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Optimality of totally singular vector controls governing dynamical systems and extension of Green theory approach to higher dimensions to evaluate optimality of such controls
Landing humans on Mars comes with many challenges, including the execution of a safe and precise entry, descent, and landing (EDL) sequence. Various NASA studies have shown that there are a variety of EDL guidance methods that potentially offer solutions to the human-scale EDL precision landing problem and work is ongoing to assess new and novel methods. As part of these ongoing studies, a dual-quaternion-based six degree-of-freedom guidance algorithm was implemented in the Program to Optimize Simulated Trajectories II (POST2), a NASA-and industry-standard spacecraft trajectory and vehicle design tool. This algorithm considers both translational and rotational dynamics and casts the trajectory optimization problem as a quadratically constrained quadratic program (QCQP) with various constraints at discrete nodes throughout the trajectory. The QCQP problem is solved via an alternating direction method of multipliers (ADMM) approach, and the output is a discretized optimal trajectory. The guidance is applied to a NASA reference human-scale Mars EDL system, and results are compared and discussed.
Landing humans on Mars comes with many challenges, including the execution of a safe and precise entry, descent, and landing (EDL) sequence. Various NASA studies have shown that there are a variety of EDL guidance methods that potentially offer solutions to the human-scale EDL precision landing problem and work is ongoing to assess new and novel methods. As part of these ongoing studies, a dual-quaternion-based six degree-of-freedom guidance algorithm was implemented in the Program to Optimize Simulated Trajectories II (POST2), a NASA-and industry-standard spacecraft trajectory and vehicle design tool. This algorithm considers both translational and rotational dynamics and casts the trajectory optimization problem as a quadratically constrained quadratic program (QCQP) with various constraints at discrete nodes throughout the trajectory. The QCQP problem is solved via an alternating direction method of multipliers (ADMM) approach, and the output is a discretized optimal trajectory. The guidance is applied to a NASA reference human-scale Mars EDL system, and results are compared and discussed.
Matrix Riccati equations for optimization in control theory
An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.
An approach to the systematic optimization of a large-scale dynamic model is proposed which consists in parameterization of simulation results as response surfaces. The optimization procedure is carried out using a second-order orthogonal design. The approach proposed here is demonstrated by an example involving the shock-initiated ignition of methane.
In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.
The potential importance of space telemanipulator systems is reviewed, along with past studies of master-slave manipulation using a generalized force reflecting master arm. Problems concerning their dynamic interaction with the human operator have been revealed in the use of these systems, with marked differences between 1-g and simulated weightless conditions. A study is outlined to investigate the optimization of the man machine dynamics of master-slave manipulation, and a set of specifications is determined for the apparatus necessary to perform this investigation. This apparatus is a one degree of freedom force reflecting hand controller with closed loop servo control which enables it to simulate arbitrary dynamic properties to high bandwidth. Design of the complete system and its performance is discussed. Finally, the experimental adjustment of the hand controller dynamics for smooth manual control performance with good operator force perception is described, resulting in low inertia, viscously damped hand controller dynamics.
As computational fluid dynamics techniques and tools become widely accepted for realworld practice today, it is intriguing to ask: what areas can it be utilized to its potential in the future. Some promising areas include design optimization and exploration of fluid dynamics phenomena (the concept of numerical wind tunnel), in which both have the common feature where some parameters are varied repeatedly and the computation can be costly. We are especially interested in the need for an accurate and efficient approach for handling these applications: (1) capturing complex nonlinear dynamics inherent in a system under consideration and (2) versatility (robustness) to encompass a range of parametric variations. In our previous paper, we proposed to use first-order Taylor expansion collected at numerous sampling points along a trajectory and assembled together via nonlinear weighting functions. The validity and performance of this approach was demonstrated for a number of problems with a vastly different input functions. In this study, we are especially interested in enhancing the method's accuracy; we extend it to include the second-orer Taylor expansion, which however requires a complicated evaluation of Hessian matrices for a system of equations, like in fluid dynamics. We propose a method to avoid these Hessian matrices, while maintaining the accuracy. Results based on the method are presented to confirm its validity.
State of randomly excited dynamical system estimated from noise measurements having finite duration, and optimal linear filter synthesized from conditional probability theory
A computer simulation was conducted to investigate the effects of both linear and parabolic tooth profile modification on the dynamic response of low-contact-ratio spur gears. The effect of the total amount of modification and the length of the modification zone were studied at various loads and speeds to find the optimal profile modification for minimal dynamic loading. Design charts consisting of normalized maximum dynamic load curves were generated for gear systems operated at various loads and with different tooth profile modification. An optimum profile modification can be determined from these design charts to minimize the dynamic loads of spur gear systems.
A computer simulation was conducted to investigate the effects of both linear and parabolic tooth profile modification on the dynamic response of low-contact-ratio spur gears. The effect of the total amount of modification and the length of the modification zone were studied at various loads and speeds to find the optimal profile modification for minimal dynamic loading. Design charts consisting of normalized maximum dynamic load curves were generated for gear systems operated at various loads and with different tooth profile modification. An optimum profile modification can be determined from these design charts to minimize the dynamic loads of spur gear systems.
This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general-purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of global quantities (stiffness, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic designs are performed at a global level and the structural design is carried out at a detailed level with considerable dialog and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several examples.
Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.
The dynamic response of a fiber optic Bragg grating to mechanical vibrations is examined both theoretically and experimentally. The theoretical expressions describing the consequences of changes in the grating's reflection spectrum are derived for partially coherent beams in an interferometer. The analysis is given in terms of the dominant wavelength, optical bandwidth, and optical path difference of the interfering signals. Changes in the reflection spectrum caused by a periodic stretching and compression of the grating were experimentally measured using an unbalanced Michelson interferometer, a Michelson interferometer with a non-zero optical path difference. The interferometer's sensitivity to changes in dominant wavelength of the interfering beams was measured as a function of interferometer unbalance and was compared to theoretical predictions. The theoretical analysis enables the user to determine the optimum performance for an unbalanced interferometer.
We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.
Work under this grant was carried out by the author and by a graduate research assistant. An instrumented bicycle ergometer was implemented focusing on the stated objective: to estimate the forces exerted by each muscle of the feet, calf, and thigh of an individual while bicycling. The sensors used were light and compact. These were probes to measure muscle EMG activity, miniature accelerometers, miniature load sensors, and small encoders to measure angular positions of the pedal. A methodology was developed and implemented to completely describe the kinematics of the limbs using data from the sensors. This work has been published as a Master's Thesis by the Graduate student supported by the grant. The instrumented ergometer along with the sensors and instrumentation were tested during a KC-135 Zero-Gravity flight in July, 1994. A complete description of the system and the tests performed have been published as a report submitted to NASA Johnson Space Center. The data collected during the KC-135 flight is currently being processed so that a kinematic description of the bicycling experiment will be soon determined. A methodology to estimate the muscle forces has been formulated based on previous work. The methodology involves the use of optimization concepts so that the individual muscle forces that represent variables in dynamic equations of motion may be estimated. Optimization of a criteria (goal) function such as minimization of energy will be used along with constraint equations defined by rigid body equations of motion. Use of optimization principles is necessary, because the equations of motion alone constitute an indeterminate system of equations with respect to the large amount of muscle forces which constitute the variables in these equations. The number of variables is reduced somewhat by using forces measured by the load cells installed on the pedal. These load cells measure pressure and shear forces on the foot. The author and his collaborators at NASA and at the University of Alabama, Tuscaloosa, are continuing the work of reducing the experimental data from the KC-135 flight, and the implementation of the optimization methods to estimate muscle forces. As soon as results from these efforts are available, they will be published in reputable journals. Results of this work will impact studies addressing bone density loss and development of countermeasures to minimize bone loss in zero gravity conditions. By analyzing muscle forces on Earth and in Space during exercise, scientists could eventually formulate new exercises and machines to help maintain bone density. On Earth, this work will impact studies concerning arthritis, and will provide the means to study possible exercise countermeasures to minimize arthritis problems.
This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.