System determination from noisy measurements.
Control system identification for noise corrupted input/output data, using algorithmic approach and iteration procedure
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Control system identification for noise corrupted input/output data, using algorithmic approach and iteration procedure
Analysis and synthesis tools are developed to improved 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; ft is easier for real-time implementations in storage and computational effort; where system identification is required, the spline function requires fewer experiments, namely four experiments; and initial startup estimator transients are eliminated. 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.
An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.
An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.
A unified approach is presented for deriving a large class of new and previously known time- and order-recursive least-squares algorithms with systolic array architectures, suitable for high-throughput-rate and VLSI implementations of space-time filtering and system identification problems. The geometrical derivation given is unique in that no assumption is made concerning the rank of the sample data correlation matrix. This method utilizes and extends the concept of oblique projections, as used previously in the derivations of the least-squares lattice algorithms. Exponentially weighted least-squares criteria are considered for both sliding and growing memory.
A multi-input/output random vibration control algorithm was developed based on system identification concepts derived from random vibration spectral analysis theory. The unique features of the algorithm are: (1) the number of input excitors and the number of output control responses need not be identical; (2) the system inverse response matrix is obtained directly from the input/output spectral matrix; and (3) the system inverse response matrix is updated every control loop cycle to accommodate system amplitude nonlinearities. A laboratory demonstration case of two imputs with three outputs is presented to demonstrate the system capabilities.
Good progress is being made in several major areas. These include eddy current modelling and analysis, design optimization methods, wind tunnel Magnetic Suspension and Balance Systems (MSBS), payload pointing and vibration isolation systems, and system identification. In addition, another successful International Symposium has been completed, with the Proceedings being printed at the time of writing. These activities continue current work under this Grant and extend previous work on magnetic suspension systems and devices in the Guidance and Control Branch and will permit the demonstration of several new developments in the field of magnetic suspension technology.
Predictive controllers have found applications in a wide range of industrial processes. Two types of such controllers are generalized predictive control and deadbeat control. Recently, deadbeat control has been augmented to include an extended horizon. This modification, named deadbeat predictive control, retains the advantage of guaranteed stability and offers a novel way of control weighting. This paper presents an application of both predictive control techniques to vibration suppression of plate modes. Several system identification routines are presented. Both algorithms are outlined and shown to be useful in the suppression of plate vibrations. Experimental results are given and the algorithms are shown to be applicable to non- minimal phase systems.
System identification techniques in common use for extracting stability derivatives from flight test data have been adapted for application to data obtained from aeroelastically-scaled flutter models flown in a wind tunnel on a cable mount system. The concept has been applied with reasonable success to data from rigid models of a Space Shuttle Orbiter and a fighter tested in the NASA Langley transonic dynamics tunnel. Further application of this technique should permit extraction of derivatives that include scaled flexibility effects, thereby obtaining additional information from the testing of expensive flutter models.
The Mini-Mast testbed is a 20 m generic truss highly representative of future deployable trusses for space applications. It is fully instrumented for system identification and active vibrations control experiments and is used as a ground testbed at NASA-Langley. The facility has actuators and feedback sensors linked via fiber optic cables to the Advanced Real Time Simulation (ARTS) system, where user defined control laws are incorporated into generic controls software. The object of the facility is to conduct comprehensive active vibration control experiments on a dynamically realistic large space structure. A primary goal is to understand the practical effects of simplifying theoretical assumptions. This User's Guide describes the hardware and its primary components, the dynamic characteristics of the test article, the control law implementation process, and the necessary safeguards employed to protect the test article. Suggestions for a strawman controls experiment are also included.
This paper presents a formulation for identification of linear multivariable systems from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identification, by extension of the repetition domain concept to include shifting time intervals. This contrasts existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate the proposed method.
This volume contains a compilation of written versions of papers presented at the Eleventh Annual Conference on Manual Control in a meeting held at NASA-Ames Research Center, May 21-23, 1975. Five main topics were discussed during this three-day conference. These were covered in sessions on Concurrent Tasks, Physiological Systems, Controls and Displays, Performance/Workload Evaluation, and System Identification. Forty-nine papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile and remote control systems.
NASA is interested in developing technology that leads to more routine, safe, and affordable access to space. Access to space using airbreathing propulsion systems has potential to meet these objectives based on Airbreathing Access to Space (AAS) system studies. To this end, the NASA Fundamental Aeronautics Program (FAP) Hypersonic Project is conducting fundamental research on a Turbine Based Combined Cycle (TBCC) propulsion system. The TBCC being studied considers a dual flow-path inlet system. One flow-path includes variable geometry to regulate airflow to a turbine engine cycle. The turbine cycle provides propulsion from take-off to supersonic flight. The second flow-path supports a dual-mode scramjet (DMSJ) cycle which would be initiated at supersonic speed to further accelerate the vehicle to hypersonic speed. For a TBCC propulsion system to accelerate a vehicle from supersonic to hypersonic speed, a critical enabling technology is the ability to safely and effectively transition from the turbine to the DMSJ-referred to as mode transition. To experimentally test methods of mode transition, a Combined Cycle Engine (CCE) Large-scale Inlet testbed was designed with two flow paths-a low speed flow-path sized for a turbine cycle and a high speed flow-path designed for a DMSJ. This testbed system is identified as the CCE Large-Scale Inlet for Mode Transition studies (CCE-LIMX). The test plan for the CCE-LIMX in the NASA Glenn Research Center (GRC) 10- by 10-ft Supersonic Wind Tunnel (10x10 SWT) is segmented into multiple phases. The first phase is a matrix of inlet characterization (IC) tests to evaluate the inlet performance and establish the mode transition schedule. The second phase is a matrix of dynamic system identification (SysID) experiments designed to support closed-loop control development at mode transition schedule operating points for the CCE-LIMX. The third phase includes a direct demonstration of controlled mode transition using a closed loop control system developed with the data obtained from the first two phases. Plans for a fourth phase include mode transition experiments with a turbine engine. This paper, focusing on the first two phases of experiments, presents developed operational and analysis tools for streamlined testing and data reduction procedures.
This paper describes our efforts in structural control experiments for a flexible precision structure using both passive and active control. Specifically, a layered structural control approach utilizing passive viscous dampers, colocated and noncolocated active control is used. The passive dampers and active colocated control loops are used to enhance stability and robustness and the noncolocated multivariable controller is designed with respect to a partially controlled structure to further improve the performance. Our approach to the multivariable design problem requires not only a state space model description of the plant, but also an accompanying uncertainty model. To support the multivariable robust control design development, a significant effort in system identification was undertaken. The process of identification and identified results are discussed. Noncolocated controllers are designed using the H(infinity)/mu-synthesis methodology. The order of the controller is typically large, hence, model reduction is performed for practical digital implementation on a real-time control system developed at JPL. Finally, experimental results are presented and some of lessons are discussed.
This paper presents a process of design and flight-test validation and flying qualities evaluation of a flight control system for a rotorcraft-based unmanned aerial vehicle (RUAV). The keystone of this process is an accurate flight-dynamic model of the aircraft, derived by using system identification modeling. The model captures the most relevant dynamic features of our unmanned rotorcraft, and explicitly accounts for the presence of a stabilizer bar. Using the identified model we were able to determine the performance margins of our original control system and identify limiting factors. The performance limitations were addressed and the attitude control system was 0ptimize.d for different three performance levels: slow, medium, fast. The optimized control laws will be implemented in our RUAV. We will first determine the validity of our control design approach by flight test validating our optimized controllers. Subsequently, we will fly a series of maneuvers with the three optimized controllers to determine the level of flying qualities that can be attained. The outcome enable us to draw important conclusions on the flying qualities requirements for small-scale RUAVs.
High performance aircraft are, by their very nature, often required to undergo maneuvers involving high angles of attack. Under these conditions unsteady vortices emanating from the wing and the fuselage will impinge on the twin fins (required for directional stability) causing excessive buffet loads, in some circumstances, to be applied to the aircraft. These loads result in oscillatory stresses, which may cause significant amounts of fatigue damage. Active control is a possible solution to this important problem. A full-scale test was carried out on an F/A-18 fuselage and fins using piezoceramic actuators to control the vibrations. Buffet loads were simulated using very powerful electromagnetic shakers. The first phase of this test was concerned with the open loop system identification whereas the second stage involved implementing linear time invariant control laws. This paper looks at some of the problems encountered as well as the corresponding solutions and some results. It is expected that flight trials of a similar control system to alleviate buffet will occur as early as 2001.
A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.
Recent work on structural identification and large-angle maneuvers with vibration suppression was presented. The recent work has sought to balance structural and controls analysis activities by involving the analysts directly in the validation and experimental aspects of the research. Some new sensing, actuation, system identification, and control concepts were successfully implemented. An overview of these results is given.