A. H. ElSinawi

Optimal Control of Magnetorheological Fluid Dampers for Seismic Isolation of Structures

This paper presents the modeling and control of a magnetorheological (MR) damper, installed in Chevron configuration, at the base of a 20-story benchmark building. The building structural model is created using the commercial software package ETABS. The MR damper model is derived from Bouc-Wen hysteresis model which provides the critical nonlinear dynamics that best represents the MR damper under a wide range of operating conditions. System identification is used to derive a low-order nonlinear model that best mimics the nonlinear dynamics of the actual MR damper. Dynamic behavior of this low-order model is tested and validated over a range of inputs. The damper model has proven its validity to a high degree of accuracy against the nonlinear model. A Kalman filter is designed to best estimate the state of the structure-damper system for feedback implementation purposes. Using the estimated states, an LQG-based compensator is designed to control the MR damper under earthquake loads. To demonstrate the effectiveness of this control strategy, four historical earthquakes are applied to the structure. Controlled and uncontrolled floor accelerations and displacements at key locations are compared. Results of the optimally controlled model demonstrate superior performance in comparison to the uncontrolled model.

Comprehensive Dynamic Model of a Viscously Damped RF-MEMS Switch Including Squeeze Film and Impact Force Effects

This work presents a new approach to modeling the dynamic behavior of a viscously damped RF-MEMS switch. The model takes into account the effect of squeeze film on resonance frequencies of the switch structure. It also presents a new approach to modeling the impact force as well as its effect on transient pull-in, and release dynamics of the perforated switch membrane. Simulation results of the proposed model are validated against experimental results of the same exact switch, and the comparison was impressive. Model results show that the model is able to capture the experimental behavior of the switch with less than 2% error.

Adaptive seismic isolation of structures using MR-fluid dampers

This paper presents the modeling and control of an MR damper installed between the ground and first floor of a 5-story base isolated building. The building structural model is derived from a benchmark structure model using ETABS. The MR damper model considered is derived from Bouc-Wen Hysteresis model proposed by Spenser et al [1], and several other authors. System identification technique is used to derive a simple 4th order nonlinear model that best approximates the dynamics of the actual MR damper. The dynamic behavior of this simple model is tested and validated over a wide range of inputs and proved to be very representative of the Bouc-Wen Hysteresis model. A Kalman filter is designed to best estimate the state of the structure-damper system for the purpose of feedback implementation. An LQG based controller is designed to control the MR damper under dynamic loads. The effectiveness of this control strategy over a wide range of historical earthquakes is demonstrated. Accelerations and drifts at all building floors are computed and plotted. The controlled and uncontrolled results are compared and significant improvement in the MR damper performance is demonstrated.

Multi-input single-output (MISO) random system modeling using methods of system identification

The paper utilizes techniques commonly used in the system identification dynamic systems behavior using output-input data to an unknown dynamic system. The identification techniques are based on nine inputs and one output. The system is applied to a financial time series that represent the historical prices of gold. The nine inputs are the technical indicators calculates form the historical data of open, high, low, close, and volume of trading the gold while the output is the forecasted value of the closing price of gold. Nonlinear Identification techniques used in this paper include wavelet Network, Sigmoid Network and Tree Partition. The purpose of the identification techniques is come up with a dynamic system model “either a transfer function or State-Space model” that is capable of predicting the values of the output “close”. The data is split into estimation set and verification set. The estimation group is used in determining the best possible model that can predict the verification set of data. The highest match obtained was 92%. Details on the modeling techniques as well as the effect of each input on the output are also presented in this paper. Simulation results are utilized to examine the accuracy and integrity of the model proposed.

Linearized state-space model of the behavior of MR-fluid dampers

Magnetorheological (MR) dampers are semi-active control dampers that use MR fluids to provide controllable damping characteristics. MR dampers have proven to be more effective than passive dampers in protecting civil structures during seismic events. While passive dampers have been thoroughly analyzed and understood by researchers, active and semi active dampers are still under investigation by many researchers. MR dampers added protection is achieved by adjusting the damping characteristics of the device so as to minimize structural dynamic loads. Models of the MR dampers highly nonlinear and difficult to adapt for active control, therefore, in this work, the MR damper model presented by Spencer et al will be solved numerically to obtain force-velocity data points. The data obtained from numerical solution of the damper model will be used to construct a linearized state-space model for control purposes. The state space model is obtained via system identification techniques and its agreement with the nonlinear model is discussed.

Dual LQG-PID control of a highly nonlinear magnetic levitation system

A study of one-dimensional position control of a light iron ball levitated by one electromagnet is proposed in this work. The vertical position of the ball is the target of the proposed control strategy. It is assumed that the position measurement of the ball is inaccessible and thus, estimates of the position are utilized as the feedback signal to the controller. Control of the balls position is carried out using LQG-based controller with the objective of manipulating the electromagnet current to drive the ball to steady state with minimal error. The integrity of the controller as well as accuracy of the systems model is evaluated via simulation.

Feedback control of membrane displacement in RF-MEMS switches

Control of transient behavior of RF-MEMS switch membrane is crucial to the durability and reliability of the switch. This work presents a novel technique for controlling the displacement of the switch membrane. The technique shows exceptional capabilities of achieving soft landing of the membrane on contact pads at pull-in voltage, and significant improvement of pull-out transient. The control technique presented in this work is physical based and generic in nature, thus making it adaptable and scalable to any switch. Comparison between switch behavior with and without control shows 80% improvement in impact dynamics and approximately 70% improvement in overshoot and settling time during pull-out.

A Study of Non-Uniform SPST RF-MEMS Switch under the Effect of Squeeze Film Damping

This work presents a practical technique that can be used to construct the dynamic model of any RF MEMS switch regardless of its shape. The presented technique also allows for inclusion of squeeze film effect in the model without resorting to complex mathematical development of the latter. The technique utilizes Finite element methods to determine mode shapes and natural frequencies of the switch. A modal-model is then constructed from the FEA results. The model can be reduced using by retaining modes with highest Hankel norm modes to reduce calculations effort associated with large models. Simulation results have shown that the proposed model has merit and agrees with published experimental data.

Active control of tool position in the presence of nonlinear cutting force and machine tool dynamics in orthogonal cutting

This work presents a practical approach to the control of tools position, in orthogonal cutting, in the presence nonlinear dynamic cutting forces and machine tool dynamics. The controller is Linear Quadratic Gaussian (LQG) type constructed from an augmented model of machine tool realization, tool-actuator dynamics, and a nonlinear dynamic model relating tool displacement to cutting forces. The latter model is obtained using black-box system identification of experimental orthogonal cutting data in which tool displacement is the input and cutting force is the output. The controller is evaluated and its performance is demonstrated.