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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
NASA NTRS1988

Accurate positioning of long, flexible ARM's (Articulated Robotic Manipulator)

An articulated robotic manipulator (ARM) system is being designed for space applications. Work being done on a concept utilizing an infinitely stiff laser beam for position reference is summarized. The laser beam is projected along the segments of the ARM, and the position is sensed by the beam rider modules (BRM) mounted on the distal ends of the segments. The BRM concept is the heart of the system. It utilizes a combination of lateral displacements and rotational and distance measurement sensors. These determine the relative position of the two ends of the segments with respect to each other in six degrees of freedom. The BRM measurement devices contain microprocessor controlled data acquisition and active positioning components. An indirect adaptive controller is used to accurately control the position of the ARM.

Malachowski, Michael J.↗
NASA NTRS1990

Beam rider for an Articulated Robot Manipulator (ARM) accurate positioning of long flexible manipulators

Laser beam positioning and beam rider modules were incorporated into the long hollow flexible segment of an articulated robot manipulator (ARM). Using a single laser beam, the system determined the position of the distal ARM endtip, with millimetric precision, in six degrees of freedom, at distances of up to 10 meters. Preliminary designs, using space rated technology for the critical systems, of a two segmented physical ARM, with a single and a dual degree of freedom articulation, were developed, prototyped, and tested. To control the positioning of the physical ARM, an indirect adaptive controller, which used the mismatch between the position of the laser beam under static and dynamic conditions, was devised. To predict the behavior of the system and test the concept, a computer simulation model was constructed. A hierarchical artificially intelligent real time ADA operating system program structure was created. The software was designed for implementation on a dedicated VME bus based Intel 80386 administered parallel processing multi-tasking computer system.

Malachowski, M. J.↗
NASA NTRS1992

An evaluation of some strategies for vibration control of flexible rotors

There is evidence that the reliability of magnetic bearings has achieved an acceptable level in applications when high cost can be tolerated. This acceptability would be enhanced if the inherent capability of magnetic bearings as active control elements were fully used. The technological and commercial promise of magnetic bearings will be fulfilled only if attention is focussed on the control problems associated with their use. The open loop adaptive control algorithm provides an efficient method of controlling the vibration of rotors without the need of a prior knowledge of parameter values. It overcomes the disadvantages normally associated with open loop control while avoiding the problem of instability associated with closed loop control algorithms. The algorithm is conceptually satisfying because it uses the capability of magnetic bearings as fully active vibration control elements rather than limiting them to act as adjustable stiffness and damping elements, as is the case when they are used with local position and velocity feedback.

Burrows, C. R.↗
NASA NTRS1989

Structures cluster

The objective of this program is to develop technology needed for structural evaluation of alternative space construction concepts. Those concepts are as follows: interactive effects on dynamic performance of various environment and self-generated disturbance; new materials concepts, failure mechanisms, and non-destructive evaluation/failure detection; develop stable control algorithms and design effective combination of hierarchical and adaptive controls; and assess control-structure integrated performance and stability.

Datta, Subhendu K.↗
NASA NTRS2001

Cockpit Adaptive Automation and Pilot Performance

The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals were met or exceeded. The results of the research extended knowledge of automation-related performance decrements in pilots and demonstrated the positive effects of adaptive task allocation. In addition, several practical implications for cockpit automation design were drawn from the research conducted. A total of 12 articles deriving from the project were published.

Parasuraman, Raja↗
NASA NTRS2004

Introductory Remarks

Future vehicle designs will see a paradigm shift from: 1) Steady to the unsteady world (e.g. flow control, adaptive morphing); 2) Passive to active; 3) Rigid designs to exploitation of flexibility and adaptability; 4) Few discrete to numerous distributed (e.g. sensors, control surfaces); 5) To obtain a vehicle that is always at optimum performance. Therefore, future designs will be inherently multidisciplinary, and the greatest technical challenges and opportunities occur at the intersection of disciplines COMSAC appears to be a step towards enabling the future vision.

Tenney, Darrel R.↗
NASA NTRS2010

Data-Based Predictive Control with Multirate Prediction Step

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Barlow, Jonathan S.↗
NASA NTRS1990

System Identification for Nonlinear Control Using Neural Networks

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

Stengel, Robert F.↗
DOE OSTI2020

PC-RPL: Joint Control of Routing Topology and Transmission Power in Real Low-Power and Lossy Networks

We present PC-RPL , a transmission power-controlled IPv6 routing protocol for low-power and lossy wireless networks that significantly improves the end-to-end packet delivery performance under heavy traffic compared to the standard RPL. We show through actual design, implementation, and experiments that a multihop wireless network can achieve better throughput and routing stability when transmission power and routing topology are “jointly and adaptively” controlled. Our experiments show that the predominant “fixed and uniform” transmission power strategy with “link quality and hop distance”–based routing topology construction (i.e., RPL) loses significant bandwidth due to hidden terminal and load imbalance problems. We design an adaptive and distributed control mechanism for transmission power and routing topology, named PC-RPL , on top of the standard RPL routing protocol for hidden terminal mitigation and load balancing. We implement PC-RPL on real embedded devices and evaluate its performance on a 49-node multihop testbed. PC-RPL reduces total end-to-end packet losses by approximately sevenfold without increasing hop distance compared to RPL with the highest transmission power, resulting in 17% improvement in aggregate bandwidth and 64% improvement for the worst-case node by successfully alleviating both hidden terminal and load imbalance problems.

Computer Science↗
NASA NTRS1986

Modeling, simulation and control for a cryogenic fluid management facility, preliminary report

The synthesis of a control system for a cryogenic fluid management facility was studied. The severe demand for reliability as well as instrumentation and control unique to the Space Station environment are prime considerations. Realizing that the effective control system depends heavily on quantitative description of the facility dynamics, a methodology for process identification and parameter estimation is postulated. A block diagram of the associated control system is also produced. Finally, an on-line adaptive control strategy is developed utilizing optimization of the velocity form control parameters (proportional gains, integration and derivative time constants) in appropriate difference equations for direct digital control. Of special concern are the communications, software and hardware supporting interaction between the ground and orbital systems. It is visualized that specialist in the OSI/ISO utilizing the Ada programming language will influence further development, testing and validation of the simplistic models presented here for adaptation to the actual flight environment.

Turner, Max A.↗
NASA NTRS1993

Adaptive array antenna for satellite cellular and direct broadcast communications

Adaptive phased-array antennas provide cost-effective implementation of large, light weight apertures with high directivity and precise beamshape control. Adaptive self-calibration allows for relaxation of all mechanical tolerances across the aperture and electrical component tolerances, providing high performance with a low-cost, lightweight array, even in the presence of large physical distortions. Beam-shape is programmable and adaptable to changes in technical and operational requirements. Adaptive digital beam-forming eliminates uplink contention by allowing a single electronically steerable antenna to service a large number of receivers with beams which adaptively focus on one source while eliminating interference from others. A large, adaptively calibrated and fully programmable aperture can also provide precise beam shape control for power-efficient direct broadcast from space. Advanced adaptive digital beamforming technologies are described for: (1) electronic compensation of aperture distortion, (2) multiple receiver adaptive space-time processing, and (3) downlink beam-shape control. Cost considerations for space-based array applications are also discussed.

Horton, Charles R.↗
NASA NTRS1987

Position Control for Non-linear, Multiple-Link Robots

Several approaches to complicated control problem examined. Report surveys methods for controlling motion of robot manipulators. Applies to coupled, highly nonlinear multiple-link robots. Presents adaptive control technique based on discrete linear model of robot arm, obtained by linearizing nonlinear dynamical equations about nominal trajectory. Parameters of model calculated with adaptive parameter-identification algorithm. Based on system model, optimal control input computed using position and velocity feedback.

Seraji, H.↗
NASA NTRS1974

Environment-sensitive manipulator control

Environment-sensitive manipulator control (control systems capable of controlling manipulator motion based on real-time response to sensor data obtained during the attempt to perform a requested task) is described, and experiments on (1) proximity control in manipulation and (2) application of an articulated and adaptively controlled hand-to-environment-sensitive manipulator control are reported. The efficiency of such systems is determined by the separation of control and data processing functions between operator and computer.

Bejczy, A. K.↗
NASA NTRS1977

Set-point control of nonlinear systems

A method of nonlinear stochastic control is applied to the problem of providing set-point control. The procedure is illustrated for a nonlinear second-order plant. The controller design uses a variation of the 'multiple-model adaptive control' approach. Specific problems related to the design are investigated, including learning time and set-point accuracy dependence on the number of approximating models, chord versus tangent approximations, and the a priori Markov switching parameter values. Simulations are provided for different situations under various levels of measurement noise.

Vanlandingham, H. F.↗
NASA NTRS1981

Pulse control of single degree-of-freedom system

The possibility of using active control for structural and mechanical systems is examined. Open loop adaptive control of structural systems subjected to deterministic and stochastic excitations is considered by means of an algorithm for a single-degree-of-freedom oscillator. The algorithm is heuristic and requires continuous monitoring of the state variables, with a pulse control applied when some prespecified level of control is exceeded. The control algorithm is based on the principle that the gradual rhythmic increase of the structural response can be eliminated by applying a pulse of suitable magnitude in the proper direction, thereby avoiding the application of large forces over sustained periods of time. The optimum pulse magnitude is determined as the minimum rms response of the system. Application to linear and nonlinear systems, as well as in chatter suppression, are outlined.

Udwadia, F. E.↗
NASA NTRS1990

Exponentially Stabilizing Robot Control Laws

New class of exponentially stabilizing laws for joint-level control of robotic manipulators introduced. In case of set-point control, approach offers simplicity of proportion/derivative control architecture. In case of tracking control, approach provides several important alternatives to completed-torque method, as far as computational requirements and convergence. New control laws modified in simple fashion to obtain asymptotically stable adaptive control, when robot model and/or payload mass properties unknown.

Wen, John T.↗