adopting Linear Quadratic Regulator (LQG) optimal control. Then, the self-powered active control strategy is designed based on the essence of the desired force, which can be passive or active types. The energy of the vibration can be harvested as electricity in energy harvesting mode, and pumped back into the mechanical system when instant active force is required. Switch based circuits with capability of bi-directional power flow are presented for the implementation of self-powered active TMDs. With taking the efficiency of the harvesting and driving circuits into account, numerical simulations are carried out based on a tall building with a TMD under random and harmonic excitations. The results indicate the feasibility and effectiveness of self-powered active TMDs.