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Applied System Identification

Analytical Methods in Vibrations

In the last decade smart technologies have become enablers that cut across traditional boundaries in materials science and engineering. Here we define smart to mean embedded actuation, sensing, and control logic in a tightly coupled feedback loop. While multiple successes have been achieved in the laboratory, we have yet to see the general applicability of smart devices to real aircraft systems. The NASA Aircraft Morphing program is an attempt to couple research across a wide range of disciplines to integrate smart technologies into high payoff aircraft applications. The program bridges research in seven individual discoplines and combines the effort into activities in three primary program thrusts. System studies are used to assess the highest-payoff program objectives, and specific research activities are defined to address the technologies required for develpment of smart aircraft systems. In this paper we address the overall program goals and programmatic structure, and discuss the challenges associated with bringing the technologies to fruition.

The Aircraft Morphing Program

A mechatronic system is an assembly of technological components, such as a mechanism, sensors, actuators, and a control unit. Recently, a number of researchers and industrial manufacturers have highlighted the potential advantages of lightweight parallel mechanisms with respect to the accuracy, dynamic performances, construction cost, and transportability issues. The design of a mechatronic system with such a mechanism requires a multidisciplinary approach, where the mechanical deformations have to be considered. This thesis proposes two original contributions in this framework. (i) First, a modular and systematic method is developed for the integrated simulation of mechatronic systems, which accounts for the strongly coupled dynamics of the mechanical and non-mechanical components. The equations of motion are formulated using the nonlinear Finite Element approach for the mechanism, and the block diagram language for the control system. The time integration algorithm relies on the generalized-α method, known in structural dynamics. Hence, well-de ned concepts from mechanics and from system dynamics are combined in a uni ed formulation, with guaranteed convergence and stability properties. Several applications are treated in the elds of robotics and vehicle dynamics. (ii) Usual methods in exible multibody dynamics lead to complex nonlinear models, not really suitable for control design. Therefore, a systematic nonlinear model reduction technique is presented, which transforms an initial high-order Finite Element model into a low-order and explicit model. The order reduction is obtained using the original concept of Global Modal Parameterization: the motion of the assembled mechanism is described in terms of rigid and exible modes, which have a global physical interpretation in the con guration space. The reduction procedure involves the component-mode technique and an approximation strategy in the con guration space. Two examples are presented: a four-bar mechanism, and a parallel kinematic machine-tool. Finally, both simulation and modeling tools are exploited for the dynamic analysis and the control design of an experimental lightweight manipulator with hydraulic actuators. A Finite Element model is rst constructed and validated with experimental data. A reduced model is derived, and an active vibration controller is designed on this basis. The simulation of the closed-loop mechatronic system predicts remarkable performances. The model-based controller is also implemented on the test-bed, and the experimental results agree with the simulation results. The performances and the other advantages of the control strategy demonstrate the relevance of our developments in mechatronics.

Integrated Simulation and Reduced-Order Modeling of Controlled Flexible Multibody Systems

Anaysis and synthesis tools are developed to improve the dynamic performance of reconfigurable nonminimum phase, nonstrictly positive real-time variant systems. A novel Spline Varying Optimal (SVO) controller is developed for the kinematic nonlinear system. There are several advantages to using the SVO controller, in which the spline function approximates the system model, observer, and controller gain. They are: The spline function approximation is simply connected, thus the SVO controller is more continuous than traditional gain scheduled controllers when implemented on a time varying plant; it is easier for real-time implementations in storage and computational effort; where system identification is required, the spline funtion requires fewer experiments, namely four experiments; and initial startup estimator transients are eleminated. The SVO compensator was evaluated on a high fidelity simulation of the Shuttle Remote Manipulator System. The SVO controller demonstrated significant improvement over the present arm performance: (1) Damping level was improved by a factor of 3: and (2) Peak joint torque was reduced by a factor of 2 following Shuttle thruster firings.

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M A Scott

Papers

Time Varying Compensator Design for Reconfigurable Structures Using Non-Collocated Feedback