Research on the design of adaptive control systems, volume 2 Final report
Satellite tracking, attitude control, and adaptive control systems
ADAPTIVE CONTROL SYSTEM↗
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Adaptive control applied to Space Station attitude control system
This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.
Lam, Quang M.↗
Dual-arm manipulators with adaptive control
The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.
Seraji, Homayoun↗
Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle
This paper focuses on the analysis and tuning of a controller based on the Adaptive Control Technology for Safe Flight (ACTS) architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller s ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft s state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.
Crespo, Luis G.↗
Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control
Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.
Kim, Kilsoo↗
Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems
The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.
Athans, M.↗
The dual momentum control device for large space systems - An example of distributed system adaptive control
One area in which large space systems require new technology is attitude control. The paper presents an adaptive control philosophy applicable to the control of distributed systems. An adaptive control system is described for stabilization of the flexible modes of a spinning ring. The system consists of a modal decomposition and identification subsystem, a gain adjustment subsystem, and a feedback control subsystem. Simulations are presented illustrating the adaptive capability of the system. The adaptive controller did produce stable results by quickly identifying the parameter differences and adjusting the feedback controller gains.
Montgomery, R. C.↗
Adaptive control with an expert system based supervisory level
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.
Sullivan, Gerald A.↗
Adaptive control system having hedge unit and related apparatus and methods
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Johnson, Eric Norman↗
Adaptive control system having hedge unit and related apparatus and methods
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Johnson, Eric Norman↗
Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification
This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.
Adaptive Contro↗
Disturbance Accommodating Adaptive Control with Application to Wind Turbines
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Frost, Susan↗
Computational issue in the analysis of adaptive control systems
Adaptive systems under slow parameter adaption can be analyzed by the method of averaging. This provides a means to assess stability (and instability) properties of most adaptive systems, either continuous-time or (more importantly for practice) discrete-time, as well as providing an estimate of the region of attraction. Although the method of averaging is conceptually straightforward, even simple examples are well beyond hand calculations. Specific software tools are proposed which can provide the basis for user-friendly environment to perform the necessary computations involved in the averaging analysis.
Kosut, Robert L.↗
Reduced order adaptive controller studies
The use of a reduced-order adaptive controller, can arise from a desire to reduce control complexity with a commensurate reduction in controller sensitivity or from necessity in an attempt to use a finite dimensional controller on an infinite dimensional system. An interest in developing adaptive controllers for flexible structures by application of existing lumped-parameter system (LPS) adaptive controller strategies to truncated expansion descriptions of the distributed parameter system (DPS) behavior of flexible structures has led to two qualitative descriptions of the misbehavior of reduced-order adaptive controllers. A summary is provided of these interpretations of the additional difficulties facing reduced-order adaptive controllers, which are bypassed by exact-order adaptive controllers. A test problem, which initializes attempts to quantify the qualitative insights, is also formulated.
Johnson, C. R., Jr.↗
Control effort associated with model reference adaptive control for vibration damping
The performance of Model Reference Adaptive Control (MRAC) is studied in numerical simulations with the objective of understanding the effects of differences between the plant and the reference model. MRAC is applied to two structural systems with adjustable error between the reference model and the actual plant. Performance indices relating to control effort and response characteristics are monitored in order to determine what effects small errors have on the control effort and performance of the two systems. It is shown that reasonable amounts of error in the reference model can cause dramatic increases in both the control effort and response magnitude (as measured by energy integrals) of the plant.
Messer, Richard Scott↗
Research on the design of adaptive control systems, volume 1 Final report
Adaptive control systems - combined optimization and adaptive control, analysis-synthesis and passive adaptive systems, learning systems, and measurement adaptive systems
LEARNING SYSTEM↗
Analytical and experimental study of control effort associated with model reference adaptive control
Numerical simulation results presently obtained for the performance of model reference adaptive control (MRAC) are experimentally verified, with a view to accounting for differences between the plant and the reference model after the control function has been brought to bear. MRAC is both experimentally and analytically applied to a single-degree-of-freedom system, as well as analytically to a MIMO system having controlled differences between the reference model and the plant. The control effort is noted to be sensitive to differences between the plant and the reference model.
Messer, R. S.↗
Experimental investigation of adaptive control of a parallel manipulator
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
Nguyen, Charles C.↗