A numerical approach to controller design for the ACES facility

In recent years the employment of active control techniques for improving the performance of systems involving highly flexible structures has become a topic of considerable research interest. Most of these systems are quite complicated, using multiple actuators and sensors, and possessing high order models. The majority of analytical controller synthesis procedures capable of handling multivariable systems in a systematic way require considerable insight into the underlying mathematical theory to achieve a successful design. This insight is needed in selecting the proper weighting matrices or weighting functions to cast what is naturally a multiple constraint satisfaction problem into an unconstrained optimization problem. Although designers possessing considerable experience with these techniques have a feel for the proper choice of weights, others may spend a significant amount of time attempting to find an acceptable solution. Another disadvantage of such procedures is that the resulting controller has an order greater than or equal to that of the model used for the design. Of course, the order of these controllers can often be reduced, but again this requires a good understanding of the theory involved

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

Microstructural Modeling of Metadynamic Recrystallization in Hot Working of IN 718 Superalloy

The hot deformation behavior of IN 718 superalloy has been characterized in the temperature range 900–1100°C and strain rate range 0.001–1.0 s−1 using compression tests on process annealed material, with a view to obtain a correlation between grain size and the process parameters. At a strain rate of 0.001 s−1, the material exhibits dynamic recrystallization (DRx) at 975°C and superplasticity at 1100°C, while metadynamic recrystallization (MDRx) occurs in the temperature range 950–1100°C and strain rate range 0.01–1.0 s−1. Unlike in the DRx domain, the grain size (d) variation in the MDRx regime could not be correlated with the standard Zener–Hollomon (Z) parameter due to strong thermal effects during cooling after hot deformation. However, it follows an equation of the type d=cexp(−Q/RT), where c, p and R are constants, Q the activation energy for MDRx and T the temperature. The value of p is very low (0.028) and the apparent activation energy is about 275 kJ mole−1, which is very close to that for self-diffusion in pure nickel. The data obtained from several investigators are in agreement with this equation. Such an equation combines the mild dynamic effect in MDRx with a stronger post-deformation cooling effect and may be used for predicting the grain size of IN 718 hot forged in the MDRx regime

Modeling Grain Size During Hot Deformation of IN 718

Aerospace gas turbine disks operate in an environment of relatively high stresses caused by centrifugal forces and elevated temperatures. These severe conditions necessitate the need for materials with high temperature strength and good low cycle fatigue resistance. One class of alloys used for this task is the nickel base superalloys, out of which, IN 718 is the most widely used in the aerospace industry (1). The properties of IN 718 are attributed to the combined effects of the chemistry, heat treatment, and microstructure. The chemistry is tailored not only for solid solution strengthening but also for precipitation hardening developed during heat treatment, which combined with a fine grained microstructure lead to excellent mechanical properties such as low cycle fatigue resistance and elevated temperature strength. The properties of a gas turbine disk are sensitive to the microstructure, in particular the grain size, which is dependent on the processing history. The ability to precisely control the microstructural development during forging is dependent on controlling the process so that the workpiece is deformed within a “safe” region where no microstructural damage or flow instabilities occur. The microstructural mechanisms during deformation may themselves vary within the “safe” region and it is desirable to determine them within the range of parameters that are commonly used in industrial processing. The objective of this work is to establish a relationship between the grain size and the process control parameters i.e., temperature and strain rate, in the hot working of IN 178

Microstructural Modeling of Metadynamic Recrystallization in Hot Working of IN 718 Superalloy

The hot deformation behavior of IN 718 superalloy has been characterized in the temperature range 900–1100°C and strain rate range 0.001–1.0 s−1 using compression tests on process annealed material, with a view to obtain a correlation between grain size and the process parameters. At a strain rate of 0.001 s−1, the material exhibits dynamic recrystallization (DRx) at 975°C and superplasticity at 1100°C, while metadynamic recrystallization (MDRx) occurs in the temperature range 950–1100°C and strain rate range 0.01–1.0 s−1. Unlike in the DRx domain, the grain size (d) variation in the MDRx regime could not be correlated with the standard Zener–Hollomon (Z) parameter due to strong thermal effects during cooling after hot deformation. However, it follows an equation of the type d=cexp(−Q/RT), where c, p and R are constants, Q the activation energy for MDRx and T the temperature. The value of p is very low (0.028) and the apparent activation energy is about 275 kJ mole−1, which is very close to that for self-diffusion in pure nickel. The data obtained from several investigators are in agreement with this equation. Such an equation combines the mild dynamic effect in MDRx with a stronger post-deformation cooling effect and may be used for predicting the grain size of IN 718 hot forged in the MDRx regime