Optimization of stochastic processes - Midcourse guidance.
Filtering and optimal control problems for discrete stochastic dynamical systems, describing various feedback controls and midcourse guidance optimization
Jazwinski, A. H.↗
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Stable adaptive control with reduced state feedback
Stability of model tracking adaptive control systems with reduced state feedback and measurement noise
Lindorff, D. P.↗
Performance capabilities of a JPL dual-arm advanced teleoperation system
The system comprises: (1) two PUMA 560 robot arms, each equipped with the latest JPL developed smart hands which contain 3-D force/moment and grasp force sensors; (2) two general purpose force reflecting hand controllers; (3) a NS32016 microprocessors based distributed computing system together with JPL developed universal motor controllers; (4) graphics display of sensor data; (5) capabilities for time delay experiments; and (6) automatic data recording capabilities. Several different types of control modes are implemented on this system using different feedback control techniques. Some of the control modes and the related feedback control techniques are described, and the achievable control performance for tracking position and force trajectories are reported. The interaction between position and force trajectory tracking is illustrated. The best performance is obtained by using a novel, task space error feedback technique.
Szakaly, Z. F.↗
Nonlinear optimal control with tensors - Some computational issues
Some computational issues associated with the calcualtion of optimal feedback controls for nonlinear systems in a tensor setting are described. The specific issues addressed pertain to the combinatorial nature of the loading of the elements into tensors used to represent the system, cost, and feedback, and the subsequent calculations involving these elements. Particular attention is given to: the symmetric tensor algebra which is a natural setting for representing polynomials; the conversions between symmetric and nonsymmetric tensors; the general nature of the calculations required; and the solution equation for nonlinear optimal feedback control. It is concluded that nonlinear tensor feedback can improve performance both in terms of system responses and in terms of system stability region.
Osullivan, J. A.↗
The design of suboptimal linear time-varying systems.
Suboptimal feedback laws for control of linear time varying systems
Athans, M.↗
The design of suboptimal linear time-varying systems.
Suboptimal feedback laws for control of linear time varying systems with quadratic performance criteria
Athans, M.↗
Open-loop-feedback-optimal adaptive stochastic control of linear systems
This paper considers the suboptimal stochastic control of linear discrete-time dynamical systems with unknown or stochastically varying parameters. The suboptimal scheme is based upon the use of the open-loop-feedback-optimal method. The state and parameter estimates are generated by an extended Kalman filter algorithm. Numerical results for first-order systems are presented.
Ku, R.↗
Design of state-feedback controllers including sensitivity reduction, with applications to precision pointing
The design procedure of feedback controllers was described and the considerations for the selection of the design parameters were given. The frequency domain properties of single-input single-output systems using state feedback controllers are analyzed, and desirable phase and gain margin properties are demonstrated. Special consideration is given to the design of controllers for tracking systems, especially those designed to track polynomial commands. As an example, a controller was designed for a tracking telescope with a polynomial tracking requirement and some special features such as actuator saturation and multiple measurements, one of which is sampled. The resulting system has a tracking performance comparing favorably with a much more complicated digital aided tracker. The parameter sensitivity reduction was treated by considering the variable parameters as random variables. A performance index is defined as a weighted sum of the state and control convariances that sum from both the random system disturbances and the parameter uncertainties, and is minimized numerically by adjusting a set of free parameters.
Hadass, Z.↗
Biocybernetic system evaluates indices of operator engagement in automated task
A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.
Cerebral Cortex/physiology↗
Ultimate temperature stability of a magnetic refrigerator
In recent years there has been an interest in using adiabatic demagnetization refrigeration in space to cool bolometers to the 0.1-0.3 K temperature range. Two different demagnetization schemes have been proposed for such refrigerators. Both methods start the same way: an isothermal magnetization followed by an adiabatic demagnetization. Once the operating temperature is reached, the two methods differ. The first method uses feedback control to perform an isothermal demagnetization. As reported, this system is limited by the resolution of the analog-to-digital converter used. While the stability of this system is the best reported to date (0.5 mK at 200 mK for 14 h), it is several orders of magnitude worse than the theoretical limit. The second method uses a complete demagnetization and allows the temperature to drift up uncontrolled. This system has the disadvantage that the responsivity and noise of a bolometer will also drift, and so will require continuous recalibration. There is some concern that fluctuations in the temperature control system of the first method would adversely affect the bolometer performance by increasing the system noise. The purpose of this note is to present the ultimate stability limit of an isothermal demagnetization feedback control system.
Kittel, P.↗
Structural analysis and design of multivariable control systems: An algebraic approach
The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.
Tsay, Yih Tsong↗
System Finds Horizontal Location of Center of Gravity
An instrumentation system rapidly and repeatedly determines the horizontal location of the center of gravity of a laboratory vehicle that slides horizontally on three air bearings (see Figure 1). Typically, knowledge of the horizontal center-of-mass location of such a vehicle is needed in order to balance the vehicle properly for an experiment and/or to assess the dynamic behavior of the vehicle. The system includes a load cell above each air bearing, electronic circuits that generate digital readings of the weight on each load cell, and a computer equipped with software that processes the readings. The total weight and, hence, the mass of the vehicle are computed from the sum of the load-cell weight readings. Then the horizontal position of the center of gravity is calculated straightforwardly as the weighted sum of the known position vectors of the air bearings, the contribution of each bearing being proportional to the weight on that bearing. In the initial application for which this system was devised, the center- of-mass calculation is particularly simple because the air bearings are located at corners of an equilateral triangle. However, the system is not restricted to this simple geometry. The system acquires and processes weight readings at a rate of 800 Hz for each load cell. The total weight and the horizontal location of the center of gravity are updated at a rate of 800/3 approx. equals 267 Hz. In a typical application, a technician would use the center-of-mass output of this instrumentation system as a guide to the manual placement of small weights on the vehicle to shift the center of gravity to a desired horizontal position. Usually, the desired horizontal position is that of the geometric center. Alternatively, this instrumentation system could be used to provide position feedback for a control system that would cause weights to be shifted automatically (see Figure 2) in an effort to keep the center of gravity at the geometric center.
Johnston, Albert S.↗
Integration of an Autopilot for a Micro Air Vehicle
Two autopilots providing autonomous flight capabilities are presented herein. The first is the Pico-Pilot, demonstrated for the 12-inch size class of micro air vehicles. The second is the MicroPilot MP2028(sup g), where its integration into a 36-inch Zagi airframe (tailless, elevons only configuration) is investigated and is the main focus of the report. Analytical methods, which include the use of the Advanced Aircraft Analysis software from DARCorp, were used to determine the stability and control derivatives, which were then validated through wind tunnel experiments. From the aerodynamic data, the linear, perturbed equations of motion from steady-state flight conditions may be cast in terms of these derivatives. Using these linear equations, transfer functions for the control and navigation systems were developed and feedback control laws based on Proportional, Integral, and Derivative (PID) control design were developed to control the aircraft. The PID gains may then be programmed into the autopilot software and uploaded to the microprocessor of the autopilot. The Pico-Pilot system was flight tested and shown to be successful in navigating a 12-inch MAV through a course defined by a number of waypoints with a high degree of accuracy, and in 20 mph winds. The system, though, showed problems with control authority in the roll and pitch motion of the aircraft: causing oscillations in these directions, but the aircraft maintained its heading while following the prescribed course. Flight tests were performed in remote control mode to evaluate handling, adjust trim, and test data logging for the Zagi with integrated MP2028(sup g). Ground testing was performed to test GPS acquisition, data logging, and control response in autonomous mode. Technical difficulties and integration limitations with the autopilot prevented fully autonomous flight from taking place, but the integration methodologies developed for this autopilot are, in general, applicable for unmanned air vehicles within the 36-inch size class or larger that use a PID control based autopilot.
Platanitis, George↗
A PDE-based methodology for modeling, parameter estimation and feedback control in structural and structural acoustic systems
A problem of continued interest concerns the control of vibrations in a flexible structure and the related problem of reducing structure-borne noise in structural acoustic systems. In both cases, piezoceramic patches bonded to the structures have been successfully used as control actuators. Through the application of a controlling voltage, the patches can be used to reduce structural vibrations which in turn lead to methods for reducing structure-borne noise. A PDE-based methodology for modeling, estimating physical parameters, and implementing a feedback control scheme for problems of this type is discussed. While the illustrating example is a circular plate, the methodology is sufficiently general so as to be applicable in a variety of structural and structural acoustic systems.
Banks, H. T.↗
Quasi-modal vibration control by means of active control bearings
This paper investigates a design method of an active control bearing system with only velocity feedback. The study provides a new quasi-modal control method for a control system design of an active control bearing system in which feedback coefficients are determined on the basis of a modal analysis. Although the number of sensors and actuators is small, this quasi-modal control method produces a control effect close to an ideal modal control.
Nonami, K.↗
Feedback Control of Flight Speed to Reduce Unmanned Aerial System Noise
The aim of this initial study is to incorporate an acoustic metric into the flight control system of an unmanned aerial vehicle. This could be used to mitigate the noise impact of unmanned aerial systems operating near residential communities. To incorporate an acoustic metric into a pre-existing flight control system, two things are required: a source noise model, and an acoustic controller. An acoustic model was developed based on Gutin's work to estimate propeller noise. The flight control system was augmented with a controller to reduce propeller noise using feedback control of the commanded flight speed until an acoustic target was met. This control approach focuses on modifying flight speed only, with no perturbation to the trajectory. Multiple flight simulations were performed and the results showed that integrating an acoustic metric into the flight control system of an unmanned aerial system is possible.
Matthew B Galles↗
Filtering technique based on high-frequency plant modeling for high-gain control
This invention was an improvement in aircraft control systems that utilized feedback motion sensors to generate a signal to control the aircraft. The improvement consisted essentially of a complementary filter comprising a simplified model of the aircraft, a high pass filter, a low pass filter and a summing amplifier. The control signal was applied to the simplified model of the aircraft which attempted to compute the vehicle response to the signal. This computed response was then fed into the high pass filter to eliminate long term errors in the calculated response, with the result that a good estimate of the high frequency content of the aircraft motion was obtained. In order to obtain a good estimate of the low frequency content of the motion, a rate gyro signal was fed through the low pass filter that eliminates all of the offending noise.
Niessen, F. R.↗
Loop Shaping Control Design for a Supersonic Propulsion System Model Using Quantitative Feedback Theory (QFT) Specifications and Bounds
This paper covers the propulsion system component modeling and controls development of an integrated mixed compression inlet and turbojet engine that will be used for an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. Using previously created nonlinear component-level propulsion system models, a linear integrated propulsion system model and loop shaping control design have been developed. The design includes both inlet normal shock position control and jet engine rotor speed control for a potential supersonic commercial transport. A preliminary investigation of the impacts of the aero-elastic effects on the incoming flow field to the propulsion system are discussed, however, the focus here is on developing a methodology for the propulsion controls design that prevents unstart in the inlet and minimizes the thrust oscillation experienced by the vehicle. Quantitative Feedback Theory (QFT) specifications and bounds, and aspects of classical loop shaping are used in the control design process. Model uncertainty is incorporated in the design to address possible error in the system identification mapping of the nonlinear component models into the integrated linear model.
Connolly, Joseph W.↗