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At least 199 records · Page 11

Stability robustness improvement using constrained optimization techniques

In a multiloop feedback control system, stability margin improvement by singular value shaping can be achieved by a noise adjustment procedure. A direct method for shaping singular value spectrum using constrained optimization technique is described. The design algorithm minimizes a standard LQG performance index while trying to satisfy minimum singular value constraints at the plant input, or output, or at both. Selected parameters of a stabilizing control law are used as the design variables. The capabilities of this method are demonstrated using a two input two output system representing a drone aircraft and its lateral attitude control system.

Mukhopadhyay, V.↗

De novo designed ice-binding proteins from twist-constrained helices

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure–activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure–activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.

Science & Technology - Other Topics↗

Use of the NLPQLP Sequential Quadratic Programming Algorithm to Solve Rotorcraft Aeromechanical Constrained Optimisation Problems

Optimization of the control vector, configuration and aerodynamic surface design potentially offers significant performance enhancement to rotorcraft systems. These analyses indicated that non-linear programming methods that solve a sequence of related quadratic-programming sub-problems could be used successfully to solve these problems. Accordingly, a license for one of the latest versions of Professor Schittkowski's very successful Sequential Quadratic Programming NLPQLP software was obtained and used to experiment and analyze typical optimization problems of the type encountered in various rotorcraft wind tunnel and flight tests. Emphasis was directed toward obtaining efficiency, robustness and speed in computation.

Use of the NLPQLP↗

Structural dynamic interaction with solar tracking control for evolutionary Space Station concepts

The sun tracking control system design of the Solar Alpha Rotary Joint (SARJ) and the interaction of the control system with the flexible structure of Space Station Freedom (SSF) evolutionary concepts are addressed. The significant components of the space station pertaining to the SARJ control are described and the tracking control system design is presented. Finite element models representing two evolutionary concepts, enhanced operations capability (EOC) and extended operations capability (XOC), are employed to evaluate the influence of low frequency flexible structure on the control system design and performance. The design variables of the control system are synthesized using a constrained optimization technique to meet design requirements, to provide a given level of control system stability margin, and to achieve the most responsive tracking performance. The resulting SARJ control system design and performance of the EOC and XOC configurations are presented and compared to those of the SSF configuration. Performance limitations caused by the low frequency of the dominant flexible mode are discussed.

Lim, Tae W.↗

Structural dynamic interaction with solar tracking control for evolutionary Space Station concepts

The paper addresses the sun tracking control system design of the Solar Alpha Rotary Joint (SARJ) and the interaction of the control system with the flexible structure of Space Station Freedom (SSF) evolutionary concepts. The significant components of the Space Station pertaining to the SARJ control are described, and the tracking control system design is presented. Finite element models representing two evolutionary concepts, Enhanced Operations Capability (EOC) and Extended Operations Capability (XOC), are employed to evaluate the influence of low frequency flexible structure on the control system design and performance. The design variables of the control system are synthesized using a constrained optimization technique to meet design requirements, to provide a given level of control system stability margin, and to achieve the most responsive tracking performance. The resulting SARJ control system design and performance of the EOC and XOC configurations are presented and compared to those of the SSF configuration.

Lim, Tae W.↗

A Typing Discipline for High-Assurance Control Systems

This poster describes a typing discipline for high-assurance industrial systems based on three novel type systems. The first type system, information flow control (IFC), controls the flow of data through the system. The second system, dependent session types, restricts messages exchanged during the execution of a communication protocol to avoid dangerous states. The third system uses dimensional analysis to avoid subtle bugs that adversaries can exploit to cause the system to enter a dangerous state. This poster describes how a combination of these approaches can prevent sophisticated cyber attacks, such as the infamous Stuxnet incident, from occurring. In addition, we provide experimental evidence to support the claim that these approaches can be applied in control systems that are resource-constrained.

42 - ENGINEERING↗

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robust on-off pulse control of flexible space vehicles

The on-off reaction jet control system is often used for attitude and orbital maneuvering of various spacecraft. Future space vehicles such as the orbital transfer vehicles, orbital maneuvering vehicles, and space station will extensively use reaction jets for orbital maneuvering and attitude stabilization. The proposed robust fuel- and time-optimal control algorithm is used for a three-mass spacing model of flexible spacecraft. A fuel-efficient on-off control logic is developed for robust rest-to-rest maneuver of a flexible vehicle with minimum excitation of structural modes. The first part of this report is concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated and solved. The second part of this report deals with obtaining parameter insensitive fuel- and time- optimal control inputs by solving a constrained optimization problem subject to robustness constraints. It is shown that sensitivity to modeling errors can be significantly reduced by the proposed, robustified open-loop control approach. The final part of this report deals with sliding mode control design for uncertain flexible structures. The benchmark problem of a flexible structure is used as an example for the feedback sliding mode controller design with bounded control inputs and robustness to parameter variations is investigated.

Wie, Bong↗

Multiplexed Predictive Control of a Large Commercial Turbofan Engine

Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

Richter, hanz↗

Controlling state explosion during automatic verification of delay-insensitive and delay-constrained VLSI systems using the POM verifier

Delay-insensitive VLSI systems have a certain appeal on the ground due to difficulties with clocks; they are even more attractive in space. We answer the question, is it possible to control state explosion arising from various sources during automatic verification (model checking) of delay-insensitive systems? State explosion due to concurrency is handled by introducing a partial-order representation for systems, and defining system correctness as a simple relation between two partial orders on the same set of system events (a graph problem). State explosion due to nondeterminism (chiefly arbitration) is handled when the system to be verified has a clean, finite recurrence structure. Backwards branching is a further optimization. The heart of this approach is the ability, during model checking, to discover a compact finite presentation of the verified system without prior composition of system components. The fully-implemented POM verification system has polynomial space and time performance on traditional asynchronous-circuit benchmarks that are exponential in space and time for other verification systems. We also sketch the generalization of this approach to handle delay-constrained VLSI systems.

Probst, D.↗

Some effects of digital sampling on orbiter flight control system operation

An entry dynamic stability ground test of the OV102 Space Shuttle Orbiter revealed some small amplitude oscillatory output of the flight control system which could have constrained flight of the STS-1 mission. These limit-cycle-type outputs were attributed to a combination of rigid body motion of the Orbiter on its landing gear and some interesting effects of its digital flight control system. These effects included frequency aliasing and phenomena associated with digital quantitization of low amplitude sensor signals. The digital effects suggest significant improvements possible in future designs.

Murray, S. V.↗

Development of Methodologies for IV and V of Neural Networks

Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

Taylor, Brian↗

Distributed Optimization

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Macready, William↗

JWST Wavefront Control Toolbox

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

Shin, Shahram Ron↗

Low cost spacecraft computers: Oxymoron or future trend?

Over the last few decades, application of current terrestrial computer technology in embedded spacecraft control systems has been expensive and wrought with many technical challenges. These challenges have centered on overcoming the extreme environmental constraints (protons, neutrons, gamma radiation, cosmic rays, temperature, vibration, etc.) that often preclude direct use of commercial off-the-shelf computer technology. Reliability, fault tolerance and power have also greatly constrained the selection of spacecraft control system computers. More recently, new constraints are being felt, cost and mass in particular, that have again narrowed the degrees of freedom spacecraft designers once enjoyed. This paper discusses these challenges, how they were previously overcome, how future trends in commercial computer technology will simplify (or hinder) selection of computer technology for spacecraft control applications, and what spacecraft electronic system designers can do now to circumvent them.

Manning, Robert M.↗

A safe reinforcement learning algorithm for supervisory control of power plants

Traditional control theory-based methods require tailored engineering for each system and constant fine-tuning. In power plant control, one often needs to obtain a precise representation of the system dynamics and carefully design the control scheme accordingly. Model-free Reinforcement learning (RL) has emerged as a promising solution for control tasks due to its ability to learn from trial-and-error interactions with the environment. It eliminates the need for explicitly modeling the environment’s dynamics, which is potentially inaccurate. However, the direct imposition of state constraints in power plant control raises challenges for standard RL methods. To address this, we propose a chance-constrained RL algorithm based on Proximal Policy Optimization for supervisory control. Our method employs Lagrangian relaxation to convert the constrained optimization problem into an unconstrained objective, where trainable Lagrange multipliers enforce the state constraints. In conclusion, our approach achieves the smallest distance of violation and violation rate in a load-follow maneuver for an advanced Nuclear Power Plant design.

constrained optimization↗

Integration of the Shuttle RMS/CBM Positioning Virtual Environment Simulation

Constructing the International Space Station, or other structures, in space presents a number of problems. In particular, payload restrictions for the Space Shuttle and other launch mechanisms prohibit assembly of large space-based structures on Earth. Instead, a number of smaller modules must be boosted into orbit separately and then assembled to form the final structure. The assembly process is difficult, as docking interfaces such as Common Berthing Mechanisms (CBMS) must be precisely positioned relative to each other to be within the "capture envelope" (approximately +/- 1 inch and +/- 0.3 degrees from the nominal position) and attach properly. In the case of the Space Station, the docking mechanisms are to be positioned robotically by an astronaut using the 55-foot-long Remote Manipulator System (RMS) robot arm. Unfortunately, direct visual or video observation of the placement process is difficult or impossible in many scenarios. One method that has been tested for aligning the CBMs uses a boresighted camera mounted on one CBM to view a standard target on the opposing CBM. While this method might be sufficient to achieve proper positioning with considerable effort, it does not provide a high level of confidence that the mechanisms have been placed within capture range of each other. It also does nothing to address the risk of inadvertent contact between the CBMS, which could result in RMS control software errors. In general, constraining the operator to a single viewpoint with few, if any, depth cues makes the task much more difficult than it would be if the target could be viewed in three-dimensional space from various viewpoints. The actual work area could be viewed by an astronaut during EVA; however, it would be extremely impractical to have an astronaut control the RMS while spacewalking. On the other hand, a view of the RMS and CBMs to be positioned in a virtual environment aboard the Space Shuttle orbiter or Space Station could provide similar benefits more safely and conveniently with little additional cost. In order to render and view the RMS and CBMs in a virtual world, the position and orientation of the end effector in three-dimensional space must be known with a high degree of accuracy. A precision video alignment sensor has been developed which can determine the position and orientation of the controlled element relative to the target CBM within approximately one-sixteenth inch and 0.07 angular degrees. Such a sensor could replace or augment the boresighted camera mentioned above. The computer system used to render the virtual world and the position tracking systems which might be used to monitor the user's movements (in order to adjust the viewpoint in virtual space) are small enough to carry to orbit. Thus, such a system would be feasible for use in constructing structures in space.

Dumas, Joseph D.↗