Effects of bearing deadbands on bearing loads and rotor stability

The Jeffcott model of a turbopump which was modified by adding deadband (clearance) effects along with fluid seal forces are currently understood. Equations of motion for the model were written in polar coordinates, and a constant side force was added to the model to account for the likely misalignment between bearings and seals. The force models and system equations of motion are described as well as limit cycle, and stability analyses. Studies of systems with rotor imbalance and with or without side effects were studied for three types of motion. Results show that: (1) deadband does not affect stability-in-the-large; (2) stability-in-the small is enhanced by deadband and side force; (3) bearings loads are highest for motion with synchronous or nonsynchronous periodic enclosing origin; (4) side force acting in concert with deadband effects may either increase or decrease bearing loads; and (5) bearing loads in a stable pump are determined primarily by rotor imbalance and side forces

Control system design for flexible structures using data models

The dynamics and control of flexible aerospace structures exercises many of the engineering disciplines. In recent years there has been considerable research in the developing and tailoring of control system design techniques for these structures. This problem involves designing a control system for a multi-input, multi-output (MIMO) system that satisfies various performance criteria, such as vibration suppression, disturbance and noise rejection, attitude control and slewing control. Considerable progress has been made and demonstrated in control system design techniques for these structures. The key to designing control systems for these structures that meet stringent performance requirements is an accurate model. It has become apparent that theoretically and finite-element generated models do not provide the needed accuracy; almost all successful demonstrations of control system design techniques have involved using test results for fine-tuning a model or for extracting a model using system ID techniques. This paper describes past and ongoing efforts at Ohio University and NASA MSFC to design controllers using 'data models.' The basic philosophy of this approach is to start with a stabilizing controller and frequency response data that describes the plant; then, iteratively vary the free parameters of the controller so that performance measures become closer to satisfying design specifications. The frequency response data can be either experimentally derived or analytically derived. One 'design-with-data' algorithm presented in this paper is called the Compensator Improvement Program (CIP). The current CIP designs controllers for MIMO systems so that classical gain, phase, and attenuation margins are achieved. The center-piece of the CIP algorithm is the constraint improvement technique which is used to calculate a parameter change vector that guarantees an improvement in all unsatisfied, feasible performance metrics from iteration to iteration. The paper also presents a recently demonstrated CIP-type algorithm, called the Model and Data Oriented Computer-Aided Design System (MADCADS), developed for achieving H(sub infinity) type design specifications using data models. Control system design for the NASA/MSFC Single Structure Control Facility are demonstrated for both CIP and MADCADS. Advantages of design-with-data algorithms over techniques that require analytical plant models are also presented