Optimal control and Galois theory
Zelikin, M I; Kiselev, D D; Lokutsievskiy, L V
2013-11-30
An important role is played in the solution of a class of optimal control problems by a certain special polynomial of degree 2(n−1) with integer coefficients. The linear independence of a family of k roots of this polynomial over the field Q implies the existence of a solution of the original problem with optimal control in the form of an irrational winding of a k-dimensional Clifford torus, which is passed in finite time. In the paper, we prove that for n≤15 one can take an arbitrary positive integer not exceeding [n/2] for k. The apparatus developed in the paper is applied to the systems of Chebyshev-Hermite polynomials and generalized Chebyshev-Laguerre polynomials. It is proved that for such polynomials of degree 2m every subsystem of [(m+1)/2] roots with pairwise distinct squares is linearly independent over the field Q. Bibliography: 11 titles.
Aerodynamic shape optimization using control theory
NASA Technical Reports Server (NTRS)
Reuther, James
1996-01-01
Aerodynamic shape design has long persisted as a difficult scientific challenge due its highly nonlinear flow physics and daunting geometric complexity. However, with the emergence of Computational Fluid Dynamics (CFD) it has become possible to make accurate predictions of flows which are not dominated by viscous effects. It is thus worthwhile to explore the extension of CFD methods for flow analysis to the treatment of aerodynamic shape design. Two new aerodynamic shape design methods are developed which combine existing CFD technology, optimal control theory, and numerical optimization techniques. Flow analysis methods for the potential flow equation and the Euler equations form the basis of the two respective design methods. In each case, optimal control theory is used to derive the adjoint differential equations, the solution of which provides the necessary gradient information to a numerical optimization method much more efficiently then by conventional finite differencing. Each technique uses a quasi-Newton numerical optimization algorithm to drive an aerodynamic objective function toward a minimum. An analytic grid perturbation method is developed to modify body fitted meshes to accommodate shape changes during the design process. Both Hicks-Henne perturbation functions and B-spline control points are explored as suitable design variables. The new methods prove to be computationally efficient and robust, and can be used for practical airfoil design including geometric and aerodynamic constraints. Objective functions are chosen to allow both inverse design to a target pressure distribution and wave drag minimization. Several design cases are presented for each method illustrating its practicality and efficiency. These include non-lifting and lifting airfoils operating at both subsonic and transonic conditions.
Helicopter trajectory planning using optimal control theory
NASA Technical Reports Server (NTRS)
Menon, P. K. A.; Cheng, V. H. L.; Kim, E.
1988-01-01
A methodology for optimal trajectory planning, useful in the nap-of-the-earth guidance of helicopters, is presented. This approach uses an adjoint-control transformation along with a one-dimensional search scheme for generating the optimal trajectories. In addition to being useful for helicopter nap-of-the-earth guidance, the trajectory planning solution is of interest in several other contexts, such as robotic vehicle guidance and terrain-following guidance for cruise missiles and aircraft. A distinguishing feature of the present research is that the terrain constraint and the threat envelopes are incorporated in the equations of motion. Second-order necessary conditions are examined.
Robust control systems design by H-infinity optimization theory
NASA Technical Reports Server (NTRS)
Chang, B. C.; Li, X. P.; Banda, S. S.; Yeh, H. H.
1991-01-01
In this paper, step-by-step procedures of applying the H-infinity theory to robust control systems design are given. The objective of the paper is to eliminate the possible difficulties a control engineer may encounter in applying H-infinity control theory and to clear up some misconceptions about H-infinity theory like high-gain controller and numerical obstacles, etc. An efficient algorithm is used to compute the optimal H-infinity norm. The Glover and Doyle (1988) controller formulas are slightly modified and used to construct an optimal controller without any numerical difficulties.
OPTIMAL CONTROL THEORY FOR SUSTAINABLE ENVIRONMENTAL MANAGEMENT
Sustainable management of the human and natural systems, taking into account their interactions, has become paramount. To achieve this complex multidisciplinary objective, systems theory based techniques prove useful. The proposed work is a step in that direction. Taking a food w...
Improving Vortex Models via Optimal Control Theory
NASA Astrophysics Data System (ADS)
Hemati, Maziar; Eldredge, Jeff; Speyer, Jason
2012-11-01
Flapping wing kinematics, common in biological flight, can allow for agile flight maneuvers. On the other hand, we currently lack sufficiently accurate low-order models that enable such agility in man-made micro air vehicles. Low-order point vortex models have had reasonable success in predicting the qualitative behavior of the aerodynamic forces resulting from such maneuvers. However, these models tend to over-predict the force response when compared to experiments and high-fidelity simulations, in part because they neglect small excursions of separation from the wing's edges. In the present study, we formulate a constrained minimization problem which allows us to relax the usual edge regularity conditions in favor of empirical determination of vortex strengths. The optimal vortex strengths are determined by minimizing the error with respect to empirical force data, while the vortex positions are constrained to evolve according to the impulse matching model developed in previous work. We consider a flat plate undergoing various canonical maneuvers. The optimized model leads to force predictions remarkably close to the empirical data. Additionally, we compare the optimized and original models in an effort to distill appropriate edge conditions for unsteady maneuvers.
Combining Optimal Control Theory and Molecular Dynamics for Protein Folding
Arkun, Yaman; Gur, Mert
2012-01-01
A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the atoms. In turn, MD simulation provides an all-atom conformation whose positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization - MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages. PMID:22238629
Theory of Optimal Phase-Unlocked Pump-Dump Control
NASA Astrophysics Data System (ADS)
Yan, Yijing
1997-04-01
A novel theory of optimal control via a pair of phase-unlocked pump-dump fields is developed. We first derive a pair of coupled nonlinear control equations for mixed or dissipative quantum systems in the strong response regime. These equations should be solved iteratively, resulting in a locally optimal pair of fields that are however usually too complicated to be realizable. To facilitate this problem, we further develop a hierarchy of reduction and arrive at a variety of simplified control equation pairs. In the weak response regime, we obtain a pair of coupled semi-linear control equations in which the globally optimal pump field at any given pump field, or vice verse, can be evaluated in a non-iterative manor. However, it still requires an iterative solution to the semi-globally optimal pair of pump-dump fields. Further reduction is then devised to consider the pure state control system in the weak response regime. In this case, we derive a generalized eigenequation for the non-iterative solution to the complete set of optimal control field pairs, and further identify the globally optimal one unambiguously. The existence of certain symmetry relation between the pump and dump fields in any optimal pair is also analyzed in the stimulate Raman pumping control configuration and demonstrated numerically.
Optimization of microstructure during deformation processing using control theory principles
Venugopal, S.; Medina, E.A.; Malas, J.C. III; Medeiros, S.; Frazier, W.G.; Mullins, W.M.; Srinivasan, R.
1997-02-01
The development of optimal design and control methods for manufacturing processes is needed for effectively reducing part cost, improving part delivery schedules and producing specified part quality on a repeatable basis. A new strategy for systematically calculating near optimal control parameters for hot deformation processes for microstructural control is presented in this communication. This approach is based on modern control theory and involves developing state-space models from available material behavior and hot deformation process models. The control system design consists of two basic stages and analysis and optimization are critical in both stages. In the first stage, the kinetics of certain dynamic microstructural behavior and the intrinsic hot workability of the material are used, along with an appropriately chosen optimality criterion, to calculate optimum strain, strain-rate, and temperature trajectories for processing. A suitable process simulation model is then used in the second stage to calculate process control parameters, such as ram velocity, die profiles and billet temperature, which approximately achieve the strain, strain-rate, and temperate trajectories calculated in the first stage at selected areas of the workpiece. The validity of this approach has been demonstrated with an example on hot extrusion of steel.
NASA Technical Reports Server (NTRS)
Newson, J. R.
1979-01-01
The results of optimal control theory are used to synthesize a feedback filter. The feedback filter is used to force the output of the filtered frequency response to match that of a desired optimal frequency response over a finite frequency range. This matching is accomplished by employing a nonlinear programing algorithm to search for the coefficients of the feedback filter that minimize the error between the optimal frequency response and the filtered frequency response. The method is applied to the synthesis of an active flutter-suppression control law for an aeroelastic wind-tunnel model. It is shown that the resulting control law suppresses flutter over a wide range of subsonic Mach numbers. This is a promising method for synthesizing practical control laws using the results of optimal control theory.
Optimal control of ICU patient discharge: from theory to implementation.
Mallor, Fermín; Azcárate, Cristina; Barado, Julio
2015-09-01
This paper deals with the management of scarce health care resources. We consider a control problem in which the objective is to minimize the rate of patient rejection due to service saturation. The scope of decisions is limited, in terms both of the amount of resources to be used, which are supposed to be fixed, and of the patient arrival pattern, which is assumed to be uncontrollable. This means that the only potential areas of control are speed or completeness of service. By means of queuing theory and optimization techniques, we provide a theoretical solution expressed in terms of service rates. In order to make this theoretical analysis useful for the effective control of the healthcare system, however, further steps in the analysis of the solution are required: physicians need flexible and medically-meaningful operative rules for shortening patient length of service to the degree needed to give the service rates dictated by the theoretical analysis. The main contribution of this paper is to discuss how the theoretical solutions can be transformed into effective management rules to guide doctors' decisions. The study examines three types of rules based on intuitive interpretations of the theoretical solution. Rules are evaluated through implementation in a simulation model. We compare the service rates provided by the different policies with those dictated by the theoretical solution. Probabilistic analysis is also included to support rule validity. An Intensive Care Unit is used to illustrate this control problem. The study focuses on the Markovian case before moving on to consider more realistic LoS distributions (Weibull, Lognormal and Phase-type distribution). PMID:25763761
Optimization of a photovoltaic pumping system based on the optimal control theory
Betka, A.; Attali, A.
2010-07-15
This paper suggests how an optimal operation of a photovoltaic pumping system based on an induction motor driving a centrifugal pump can be realized. The optimization problem consists in maximizing the daily pumped water quantity via the optimization of the motor efficiency for every operation point. The proposed structure allows at the same time the minimization the machine losses, the field oriented control and the maximum power tracking of the photovoltaic array. This will be attained based on multi-input and multi-output optimal regulator theory. The effectiveness of the proposed algorithm is described by simulation and the obtained results are compared to those of a system working with a constant air gap flux. (author)
NASA Technical Reports Server (NTRS)
Armand, J. P.
1972-01-01
An extension of classical methods of optimal control theory for systems described by ordinary differential equations to distributed-parameter systems described by partial differential equations is presented. An application is given involving the minimum-mass design of a simply-supported shear plate with a fixed fundamental frequency of vibration. An optimal plate thickness distribution in analytical form is found. The case of a minimum-mass design of an elastic sandwich plate whose fundamental frequency of free vibration is fixed. Under the most general conditions, the optimization problem reduces to the solution of two simultaneous partial differential equations involving the optimal thickness distribution and the modal displacement. One equation is the uniform energy distribution expression which was found by Ashley and McIntosh for the optimal design of one-dimensional structures with frequency constraints, and by Prager and Taylor for various design criteria in one and two dimensions. The second equation requires dynamic equilibrium at the preassigned vibration frequency.
Application of a locally optimized control theory to pump dump laser-driven chemical reactions
NASA Astrophysics Data System (ADS)
Ohtsuki, Y.; Yahata, Y.; Kono, H.; Fujimura, Y.
1998-05-01
A locally optimized control theory is developed. This theory is applied to pump-dump laser-driven chemical reactions via an electronically excited state. The results show that the theory can design the pulse shapes for chemical reactions with high quantum yields in strong laser intensity regimes in which perturbative treatments break down.
Reduced state feedback gain computation. [optimization and control theory for aircraft control
NASA Technical Reports Server (NTRS)
Kaufman, H.
1976-01-01
Because application of conventional optimal linear regulator theory to flight controller design requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. Therefore, a stochastic linear model that was developed is presented which accounts for aircraft parameter and initial uncertainty, measurement noise, turbulence, pilot command and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.
Aerodynamic shape optimization of wing and wing-body configurations using control theory
NASA Technical Reports Server (NTRS)
Reuther, James; Jameson, Antony
1995-01-01
This paper describes the implementation of optimization techniques based on control theory for wing and wing-body design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for airfoils and wings in which the shape and the surrounding body-fitted mesh are both generated analytically, and the control is the mapping function. Recently, the method has been implemented for both potential flows and flows governed by the Euler equations using an alternative formulation which employs numerically generated grids, so that it can more easily be extended to treat general configurations. Here results are presented both for the optimization of a swept wing using an analytic mapping, and for the optimization of wing and wing-body configurations using a general mesh.
Asplund, Erik; Kluener, Thorsten
2012-03-28
In this paper, control of open quantum systems with emphasis on the control of surface photochemical reactions is presented. A quantum system in a condensed phase undergoes strong dissipative processes. From a theoretical viewpoint, it is important to model such processes in a rigorous way. In this work, the description of open quantum systems is realized within the surrogate Hamiltonian approach [R. Baer and R. Kosloff, J. Chem. Phys. 106, 8862 (1997)]. An efficient and accurate method to find control fields is optimal control theory (OCT) [W. Zhu, J. Botina, and H. Rabitz, J. Chem. Phys. 108, 1953 (1998); Y. Ohtsuki, G. Turinici, and H. Rabitz, J. Chem. Phys. 120, 5509 (2004)]. To gain control of open quantum systems, the surrogate Hamiltonian approach and OCT, with time-dependent targets, are combined. Three open quantum systems are investigated by the combined method, a harmonic oscillator immersed in an ohmic bath, CO adsorbed on a platinum surface, and NO adsorbed on a nickel oxide surface. Throughout this paper, atomic units, i.e., ({Dirac_h}/2{pi})=m{sub e}=e=a{sub 0}= 1, have been used unless otherwise stated.
A comparison of design variables for control theory based airfoil optimization
NASA Technical Reports Server (NTRS)
Reuther, James; Jameson, Antony
1995-01-01
This paper describes the implementation of optimization techniques based on control theory for airfoil design. In our previous work in the area it was shown that control theory could be employed to devise effective optimization procedures for two-dimensional profiles by using either the potential flow or the Euler equations with either a conformal mapping or a general coordinate system. We have also explored three-dimensional extensions of these formulations recently. The goal of our present work is to demonstrate the versatility of the control theory approach by designing airfoils using both Hicks-Henne functions and B-spline control points as design variables. The research also demonstrates that the parameterization of the design space is an open question in aerodynamic design.
Approximation theory for LQG (Linear-Quadratic-Gaussian) optimal control of flexible structures
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Adamian, A.
1988-01-01
An approximation theory is presented for the LQG (Linear-Quadratic-Gaussian) optimal control problem for flexible structures whose distributed models have bounded input and output operators. The main purpose of the theory is to guide the design of finite dimensional compensators that approximate closely the optimal compensator. The optimal LQG problem separates into an optimal linear-quadratic regulator problem and an optimal state estimation problem. The solution of the former problem lies in the solution to an infinite dimensional Riccati operator equation. The approximation scheme approximates the infinite dimensional LQG problem with a sequence of finite dimensional LQG problems defined for a sequence of finite dimensional, usually finite element or modal, approximations of the distributed model of the structure. Two Riccati matrix equations determine the solution to each approximating problem. The finite dimensional equations for numerical approximation are developed, including formulas for converting matrix control and estimator gains to their functional representation to allow comparison of gains based on different orders of approximation. Convergence of the approximating control and estimator gains and of the corresponding finite dimensional compensators is studied. Also, convergence and stability of the closed-loop systems produced with the finite dimensional compensators are discussed. The convergence theory is based on the convergence of the solutions of the finite dimensional Riccati equations to the solutions of the infinite dimensional Riccati equations. A numerical example with a flexible beam, a rotating rigid body, and a lumped mass is given.
Optimal planning of LEO active debris removal based on hybrid optimal control theory
NASA Astrophysics Data System (ADS)
Yu, Jing; Chen, Xiao-qian; Chen, Li-hu
2015-06-01
The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.
Goodwin, D. L.; Kuprov, Ilya
2015-08-28
Auxiliary matrix exponential method is used to derive simple and numerically efficient general expressions for the following, historically rather cumbersome, and hard to compute, theoretical methods: (1) average Hamiltonian theory following interaction representation transformations; (2) Bloch-Redfield-Wangsness theory of nuclear and electron relaxation; (3) gradient ascent pulse engineering version of quantum optimal control theory. In the context of spin dynamics, the auxiliary matrix exponential method is more efficient than methods based on matrix factorizations and also exhibits more favourable complexity scaling with the dimension of the Hamiltonian matrix.
NASA Technical Reports Server (NTRS)
Armstrong, E. S.
1975-01-01
A digital computer program (ORACLS) for implementing the optimal regulator theory approach to the design of controllers for linear time-invariant systems is described. The user-oriented program employs the latest numerical techniques and is applicable to both the digital and continuous control problems.
Credibility theory based dynamic control bound optimization for reservoir flood limited water level
NASA Astrophysics Data System (ADS)
Jiang, Zhiqiang; Sun, Ping; Ji, Changming; Zhou, Jianzhong
2015-10-01
The dynamic control operation of reservoir flood limited water level (FLWL) can solve the contradictions between reservoir flood control and beneficial operation well, and it is an important measure to make sure the security of flood control and realize the flood utilization. The dynamic control bound of FLWL is a fundamental key element for implementing reservoir dynamic control operation. In order to optimize the dynamic control bound of FLWL by considering flood forecasting error, this paper took the forecasting error as a fuzzy variable, and described it with the emerging credibility theory in recent years. By combining the flood forecasting error quantitative model, a credibility-based fuzzy chance constrained model used to optimize the dynamic control bound was proposed in this paper, and fuzzy simulation technology was used to solve the model. The FENGTAN reservoir in China was selected as a case study, and the results show that, compared with the original operation water level, the initial operation water level (IOWL) of FENGTAN reservoir can be raised 4 m, 2 m and 5.5 m respectively in the three division stages of flood season, and without increasing flood control risk. In addition, the rationality and feasibility of the proposed forecasting error quantitative model and credibility-based dynamic control bound optimization model are verified by the calculation results of extreme risk theory.
NASA Technical Reports Server (NTRS)
Byrnes, C. I.
1980-01-01
It is noted that recent work by Kamen (1979) on the stability of half-plane digital filters shows that the problem of the existence of a feedback law also arises for other Banach algebras in applications. This situation calls for a realization theory and stabilizability criteria for systems defined over Banach for Frechet algebra A. Such a theory is developed here, with special emphasis placed on the construction of finitely generated realizations, the existence of coprime factorizations for T(s) defined over A, and the solvability of the quadratic optimal control problem and the associated algebraic Riccati equation over A.
Management of redundancy in flight control systems using optimal decision theory
NASA Technical Reports Server (NTRS)
1981-01-01
The problem of using redundancy that exists between dissimilar systems in aircraft flight control is addressed. That is, using the redundancy that exists between a rate gyro and an accelerometer--devices that have dissimilar outputs which are related only through the dynamics of the aircraft motion. Management of this type of redundancy requires advanced logic so that the system can monitor failure status and can reconfigure itself in the event of one or more failures. An optimal decision theory was tutorially developed for the management of sensor redundancy and the theory is applied to two aircraft examples. The first example is the space shuttle and the second is a highly maneuvering high performance aircraft--the F8-C. The examples illustrate the redundancy management design process and the performance of the algorithms presented in failure detection and control law reconfiguration.
Application of optimal control theory to the design of the NASA/JPL 70-meter antenna servos
NASA Technical Reports Server (NTRS)
Alvarez, L. S.; Nickerson, J.
1989-01-01
The application of Linear Quadratic Gaussian (LQG) techniques to the design of the 70-m axis servos is described. Linear quadratic optimal control and Kalman filter theory are reviewed, and model development and verification are discussed. Families of optimal controller and Kalman filter gain vectors were generated by varying weight parameters. Performance specifications were used to select final gain vectors.
NASA Astrophysics Data System (ADS)
Gobinddass, Marie-Line; Omrane, Abdennebi
Among scientific challenges in space science we find the understanding and the managing of relativity and acceleration's effects on space satellites. Due to the high number of satellite launch every year, the question of recycling addressed by several countries in the world. Some projects focus on the rejection of satellites out of the gravity field of the earth for avoiding a sudden fall in a populated area, but other environmentally friendly projects involve trying to get these satellites for recycling purposes. We will focus on the second recycling point. The good knowledge of these effects can allow the control of all satellites orbit during their lifetime and also after. A mathematical analysis together with the optimal control point of view are here used. We will develop an existence method based on a variational formulation. Then we will use the optimal control theory for the trajectory optimal control under pollution (recycling satellites). Finally, we will focus on the possible generalization of the method with different fixed parameters.
Sustainable ecosystem management using optimal control theory: part 1 (deterministic systems).
Shastri, Y; Diwekar, U
2006-08-01
The concept of sustainability, an abstract one by its nature, has been given a mathematical representation through the use of Fisher information as a measure. It is used to propose the sustainability hypotheses for dynamical systems, which has paved the way to achieve sustainable development through externally enforced control schemes. For natural systems, this refers to the task of ecosystem management, which is complicated due the lack of clear objectives. This work attempts to incorporate the idea of sustainability in ecosystem management. The natural regulation of ecosystems suggests two possible control options, top-down control and bottom-up control. A comparison of these two control philosophies is made on generic food chain models using the objectives derived from the sustainability hypotheses. Optimal control theory is used to derive the control profiles to handle the complex nature of the models and the objectives. The results indicate a strong relationship between the hypotheses and the dynamic behavior of the models, supporting the use of Fisher information as a measure. As regards to ecosystem management, it has been observed that top-down control is more aggressive but can result in instability, while bottom-up control is guaranteed to give a stable and improved dynamic response. The results also indicate that bottom-up control is a better option to affect shifts in the dynamic regimes of a system, which may be required to recover the system from a natural disaster like the hurricane Katrina. PMID:16438988
Optimal control theory investigation of proprotor/wing response to vertical gust
NASA Technical Reports Server (NTRS)
Frick, J. K. D.; Johnson, W.
1974-01-01
Optimal control theory is used to design linear state variable feedback to improve the dynamic characteristics of a rotor and cantilever wing representing the tilting proprotor aircraft in cruise flight. The response to a vertical gust and system damping are used as criteria for the open and closed loop performance. The improvement in the dynamic characteristics achievable is examined for a gimballed rotor and for a hingeless rotor design. Several features of the design process are examined, including: (1) using only the wing or only the rotor dynamics in the control system design; (2) the use of a wing flap as well as the rotor controls for inputs; (3) and the performance of the system designed for one velocity at other forward speeds.
Optimal control theory (OWEM) applied to a helicopter in the hover and approach phase
NASA Technical Reports Server (NTRS)
Born, G. J.; Kai, T.
1975-01-01
A major difficulty in the practical application of linear-quadratic regulator theory is how to choose the weighting matrices in quadratic cost functions. The control system design with optimal weighting matrices was applied to a helicopter in the hover and approach phase. The weighting matrices were calculated to extremize the closed loop total system damping subject to constraints on the determinants. The extremization is really a minimization of the effects of disturbances, and interpreted as a compromise between the generalized system accuracy and the generalized system response speed. The trade-off between the accuracy and the response speed is adjusted by a single parameter, the ratio of determinants. By this approach an objective measure can be obtained for the design of a control system. The measure is to be determined by the system requirements.
APPLICATION OF GAME THEORY IN THE DESIGN OF OPTIMAL AIR POLLUTION CONTROL MEASURES
Methods of game theory are used to develop a technique for finding optimal solutions to air quality problems that involve multiple objectives. The technique is demonstrated using a hypothetical problem in which sites for two new power plants are sought that optimally satisfy five...
ERIC Educational Resources Information Center
Toso, Robert B.
2000-01-01
Inspired by William Glasser's Reality Therapy ideas, Control Theory (CT) is a disciplinary approach that stresses people's ability to control only their own behavior, based on internal motivations to satisfy five basic needs. At one North Dakota high school, CT-trained teachers are the program's best recruiters. (MLH)
NASA Astrophysics Data System (ADS)
Dutton, Kevin E.
1994-07-01
The personnel launch system (PLS) being studied by NASA is a system to complement the space shuttle and provide alternative access to space. The PLS consists of a manned spacecraft launched by an expendable launch vehicle (ELV). A candidate for the manned spacecraft is the HL-20 lifting body. In the event of an ELV malfunction during the initial portion of the ascent trajectory, the HL-20 will separate from the rocket and perform an unpowered return to launch site (RTLS) abort. This work details an investigation, using optimal control theory, of the RTLS abort scenario. The objective of the optimization was to maximize final altitude. With final altitude as the cost function, the feasibility of an RTLS abort at different times during the ascent was determined. The method of differential inclusions was used to determine the optimal state trajectories, and the optimal controls were then calculated from the optimal states and state rates.
NASA Technical Reports Server (NTRS)
Dutton, Kevin E.
1994-01-01
The personnel launch system (PLS) being studied by NASA is a system to complement the space shuttle and provide alternative access to space. The PLS consists of a manned spacecraft launched by an expendable launch vehicle (ELV). A candidate for the manned spacecraft is the HL-20 lifting body. In the event of an ELV malfunction during the initial portion of the ascent trajectory, the HL-20 will separate from the rocket and perform an unpowered return to launch site (RTLS) abort. This work details an investigation, using optimal control theory, of the RTLS abort scenario. The objective of the optimization was to maximize final altitude. With final altitude as the cost function, the feasibility of an RTLS abort at different times during the ascent was determined. The method of differential inclusions was used to determine the optimal state trajectories, and the optimal controls were then calculated from the optimal states and state rates.
ERIC Educational Resources Information Center
Heppler, Brad
2008-01-01
This is a book about quality and how to control quality through deliberate actions on the part of the professionals developing and implementing the instances of instruction available at an organization. Quality control theory favors no particular learning philosophy and is only directed towards aspects of how, what, where and when measurements are…
UAV path planning using artificial potential field method updated by optimal control theory
NASA Astrophysics Data System (ADS)
Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long
2016-04-01
The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.
Orlando, Paul A; Gatenby, Robert A; Brown, Joel S
2012-12-01
Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors 'choose' an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor 'chooses' its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients. PMID:23197192
NASA Astrophysics Data System (ADS)
Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.
2012-12-01
Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.
Application of Optimal Production Control theory for Home Energy Management in a Micro Grid
Malikopoulos, Andreas; Djouadi, Seddik M; Kuruganti, Teja
2016-01-01
We consider the optimal stochastic control problem for home energy systems with solar and energy storage devices when the demand is realized from the grid. The demand is subject to Brownian motions with both drift and variance parameters modulated by a continuous-time Markov chain that represents the regime of electricity price. We model the systems as pure stochastic differential equation models, and then we follow the completing square technique to solve the stochastic home energy management problem. The effectiveness of the efficiency of the proposed approach is validated through a simulation example. For practical situations with constraints consistent to those studied here, our results imply the proposed framework could reduce the electricity cost from short-term purchase in peak hour market.
Neighboring optimal guidance theory and computer program
NASA Technical Reports Server (NTRS)
Powers, W. F.
1974-01-01
Developments of the linear quadratic optimal control problem are discussed. The theory is applicable to the development of neighboring optimal feedback guidance gains, and is useful as a tool for synthesizing feedback control laws. A computer program which requires only the pertinent matrices of the linear quadratic problem is described.
NASA Technical Reports Server (NTRS)
Leyland, Jane Anne
2001-01-01
Given the predicted growth in air transportation, the potential exists for significant market niches for rotary wing subsonic vehicles. Technological advances which optimise rotorcraft aeromechanical behaviour can contribute significantly to both their commercial and military development, acceptance, and sales. Examples of the optimisation of rotorcraft aeromechanical behaviour which are of interest include the minimisation of vibration and/or loads. The reduction of rotorcraft vibration and loads is an important means to extend the useful life of the vehicle and to improve its ride quality. Although vibration reduction can be accomplished by using passive dampers and/or tuned masses, active closed-loop control has the potential to reduce vibration and loads throughout a.wider flight regime whilst requiring less additional weight to the aircraft man that obtained by using passive methads. It is ernphasised that the analysis described herein is applicable to all those rotorcraft aeromechanical behaviour optimisation problems for which the relationship between the harmonic control vector and the measurement vector can be adequately described by a neural-network model.
NASA Technical Reports Server (NTRS)
Chukwu, Ethelbert Nwakuche
1992-01-01
The author derives an equation determining the dynamics of the deterministic model of a flying vehicle. He next examines a simplified mechanical problem whose optimal feedback control strategy is investigated. From there robotics are incorporated into the mathematical model to develop an equation describing optimal control of the dynamics.
Economic policy optimization based on both one stochastic model and the parametric control theory
NASA Astrophysics Data System (ADS)
Ashimov, Abdykappar; Borovskiy, Yuriy; Onalbekov, Mukhit
2016-06-01
A nonlinear dynamic stochastic general equilibrium model with financial frictions is developed to describe two interacting national economies in the environment of the rest of the world. Parameters of nonlinear model are estimated based on its log-linearization by the Bayesian approach. The nonlinear model is verified by retroprognosis, estimation of stability indicators of mappings specified by the model, and estimation the degree of coincidence for results of internal and external shocks' effects on macroeconomic indicators on the basis of the estimated nonlinear model and its log-linearization. On the base of the nonlinear model, the parametric control problems of economic growth and volatility of macroeconomic indicators of Kazakhstan are formulated and solved for two exchange rate regimes (free floating and managed floating exchange rates)
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Semiclassical guided optimal control of molecular dynamics
Kondorskiy, A.; Mil'nikov, G.; Nakamura, H.
2005-10-15
An efficient semiclassical optimal control theory applicable to multidimensional systems is formulated for controlling wave packet dynamics on a single adiabatic potential energy surface. The approach combines advantages of different formulations of optimal control theory: quantum and classical on one hand and global and local on the other. Numerical applications to the control of HCN-CNH isomerization demonstrate that this theory can provide an efficient tool to manipulate molecular dynamics of many degrees of freedom by laser pulses.
Optimal control computer programs
NASA Technical Reports Server (NTRS)
Kuo, F.
1992-01-01
The solution of the optimal control problem, even with low order dynamical systems, can usually strain the analytical ability of most engineers. The understanding of this subject matter, therefore, would be greatly enhanced if a software package existed that could simulate simple generic problems. Surprisingly, despite a great abundance of commercially available control software, few, if any, address the part of optimal control in its most generic form. The purpose of this paper is, therefore, to present a simple computer program that will perform simulations of optimal control problems that arise from the first necessary condition and the Pontryagin's maximum principle.
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
Optimal control of sun tracking solar concentrators
NASA Technical Reports Server (NTRS)
Hughes, R. O.
1979-01-01
Application of the modern control theory to derive an optimal sun tracking control for a point focusing solar concentrator is presented. A standard tracking problem converted to regulator problem using a sun rate input achieves an almost zero steady state tracking error with the optimal control formulation. However, these control techniques are costly because optimal type algorithms require large computing systems, thus they will be used mainly as comparison standards for other types of control algorithms and help in their development.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
NASA Technical Reports Server (NTRS)
Zhang, Zhimin; Tomlinson, John; Martin, Clyde
1994-01-01
In this work, the relationship between splines and the control theory has been analyzed. We show that spline functions can be constructed naturally from the control theory. By establishing a framework based on control theory, we provide a simple and systematic way to construct splines. We have constructed the traditional spline functions including the polynomial splines and the classical exponential spline. We have also discovered some new spline functions such as trigonometric splines and the combination of polynomial, exponential and trigonometric splines. The method proposed in this paper is easy to implement. Some numerical experiments are performed to investigate properties of different spline approximations.
Porsa, Sina; Lin, Yi-Chung; Pandy, Marcus G
2016-08-01
The aim of this study was to compare the computational performances of two direct methods for solving large-scale, nonlinear, optimal control problems in human movement. Direct shooting and direct collocation were implemented on an 8-segment, 48-muscle model of the body (24 muscles on each side) to compute the optimal control solution for maximum-height jumping. Both algorithms were executed on a freely-available musculoskeletal modeling platform called OpenSim. Direct collocation converged to essentially the same optimal solution up to 249 times faster than direct shooting when the same initial guess was assumed (3.4 h of CPU time for direct collocation vs. 35.3 days for direct shooting). The model predictions were in good agreement with the time histories of joint angles, ground reaction forces and muscle activation patterns measured for subjects jumping to their maximum achievable heights. Both methods converged to essentially the same solution when started from the same initial guess, but computation time was sensitive to the initial guess assumed. Direct collocation demonstrates exceptional computational performance and is well suited to performing predictive simulations of movement using large-scale musculoskeletal models. PMID:26715209
Johnson, E.A.; Leung, C.; Schira, J.J.
1983-03-01
A closed loop timing optimization control for an internal combustion engine closed about the instantaneous rotational velocity of the engine's crankshaft is disclosed herein. The optimization control computes from the instantaneous rotational velocity of the engine's crankshaft, a signal indicative of the angle at which the crankshaft has a maximum rotational velocity for the torque impulses imparted to the engine's crankshaft by the burning of an air/fuel mixture in each of the engine's combustion chambers and generates a timing correction signal for each of the engine's combustion chambers. The timing correction signals, applied to the engine timing control, modifies the time at which the ignition signal, injection signals or both are generated such that the rotational velocity of the engine's crankshaft has a maximum value at a predetermined angle for each torque impulse generated optimizing the conversion of the combustion energy to rotational torque.
Optimal control of native predators
Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.
2010-01-01
We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.
Optimal Control of Evolution Mixed Variational Inclusions
Alduncin, Gonzalo
2013-12-15
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
Egger, D J; Wilhelm, F K
2014-06-20
Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful. PMID:24996074
Optimization Theory in Behavioural Ecology.
ERIC Educational Resources Information Center
Reiss, Michael J.
1987-01-01
Discusses variables which determine the strategies animals use to organize their lives. Describes advances in understanding animal behaviors. Shows how game theory has helped to explain the existence of alternative behavioral strategies and the constraints under which organizers exist. (Author/CW)
NASA Technical Reports Server (NTRS)
Tumin, Anatoli; Ashpis, David E.
2003-01-01
An analysis of the non-modal growth of perturbations in a boundary layer in the presence of a streamwise pressure gradient is presented. The analysis is based on PSE equations for an incompressible fluid. Examples with Falkner-Skan profiles indicate that a favorable pressure gradient decreases the non-modal growth while an unfavorable pressure gradient leads to an increase of the amplification. It is suggested that the transient growth mechanism be utilized to choose optimal parameters of tripping elements on a low-pressure turbine (LPT) airfoil. As an example, a boundary layer flow with a streamwise pressure gradient corresponding to the pressure distribution over a LPT airfoil is considered. It is shown that there is an optimal spacing of the tripping elements and that the transient growth effect depends on the starting point. At very low Reynolds numbers, there is a possibility to enhance the transient energy growth by means of wall cooling.
Optimal control of HIV/AIDS dynamic: Education and treatment
NASA Astrophysics Data System (ADS)
Sule, Amiru; Abdullah, Farah Aini
2014-07-01
A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.
NASA Technical Reports Server (NTRS)
Allan, Brian; Owens, Lewis
2010-01-01
In support of the Blended-Wing-Body aircraft concept, a new flow control hybrid vane/jet design has been developed for use in a boundary-layer-ingesting (BLI) offset inlet in transonic flows. This inlet flow control is designed to minimize the engine fan-face distortion levels and the first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. This concept represents a potentially enabling technology for quieter and more environmentally friendly transport aircraft. An optimum vane design was found by minimizing the engine fan-face distortion, DC60, and the first five Fourier harmonic half amplitudes, while maximizing the total pressure recovery. The optimal vane design was then used in a BLI inlet wind tunnel experiment at NASA Langley's 0.3-meter transonic cryogenic tunnel. The experimental results demonstrated an 80-percent decrease in DPCPavg, the reduction in the circumferential distortion levels, at an inlet mass flow rate corresponding to the middle of the operational range at the cruise condition. Even though the vanes were designed at a single inlet mass flow rate, they performed very well over the entire inlet mass flow range tested in the wind tunnel experiment with the addition of a small amount of jet flow control. While the circumferential distortion was decreased, the radial distortion on the outer rings at the aerodynamic interface plane (AIP) increased. This was a result of the large boundary layer being distributed from the bottom of the AIP in the baseline case to the outer edges of the AIP when using the vortex generator (VG) vane flow control. Experimental results, as already mentioned, showed an 80-percent reduction of DPCPavg, the circumferential distortion level at the engine fan-face. The hybrid approach leverages strengths of vane and jet flow control devices, increasing inlet performance over a broader operational range with significant reduction in mass flow requirements. Minimal distortion level requirements
On Restructurable Control System Theory
NASA Technical Reports Server (NTRS)
Athans, M.
1983-01-01
The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.
Optimal control techniques for active noise suppression
NASA Technical Reports Server (NTRS)
Banks, H. T.; Keeling, S. L.; Silcox, R. J.
1988-01-01
Active suppression of noise in a bounded enclosure is considered within the framework of optimal control theory. A sinusoidal pressure field due to exterior offending noise sources is assumed to be known in a neighborhood of interior sensors. The pressure field due to interior controlling sources is assumed to be governed by a nonhomogeneous wave equation within the enclosure and by a special boundary condition designed to accommodate frequency-dependent reflection properties of the enclosure boundary. The form of the controlling sources is determined by considering the steady-state behavior of the system, and it is established that the control strategy proposed is stable and asymptotically optimal.
Metacognitive Control and Optimal Learning
ERIC Educational Resources Information Center
Son, Lisa K.; Sethi, Rajiv
2006-01-01
The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake…
Optimal search behavior and classic foraging theory
NASA Astrophysics Data System (ADS)
Bartumeus, F.; Catalan, J.
2009-10-01
Random walk methods and diffusion theory pervaded ecological sciences as methods to analyze and describe animal movement. Consequently, statistical physics was mostly seen as a toolbox rather than as a conceptual framework that could contribute to theory on evolutionary biology and ecology. However, the existence of mechanistic relationships and feedbacks between behavioral processes and statistical patterns of movement suggests that, beyond movement quantification, statistical physics may prove to be an adequate framework to understand animal behavior across scales from an ecological and evolutionary perspective. Recently developed random search theory has served to critically re-evaluate classic ecological questions on animal foraging. For instance, during the last few years, there has been a growing debate on whether search behavior can include traits that improve success by optimizing random (stochastic) searches. Here, we stress the need to bring together the general encounter problem within foraging theory, as a mean for making progress in the biological understanding of random searching. By sketching the assumptions of optimal foraging theory (OFT) and by summarizing recent results on random search strategies, we pinpoint ways to extend classic OFT, and integrate the study of search strategies and its main results into the more general theory of optimal foraging.
Supercomputer optimizations for stochastic optimal control applications
NASA Technical Reports Server (NTRS)
Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang
1991-01-01
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.
Investigating Optimal Foraging Theory in the Laboratory
ERIC Educational Resources Information Center
Harden, Siegfried; Grilliot, Matthew E.
2014-01-01
Optimal foraging theory is a principle that is often presented in the community ecology section of biology textbooks, but also can be demonstrated in the laboratory. We introduce a lab activity that uses an interactive strategy to teach high school and/or college students about this ecological concept. The activity is ideal because it engages…
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Fuel consumption in optimal control
NASA Technical Reports Server (NTRS)
Redmond, Jim; Silverberg, Larry
1992-01-01
A method has been developed for comparing three optimal control strategies based on fuel consumption. A general cost function minimization procedure was developed by applying two theorems associated with convex sets. Three cost functions associated with control saturation, pseudofuel, and absolute fuel are introduced and minimized. The first two cost functions led to the bang-bang and continuous control strategies, and the minimization of absolute fuel led to an impulsive strategy. The three control strategies were implemented on two elementary systems and a comparison of fuel consumption was made. The impulse control strategy consumes significantly less fuel than the continuous and bang-bang control strategies. This comparison suggests a potential for fuel savings in higher-order systems using impulsive control strategies. However, since exact solutions to fuel-optimal control for large-order systems are difficult if not impossible to achieve, the alternative is to develop near-optimal control strategies.
Optimal control of the spine system.
Xu, Yunfei; Choi, Jongeun; Reeves, N Peter; Cholewicki, Jacek
2010-05-01
The goal of this work is to present methodology to first evaluate the performance of an in vivo spine system and then to synthesize optimal neuromuscular control for rehabilitation interventions. This is achieved (1) by determining control system parameters such as static feedback gains and delays from experimental data, (2) by synthesizing the optimal feedback gains to attenuate the effect of disturbances to the system using modern control theory, and (3) by evaluating the robustness of the optimized closed-loop system. We also apply these methods to a postural control task, with two different control strategies, and evaluate the robustness of the spine system with respect to longer latencies found in the low back pain population. This framework could be used for rehabilitation design. To this end, we discuss several future research needs necessary to implement our framework in practice. PMID:20459205
Optimal and multivariable control of a turbogenerator
NASA Astrophysics Data System (ADS)
Lahoud, M. A.; Harley, R. G.; Secker, A.
The use of modern control methods to design multivariable controllers which improve the performance of a turbogenerator was investigated. The turbogenerator nonlinear mathematical model from which a linearized model is deduced is presented. The inverse Nyquist Array method and the theory of optimal control are both applied to the linearized model to generate two alternative control schemes. The schemes are implemented on the nonlinear simulation model to assess their dynamic performance. Results from modern multivariable control schemes are compared with the classical automatic voltage regulator and speed governor system.
Control Theory and Statistical Generalizations.
ERIC Educational Resources Information Center
Powers, William T.
1990-01-01
Contrasts modeling methods in control theory to the methods of statistical generalizations in empirical studies of human or animal behavior. Presents a computer simulation that predicts behavior based on variables (effort and rewards) determined by the invariable (desired reward). Argues that control theory methods better reflect relationships to…
Optimized Perturbation Theory:. Finite Temperature Applications
NASA Astrophysics Data System (ADS)
Pinto, Marcus Benghi
2001-09-01
We review the optimized perturbation theory (or linear δ-expansion) illustrating with an application to the anharmonic oscillator. We then apply the method to multi-field O(N1) × O(N2) scalar theories at high temperatures to investigate the possibility of inverse symmetry breaking (or symmetry non restoration). Our results support inverse symmetry breaking and reveal the possibility of other high temperature symmetry breaking patterns for which the last term in the breaking sequence is O(N1 - 1) × O(N2 - 1).
Optimal control for electron shuttling
NASA Astrophysics Data System (ADS)
Zhang, Jun; Greenman, Loren; Deng, Xiaotian; Hayes, Ian M.; Whaley, K. Birgitta
2013-06-01
In this paper we apply an optimal control technique to derive control fields that transfer an electron between ends of a chain of donors or quantum dots. We formulate the transfer as an optimal steering problem, and then derive the dynamics of the optimal control. A numerical algorithm is developed to effectively generate control pulses. We apply this technique to transfer an electron between sites of a triple quantum dot and an ionized chain of phosphorus dopants in silicon. Using the optimal pulses for the spatial shuttling of phosphorus dopants, we then add hyperfine interactions to the Hamiltonian and show that a 500 G magnetic field will transfer the electron spatially as well as transferring the spin components of two of the four hyperfine states of the electron-nuclear spin pair.
Optimally designed fields for controlling molecular dynamics
NASA Astrophysics Data System (ADS)
Rabitz, Herschel
1991-10-01
This research concerns the development of molecular control theory techniques for designing optical fields capable of manipulating molecular dynamic phenomena. Although is has been long recognized that lasers should be capable of manipulating dynamic events, many frustrating years of intuitively driven laboratory studies only serve to illustrate the point that the task is complex and defies intuition. The principal new component in the present research is the recognition that this problem falls into the category of control theory and its inherent complexities require the use of modern control theory tools largely developed in the engineering disciplines. Thus, the research has initiated a transfer of the control theory concepts to the molecular scale. Although much contained effort will be needed to fully develop these concepts, the research in this grant set forth the basic components of the theory and carried out illustrative studies involving the design of optical fields capable of controlling rotational, vibrational and electronic degrees of freedom. Optimal control within the quantum mechanical molecular realm represents a frontier area with many possible ultimate applications. At this stage, the theoretical tools need to be joined with merging laboratory optical pulse shaping capabilities to illustrate the power of the concepts.
Cancer Behavior: An Optimal Control Approach
Gutiérrez, Pedro J.; Russo, Irma H.; Russo, J.
2009-01-01
With special attention to cancer, this essay explains how Optimal Control Theory, mainly used in Economics, can be applied to the analysis of biological behaviors, and illustrates the ability of this mathematical branch to describe biological phenomena and biological interrelationships. Two examples are provided to show the capability and versatility of this powerful mathematical approach in the study of biological questions. The first describes a process of organogenesis, and the second the development of tumors. PMID:22247736
Optimality principles in sensorimotor control (review)
Todorov, Emanuel
2006-01-01
The sensorimotor system is a product of evolution, development, learning, adaptation – processes that work on different time scales to improve behavioral performance. Consequenly, many theories of motor function are based on the notion of optimal performance: they quantify the task goals, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, has explained a wider range of empirical phenomena than any other class of models. Traditional emphasis has been on optimizing average trajectories while ignoring sensory feedback. Recent work has redefined optimality on the level of feedback control laws, and focused on the mechanisms that generate behavior online. This has made it possible to fit a number of previously unrelated concepts and observations into what may become a unified theoretical framework for interpreting motor function. At the heart of the framework is the relationship between high-level goals, and the realtime sensorimotor control strategies most suitable for accomplishing those goals. PMID:15332089
Optimal control of motorsport differentials
NASA Astrophysics Data System (ADS)
Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.
2015-12-01
Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.
Optimal and robust control of transition
NASA Technical Reports Server (NTRS)
Bewley, T. R.; Agarwal, R.
1996-01-01
Optimal and robust control theories are used to determine feedback control rules that effectively stabilize a linearly unstable flow in a plane channel. Wall transpiration (unsteady blowing/suction) with zero net mass flux is used as the control. Control algorithms are considered that depend both on full flowfield information and on estimates of that flowfield based on wall skin-friction measurements only. The development of these control algorithms accounts for modeling errors and measurement noise in a rigorous fashion; these disturbances are considered in both a structured (Gaussian) and unstructured ('worst case') sense. The performance of these algorithms is analyzed in terms of the eigenmodes of the resulting controlled systems, and the sensitivity of individual eigenmodes to both control and observation is quantified.
Optimal control with multiple human papillomavirus vaccines.
Malik, Tufail; Imran, Mudassar; Jayaraman, Raja
2016-03-21
A two-sex, deterministic ordinary differential equations model for human papillomavirus (HPV) is constructed and analyzed for optimal control strategies in a vaccination program administering three types of vaccines in the female population: a bivalent vaccine that targets two HPV types and provides longer duration of protection and cross-protection against some non-target types, a quadrivalent vaccine which targets an additional two HPV types, and a nonavalent vaccine which targets nine HPV types (including those covered by the quadrivalent vaccine), but with lesser type-specific efficacy. Considering constant vaccination controls, the disease-free equilibrium and the effective reproduction number Rv for the autonomous model are computed in terms of the model parameters. Local-asymptotic stability of the disease-free equilibrium is established in terms of Rv. Uncertainty and Sensitivity analyses are carried out to study the influence of various important model parameters on the HPV infection prevalence. Assuming the HPV infection prevalence in the population under the constant control, optimal control theory is used to devise optimal vaccination strategies for the associated non-autonomous model when the vaccination rates are functions of time. The impact of these strategies on the number of infected individuals and the accumulated cost is assessed and compared with the constant control case. Switch times from one vaccine combination to a different combination including the nonavalent vaccine are assessed during an optimally designed HPV immunization program. PMID:26796222
Optimal dynamic control of resources in a distributed system
NASA Technical Reports Server (NTRS)
Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang
1989-01-01
The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.
H2-optimal control with generalized state-space models for use in control-structure optimization
NASA Technical Reports Server (NTRS)
Wette, Matt
1991-01-01
Several advances are provided solving combined control-structure optimization problems. The author has extended solutions from H2 optimal control theory to the use of generalized state space models. The generalized state space models preserve the sparsity inherent in finite element models and hence provide some promise for handling very large problems. Also, expressions for the gradient of the optimal control cost are derived which use the generalized state space models.
Optimal Feedback Control of Thermal Networks
NASA Technical Reports Server (NTRS)
Papalexandris, Miltiadis
2003-01-01
An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.
Optimization of constrained density functional theory
NASA Astrophysics Data System (ADS)
O'Regan, David D.; Teobaldi, Gilberto
2016-07-01
Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated Lagrange multiplier optimization is necessary for multiple constraints to be applied efficiently in cDFT, for it to be used in tandem with geometry optimization, or with molecular dynamics. In order to facilitate this, we comprehensively develop the connection between cDFT energy derivatives and response functions, providing a rigorous assessment of the uniqueness and character of cDFT stationary points while accounting for electronic interactions and screening. In particular, we provide a nonperturbative proof that stable stationary points of linear density constraints occur only at energy maxima with respect to their Lagrange multipliers. We show that multiple solutions, hysteresis, and energy discontinuities may occur in cDFT. Expressions are derived, in terms of convenient by-products of cDFT optimization, for quantities such as the dielectric function and a condition number quantifying ill definition in multiple constraint cDFT.
Optimal control strategies for coupled quantum dots
NASA Astrophysics Data System (ADS)
Räsänen, Esa; Putaja, Antti; Mardoukhi, Yousof
2013-09-01
Semiconductor quantum dots are ideal candidates for quantum information applications in solid-state technology. However, advanced theoretical and experimental tools are required to coherently control, for example, the electronic charge in these systems. Here we demonstrate how quantum optimal control theory provides a powerful way to manipulate the electronic structure of coupled quantum dots with an extremely high fidelity. As alternative control fields we apply both laser pulses as well as electric gates, respectively. We focus on double and triple quantum dots containing a single electron or two electrons interacting via Coulomb repulsion. In the two-electron situation we also briefly demonstrate the challenges of timedependent density-functional theory within the adiabatic local-density approximation to produce comparable results with the numerically exact approach.
Unifying process control and optimization
Makansi, J.
2005-09-01
About 40% of US generation is now subject to wholesale competition. To intelligently bid into these new markets, real-time prices must be aligned with real-time costs. It is time to integrate the many advanced applications, sensors, and analyzers used for control, automation, and optimization into a system that reflects process and financial objectives. The paper reports several demonstration projects in the USA revealing what is being done in the area of advanced process optimization (by Alliant Energy, American Electric Power, PacifiCorp, Detroit Edison and Tennessee Valley Authority). In addition to these projects US DOE's NETL has funded the plant environment and cost optimization system, PECOS which combines physical models, neural networks and fuzzy logic control to provide operators with least cost setpoints for controllable variables. At Dynegy Inc's Baldwin station in Illinois the DOE is subsidizing a project where real time, closed-loop IT systems will optimize combustion, soot-blowing and SCR performance as well as unit thermal performance and plant economic performance. Commercial products such as Babcock and Wilcox's Flame Doctor, continuous emissions monitoring systems and various real-time predictive monitoring systems are also available. 4 figs.
Mean-field sparse optimal control
Fornasier, Massimo; Piccoli, Benedetto; Rossi, Francesco
2014-01-01
We introduce the rigorous limit process connecting finite dimensional sparse optimal control problems with ODE constraints, modelling parsimonious interventions on the dynamics of a moving population divided into leaders and followers, to an infinite dimensional optimal control problem with a constraint given by a system of ODE for the leaders coupled with a PDE of Vlasov-type, governing the dynamics of the probability distribution of the followers. In the classical mean-field theory, one studies the behaviour of a large number of small individuals freely interacting with each other, by simplifying the effect of all the other individuals on any given individual by a single averaged effect. In this paper, we address instead the situation where the leaders are actually influenced also by an external policy maker, and we propagate its effect for the number N of followers going to infinity. The technical derivation of the sparse mean-field optimal control is realized by the simultaneous development of the mean-field limit of the equations governing the followers dynamics together with the Γ-limit of the finite dimensional sparse optimal control problems. PMID:25288818
Optimal woofer tweeter control demonstration
NASA Astrophysics Data System (ADS)
Le Roux, B.; El Hadi, K.; NDiaye, M.; Gray, M.
2011-09-01
Large aperture telescope adaptive optics incorporates several deformable and active mirrors. Several options have been proposed for several DM adaptive optics systems. We study an optimal control approach for these woofer tweeter systems based on a Kalman filtering method. This approach allows to share out the spatial energy of correction between the mirrors and to deal with different temporal response time. The approach is presented and a validation of the control method is carried out in a numerical simulation. We finally present the experimental validation of such control solutions for woofer-tweeter systems. The validation bench and the optical components are presented and the first experimental results are shown.
Optimal control of hydroelectric facilities
NASA Astrophysics Data System (ADS)
Zhao, Guangzhi
This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the
Practical synchronization on complex dynamical networks via optimal pinning control.
Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu
2015-07-01
We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications. PMID:26274112
Combined control-structure optimization
NASA Technical Reports Server (NTRS)
Salama, M.; Milman, M.; Bruno, R.; Scheid, R.; Gibson, S.
1989-01-01
An approach for combined control-structure optimization keyed to enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and appears to be effective for generating families of designs that can be used in these early trade studies. Analytical results were obtained for classes of structure/control objectives with linear quadratic Gaussian (LQG) and linear quadratic regulator (LQR) costs. For these, researchers demonstrated that global optima can be computed for small values of the homotopy parameter. Conditions for local optima along the homotopy path were also given. Details of two numerical examples employing the LQR control cost were given showing variations of the optimal design variables along the homotopy path. The results of the second example suggest that introducing a second homotopy parameter relating the two parts of the control index in the LQG/LQR formulation might serve to enlarge the family of Pareto optima, but its effect on modifying the optimal structural shapes may be analogous to the original parameter lambda.
Pilot-optimal multivariable control synthesis by output feedback
NASA Technical Reports Server (NTRS)
Schmidt, D. K.; Innocenti, M.
1981-01-01
A control system design approach for optimal stability augmentation, systems, using limited state feedback theory with the specific inclusion of the human pilot in the loop is presented. The methodology is especially suitable for application to flight vehicles exhibiting nonconventional dynamic characteristics and for which quantitative handling qualities specifications are not available. The design is based on a correlation between pilot ratings and objective function of the optimal control model of the human pilot. Simultaneous optimization for augmentation and pilot gains are required.
NASA Technical Reports Server (NTRS)
Broussard, J. R.; Halyo, N.
1984-01-01
This report contains the development of a digital outer-loop three dimensional radio navigation (3-D RNAV) flight control system for a small commercial jet transport. The outer-loop control system is designed using optimal stochastic limited state feedback techniques. Options investigated using the optimal limited state feedback approach include integrated versus hierarchical control loop designs, 20 samples per second versus 5 samples per second outer-loop operation and alternative Type 1 integration command errors. Command generator tracking techniques used in the digital control design enable the jet transport to automatically track arbitrary curved flight paths generated by waypoints. The performance of the design is demonstrated using detailed nonlinear aircraft simulations in the terminal area, frequency domain multi-input sigma plots, frequency domain single-input Bode plots and closed-loop poles. The response of the system to a severe wind shear during a landing approach is also presented.
Optimal control in a macroeconomic problem
NASA Astrophysics Data System (ADS)
Bulgakov, V. K.; Shatov, G. L.
2007-08-01
The Pontryagin maximum principle is used to develop an original algorithm for finding an optimal control in a macroeconomic problem. Numerical results are presented for the optimal control and optimal trajectory of the development of a regional economic system. For an optimal control satisfying a certain constraint, an invariant of a macroeconomic system is derived.
Aerodynamic design via control theory
NASA Technical Reports Server (NTRS)
Jameson, Antony
1988-01-01
The question of how to modify aerodynamic design in order to improve performance is addressed. Representative examples are given to demonstrate the computational feasibility of using control theory for such a purpose. An introduction and historical survey of the subject is included.
Quasivelocities and Optimal Control for underactuated Mechanical Systems
Colombo, L.; Martin de Diego, D.
2010-07-28
This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.
Quasivelocities and Optimal Control for underactuated Mechanical Systems
NASA Astrophysics Data System (ADS)
Colombo, L.; de Diego, D. Martín
2010-07-01
This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.
Optimal coordination and control of posture and movements.
Johansson, Rolf; Fransson, Per-Anders; Magnusson, Måns
2009-01-01
This paper presents a theoretical model of stability and coordination of posture and locomotion, together with algorithms for continuous-time quadratic optimization of motion control. Explicit solutions to the Hamilton-Jacobi equation for optimal control of rigid-body motion are obtained by solving an algebraic matrix equation. The stability is investigated with Lyapunov function theory and it is shown that global asymptotic stability holds. It is also shown how optimal control and adaptive control may act in concert in the case of unknown or uncertain system parameters. The solution describes motion strategies of minimum effort and variance. The proposed optimal control is formulated to be suitable as a posture and movement model for experimental validation and verification. The combination of adaptive and optimal control makes this algorithm a candidate for coordination and control of functional neuromuscular stimulation as well as of prostheses. Validation examples with experimental data are provided. PMID:19671443
Orbital-optimized density cumulant functional theory
Sokolov, Alexander Yu. Schaefer, Henry F.
2013-11-28
In density cumulant functional theory (DCFT) the electronic energy is evaluated from the one-particle density matrix and two-particle density cumulant, circumventing the computation of the wavefunction. To achieve this, the one-particle density matrix is decomposed exactly into the mean-field (idempotent) and correlation components. While the latter can be entirely derived from the density cumulant, the former must be obtained by choosing a specific set of orbitals. In the original DCFT formulation [W. Kutzelnigg, J. Chem. Phys. 125, 171101 (2006)] the orbitals were determined by diagonalizing the effective Fock operator, which introduces partial orbital relaxation. Here we present a new orbital-optimized formulation of DCFT where the energy is variationally minimized with respect to orbital rotations. This introduces important energy contributions and significantly improves the description of the dynamic correlation. In addition, it greatly simplifies the computation of analytic gradients, for which expressions are also presented. We offer a perturbative analysis of the new orbital stationarity conditions and benchmark their performance for a variety of chemical systems.
An Affect Control Theory of Technology
ERIC Educational Resources Information Center
Shank, Daniel B.
2010-01-01
Affect control theory is a theory of interaction that takes into account cultural meanings. Affect control research has previously considered interaction with technology, but there remains a lack of theorizing about inclusion of technology within the theory. This paper lays a foundation for an affect control theory of technology by addressing key…
Optimal control of overdamped systems.
Zulkowski, Patrick R; DeWeese, Michael R
2015-09-01
Nonequilibrium physics encompasses a broad range of natural and synthetic small-scale systems. Optimizing transitions of such systems will be crucial for the development of nanoscale technologies and may reveal the physical principles underlying biological processes at the molecular level. Recent work has demonstrated that when a thermodynamic system is driven away from equilibrium then the space of controllable parameters has a Riemannian geometry induced by a generalized inverse diffusion tensor. We derive a simple, compact expression for the inverse diffusion tensor that depends solely on equilibrium information for a broad class of potentials. We use this formula to compute the minimal dissipation for two model systems relevant to small-scale information processing and biological molecular motors. In the first model, we optimally erase a single classical bit of information modeled by an overdamped particle in a smooth double-well potential. In the second model, we find the minimal dissipation of a simple molecular motor model coupled to an optical trap. In both models, we find that the minimal dissipation for the optimal protocol of duration τ is proportional to 1/τ, as expected, though the dissipation for the erasure model takes a different form than what we found previously for a similar system. PMID:26465436
HCCI Engine Optimization and Control
Rolf D. Reitz
2005-09-30
The goal of this project was to develop methods to optimize and control Homogeneous-Charge Compression Ignition (HCCI) engines, with emphasis on diesel-fueled engines. HCCI offers the potential of nearly eliminating IC engine NOx and particulate emissions at reduced cost over Compression Ignition Direct Injection engines (CIDI) by controlling pollutant emissions in-cylinder. The project was initiated in January, 2002, and the present report is the final report for work conducted on the project through December 31, 2004. Periodic progress has also been reported at bi-annual working group meetings held at USCAR, Detroit, MI, and at the Sandia National Laboratories. Copies of these presentation materials are available on CD-ROM, as distributed by the Sandia National Labs. In addition, progress has been documented in DOE Advanced Combustion Engine R&D Annual Progress Reports for FY 2002, 2003 and 2004. These reports are included as the Appendices in this Final report.
Aerospace plane guidance using geometric control theory
NASA Technical Reports Server (NTRS)
Van Buren, Mark A.; Mease, Kenneth D.
1990-01-01
A reduced-order method employing decomposition, based on time-scale separation, of the 4-D state space in a 2-D slow manifold and a family of 2-D fast manifolds is shown to provide an excellent approximation to the full-order minimum-fuel ascent trajectory. Near-optimal guidance is obtained by tracking the reduced-order trajectory. The tracking problem is solved as regulation problems on the family of fast manifolds, using the exact linearization methodology from nonlinear geometric control theory. The validity of the overall guidance approach is indicated by simulation.
Testing Optimal Foraging Theory Using Bird Predation on Goldenrod Galls
ERIC Educational Resources Information Center
Yahnke, Christopher J.
2006-01-01
All animals must make choices regarding what foods to eat, where to eat, and how much time to spend feeding. Optimal foraging theory explains these behaviors in terms of costs and benefits. This laboratory exercise focuses on optimal foraging theory by investigating the winter feeding behavior of birds on the goldenrod gall fly by comparing…
Adaptive, predictive controller for optimal process control
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
New Applications of Variational Analysis to Optimization and Control
NASA Astrophysics Data System (ADS)
Mordukhovich, Boris S.
We discuss new applications of advanced tools of variational analysis and generalized differentiation to a number of important problems in optimization theory, equilibria, optimal control, and feedback control design. The presented results are largely based on the recent work by the author and his collaborators. Among the main topics considered and briefly surveyed in this paper are new calculus rules for generalized differentiation of nonsmooth and set-valued mappings; necessary and sufficient conditions for new notions of linear subextremality and suboptimality in constrained problems; optimality conditions for mathematical problems with equilibrium constraints; necessary optimality conditions for optimistic bilevel programming with smooth and nonsmooth data; existence theorems and optimality conditions for various notions of Pareto-type optimality in problems of multiobjective optimization with vector-valued and set-valued cost mappings; Lipschitzian stability and metric regularity aspects for constrained and variational systems.
Fuzzy logic control and optimization system
Lou, Xinsheng
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Applying new optimization algorithms to more predictive control
Wright, S.J.
1996-03-01
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
The neural optimal control hierarchy for motor control
NASA Astrophysics Data System (ADS)
DeWolf, T.; Eliasmith, C.
2011-10-01
Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.
Control optimization of the cryoplant warm compressor station for EAST
Zhuang, M.; Hu, L. B.; Zhou, Z. W.; Xia, G. H.
2014-01-29
The cryogenic control system for EAST (Experimental Advanced Superconducting Tokamak) was designed based on DeltaV DCS of Emerson Corporation. The automatic control of the cryoplant warm compressors has been implemented. However, with ever-degrading performance of critical equipment, the cryoplant operation in the partial design conditions makes the control system fluctuate and unstable. In this paper, the warm compressor control system was optimized to eliminate the pressure oscillation based on the expert PID theory.
Optimal control of orbital transfer vehicles
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1983-01-01
During the past two decades, considerable research effort has been spent to convincingly prove that the use of aerodynamic forces to assist in the orbital transfer can significantly reduce the fuel consumption as compared to the pure propulsive mode. Since in this aeroassisted mode, preliminary maneuvers in the vacuum effect the resulting performance in the atmospheric phase, and vice versa, the two, space and atmospheric maneuvers, are, to a great extent, coupled. This paper summarizes, via optimal control theory, the fundamental results in the problem of orbital transfer using combined propulsive and aerodynamic forces. For the atmospheric phase, the use of Chapman's variables reduced the number of the physical characteristics of the vehicle and the atmosphere to a minimum and hence allows a better generalization of the results. The paper concludes with some illustrative examples.
On Applications of Extreme Value Theory in Optimization
NASA Astrophysics Data System (ADS)
Hüsler, Jürg
We present a statistical study of the distribution of the objective value of solutions (outcomes) obtained by stochastic optimizers, applied for continuous objective functions. We discuss the application of extreme value theory for the optimization procedures. A short review of the extreme value theory is presented to understand the investigations. In this chapter three optimization procedures are compared in this context: the random search and two evolution strategies. The outcomes of these optimizers applied to three objective functions are discussed in the context of extreme value theory and the performances of the procedures investigated, analytically and by simulations. In particular, we find that the estimated extreme value distributions and the fit to the outcomes characterize the performance of the optimizer in one single instance.
Backward bifurcation and optimal control of Plasmodium Knowlesi malaria
NASA Astrophysics Data System (ADS)
Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini
2014-07-01
A deterministic model for the transmission dynamics of Plasmodium Knowlesi malaria with direct transmission is developed. The model is analyzed using dynamical system techniques and it shows that the backward bifurcation occurs for some range of parameters. The model is extended to assess the impact of time dependent preventive (biological and chemical control) against the mosquitoes and vaccination for susceptible humans, while treatment for infected humans. The existence of optimal control is established analytically by the use of optimal control theory. Numerical simulations of the problem, suggest that applying the four control measure can effectively reduce if not eliminate the spread of Plasmodium Knowlesi in a community.
Optimal singular control with applications to trajectory optimization
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1977-01-01
A comprehensive discussion of the problem of singular control is presented. Singular control enters an optimal trajectory when the so called switching function vanishes identically over a finite time interval. Using the concept of domain of maneuverability, the problem of optical switching is analyzed. Criteria for the optimal direction of switching are presented. The switching, or junction, between nonsingular and singular subarcs is examined in detail. Several theorems concerning the necessary, and also sufficient conditions for smooth junction are presented. The concepts of quasi-linear control and linearized control are introduced. They are designed for the purpose of obtaining approximate solution for the difficult Euler-Lagrange type of optimal control in the case where the control is nonlinear.
Adaptive optimization and control using neural networks
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Optimizing Dynamical Network Structure for Pinning Control
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-01-01
Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights. PMID:27067020
Optimizing Dynamical Network Structure for Pinning Control.
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-01-01
Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights. PMID:27067020
Optimizing Dynamical Network Structure for Pinning Control
NASA Astrophysics Data System (ADS)
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-04-01
Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.
Mixed-Strategy Chance Constrained Optimal Control
NASA Technical Reports Server (NTRS)
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.
2013-01-01
This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.
Optimal control of vaccine distribution in a rabies metapopulation model.
Asano, Erika; Gross, Louis J; Lenhart, Suzanne; Real, Leslie A
2008-04-01
We consider an SIR metapopulation model for the spread of rabies in raccoons. This system of ordinary differential equations considers subpopulations connected by movement. Vaccine for raccoons is distributed through food baits. We apply optimal control theory to find the best timing for distribution of vaccine in each of the linked subpopulations across the landscape. This strategy is chosen to limit the disease optimally by making the number of infections as small as possible while accounting for the cost of vaccination. PMID:18613731
The Clinical Significance of Optimality Theory for Phonological Disorders
ERIC Educational Resources Information Center
Gierut, Judith A.; Morrisette, Michele L.
2005-01-01
Linguistic theory has made important contributions to the clinical assessment and treatment of children with functional phonological disorders. In this article, Optimality Theory (OT) is introduced as a new linguistic model of grammar. Basic assumptions of the model are described and extended to clinical assessment and treatment. The aim is (1) to…
Optimal protein-folding codes from spin-glass theory.
Goldstein, R A; Luthey-Schulten, Z A; Wolynes, P G
1992-01-01
Protein-folding codes embodied in sequence-dependent energy functions can be optimized using spin-glass theory. Optimal folding codes for associative-memory Hamiltonians based on aligned sequences are deduced. A screening method based on these codes correctly recognizes protein structures in the "twilight zone" of sequence identity in the overwhelming majority of cases. Simulated annealing for the optimally encoded Hamiltonian generally leads to qualitatively correct structures. Images PMID:1594594
Optimal Discrete Event Supervisory Control of Aircraft Gas Turbine Engines
NASA Technical Reports Server (NTRS)
Litt, Jonathan (Technical Monitor); Ray, Asok
2004-01-01
This report presents an application of the recently developed theory of optimal Discrete Event Supervisory (DES) control that is based on a signed real measure of regular languages. The DES control techniques are validated on an aircraft gas turbine engine simulation test bed. The test bed is implemented on a networked computer system in which two computers operate in the client-server mode. Several DES controllers have been tested for engine performance and reliability.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Optimal selection theory for superconcurrency. Technical document
Freund, R.F.
1989-10-01
This paper describes a mathematical programming approach to finding an optimal, heterogeneous suite of processors to solve supercomputing problems. This technique, called superconcurrency, works best when the computational requirements are diverse and significant portions of the code are not tightly-coupled. It is also dependent on new methods of benchmarking and code profiling, as well as eventual use of AI techniques for intelligent management of the selected superconcurrent suite.
Approximation in control of flexible structures, theory and application
NASA Technical Reports Server (NTRS)
Gibson, J. S.
1983-01-01
The sense in which the feedback control law based on an approximate finite dimensional model of a continuous structure approximates a control law which is optimal for the distributed, or infinite dimensional, model of the structure is studied. From the analysis of the various control and stability issues associated with this basis question, useful information for designing finite dimensional compensators which produce near-optimal performance in infinite dimensional systems is gained. Some of the important predictions that can be made about large-order finite dimensional control laws, using the theory of infinite dimensional Riccati equations are indicated.
Discover for Yourself: An Optimal Control Model in Insect Colonies
ERIC Educational Resources Information Center
Winkel, Brian
2013-01-01
We describe the enlightening path of self-discovery afforded to the teacher of undergraduate mathematics. This is demonstrated as we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at…
Lie theory and control systems defined on spheres
NASA Technical Reports Server (NTRS)
Brockett, R. W.
1972-01-01
It is shown that in constructing a theory for the most elementary class of control problems defined on spheres, some results from the Lie theory play a natural role. To understand controllability, optimal control, and certain properties of stochastic equations, Lie theoretic ideas are needed. The framework considered here is the most natural departure from the usual linear system/vector space problems which have dominated control systems literature. For this reason results are compared with those previously available for the finite dimensional vector space case.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
Athans, M. (Editor); Willsky, A. S. (Editor)
1982-01-01
The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory.
Linear optimal control of tokamak fusion devices
Kessel, C.E.; Firestone, M.A.; Conn, R.W.
1989-05-01
The control of plasma position, shape and current in a tokamak fusion reactor is examined using linear optimal control. These advanced tokamaks are characterized by non up-down symmetric coils and structure, thick structure surrounding the plasma, eddy currents, shaped plasmas, superconducting coils, vertically unstable plasmas, and hybrid function coils providing ohmic heating, vertical field, radial field, and shaping field. Models of the electromagnetic environment in a tokamak are derived and used to construct control gains that are tested in nonlinear simulations with initial perturbations. The issues of applying linear optimal control to advanced tokamaks are addressed, including complex equilibrium control, choice of cost functional weights, the coil voltage limit, discrete control, and order reduction. Results indicate that the linear optimal control is a feasible technique for controlling advanced tokamaks where the more common classical control will be severely strained or will not work. 28 refs., 13 figs.
Control theory based airfoil design using the Euler equations
NASA Technical Reports Server (NTRS)
Jameson, Antony; Reuther, James
1994-01-01
This paper describes the implementation of optimization techniques based on control theory for airfoil design. In our previous work it was shown that control theory could be employed to devise effective optimization procedures for two-dimensional profiles by using the potential flow equation with either a conformal mapping or a general coordinate system. The goal of our present work is to extend the development to treat the Euler equations in two-dimensions by procedures that can readily be generalized to treat complex shapes in three-dimensions. Therefore, we have developed methods which can address airfoil design through either an analytic mapping or an arbitrary grid perturbation method applied to a finite volume discretization of the Euler equations. Here the control law serves to provide computationally inexpensive gradient information to a standard numerical optimization method. Results are presented for both the inverse problem and drag minimization problem.
Stochastic Optimally Tuned Range-Separated Hybrid Density Functional Theory.
Neuhauser, Daniel; Rabani, Eran; Cytter, Yael; Baer, Roi
2016-05-19
We develop a stochastic formulation of the optimally tuned range-separated hybrid density functional theory that enables significant reduction of the computational effort and scaling of the nonlocal exchange operator at the price of introducing a controllable statistical error. Our method is based on stochastic representations of the Coulomb convolution integral and of the generalized Kohn-Sham density matrix. The computational cost of the approach is similar to that of usual Kohn-Sham density functional theory, yet it provides a much more accurate description of the quasiparticle energies for the frontier orbitals. This is illustrated for a series of silicon nanocrystals up to sizes exceeding 3000 electrons. Comparison with the stochastic GW many-body perturbation technique indicates excellent agreement for the fundamental band gap energies, good agreement for the band edge quasiparticle excitations, and very low statistical errors in the total energy for large systems. The present approach has a major advantage over one-shot GW by providing a self-consistent Hamiltonian that is central for additional postprocessing, for example, in the stochastic Bethe-Salpeter approach. PMID:26651840
Dynamic optimization and adaptive controller design
NASA Astrophysics Data System (ADS)
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Role of controllability in optimizing quantum dynamics
Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel
2011-06-15
This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.
Network Anomaly Detection System with Optimized DS Evidence Theory
Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu
2014-01-01
Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258
Network anomaly detection system with optimized DS evidence theory.
Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu
2014-01-01
Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258
Optimizing protein representations with information theory.
Mintseris, Julian; Weng, Zhiping
2004-01-01
The problem of describing a protein representation by breaking up the amino acids atoms into functionally similar atom groups has been addressed by many researchers in the past 25 years. They have used a variety of physical, chemical and biological criteria of varying degrees of rigor to essentially impose our understanding of protein structures onto various atom-typing schemes used in studies of protein folding, protein-protein and protein-ligand interactions, and others. Here, instead, we have chosen to rely primarily on the data and use information-theoretic techniques to dissect it. We show that we can obtain an optimized protein representation for a given alphabet size from protein monomers or protein interface datasets that are in agreement with general concepts of protein energetics. Closer inspection of the atom partitions led to interesting observations pointing to the greater importance of the hydrophobic interactions in protein monomers compared to interfaces and, conversely, greater importance of polar/charged interaction in protein interfaces. Comparing the atom partitions from the two datasets we show that the two are strikingly similar at alphabet size of five, proving that despite some differences, the general energetic concepts are very similar for folding and binding. Implications for further structural studies are discussed. PMID:15712119
Optimized perturbation theory: the pion form factor
Gupta, R.
1981-10-01
The order ..cap alpha../sup 2//sub s/(Q/sup 2/) corrections to the pion form-factor F/sub ..pi../(Q/sup 2/) are calculated using perturbative QCD and dimensional regularization. The result is compared in the MS and MOM subtraction schemes and plotted as a function of Q/sup 2//Q/sup 2/ where Q is the subtraction point. There is a large dependence on the scheme, the definition of the running coupling constant ..cap alpha../sub s/(Q/sup 2/) and the subtraction point Q. We find it best to invert the ..beta..-function equation for the definition of ..cap alpha../sub s/ rather than make an expansion in powers of log(Q/sup 2//..lambda../sup 2/). We study two methods to optimize the result with respect to Q: Stevenson's prescription and putting the 0(..cap alpha../sup 2//sub s/) term to zero. Both methods give almost the same value for Q/sup 2/F/sub ..pi../ and this value is scheme independent.
Theory and practice of parallel direct optimization.
Janies, Daniel A; Wheeler, Ward C
2002-01-01
Our ability to collect and distribute genomic and other biological data is growing at a staggering rate (Pagel, 1999). However, the synthesis of these data into knowledge of evolution is incomplete. Phylogenetic systematics provides a unifying intellectual approach to understanding evolution but presents formidable computational challenges. A fundamental goal of systematics, the generation of evolutionary trees, is typically approached as two distinct NP-complete problems: multiple sequence alignment and phylogenetic tree search. The number of cells in a multiple alignment matrix are exponentially related to sequence length. In addition, the number of evolutionary trees expands combinatorially with respect to the number of organisms or sequences to be examined. Biologically interesting datasets are currently comprised of hundreds of taxa and thousands of nucleotides and morphological characters. This standard will continue to grow with the advent of highly automated sequencing and development of character databases. Three areas of innovation are changing how evolutionary computation can be addressed: (1) novel concepts for determination of sequence homology, (2) heuristics and shortcuts in tree-search algorithms, and (3) parallel computing. In this paper and the online software documentation we describe the basic usage of parallel direct optimization as implemented in the software POY (ftp://ftp.amnh.org/pub/molecular/poy). PMID:11924490
Direct Optimal Control of Duffing Dynamics
NASA Technical Reports Server (NTRS)
Oz, Hayrani; Ramsey, John K.
2002-01-01
The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.
Technology Transfer Automated Retrieval System (TEKTRAN)
Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...
An intellignet controller for optimized sootblowing
Baldridge, D.; Bangham, M.; Gratcheva, K.
1996-05-01
Efficiency losses of over 200 Btu/KWH have been attributed to sub-optimal control of sootblowers in coal-fired boilers, frequently accounting for over 80% of the controllable losses. For a 500 MW power plant, this translates into yearly costs of over $1 M. The primary impediment to sootblowing optimization to date has been the difficulty associated with modeling the relationship between sootblowing, and boiler efficiency. New advances in neural network technology now provide an attractive approach to address this issue. This paper presents results to date of a project currently under way at DHR Technologies, Inc. (DHR), George Washington University (GWU), and Baltimore Gas and Electric Company (BGE), with funding provided by the Department of Energy (DOE), to develop an Intelligent Controller for Optimized Sootblowing (ICOS). The ICOS system combines a neural network-based process model with an optimization algorithm to provide automated, optimized control of steam or compressed air sootblowers for fossil utility boilers. In Phase I of the project, the proposed optimization approach was tested and validated using data from BGE`s Brandon Shores Station. Phase I quantified the expected savings of the controller and verified the effectiveness of the proposed technical approach. In Phase II, the control algorithm will be incorporated into DHR`s TOPAZ{trademark} optimization system and interfaced with Brandon Shore`s Diamond Power sootblowing controller, and will be demonstrated and tested for closed-loop, optimal sootblowing control. The savings achieved through use of the ICOS controller during testing will also be quantified.
Parameter optimization in AQM controller design to support TCP traffic
NASA Astrophysics Data System (ADS)
Yang, Wei; Yang, Oliver W.
2004-09-01
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
Optimal torque control for SCOLE slewing maneuvers
NASA Technical Reports Server (NTRS)
Bainum, P. M.; Li, Feiyue
1987-01-01
The Spacecraft Control Laboratory Experiment (SCOLE) was slewed from one attitude to the required attitude and an integral performance index which involves the control torques was minimized. Kinematic and dynamical equations, optimal control, two-point boundary-value problems, and estimation of unknown boundary conditions are presented.
Applications of robust control theory - Educational implications
NASA Technical Reports Server (NTRS)
Dorato, P.; Yedavalli, R. K.
1992-01-01
A survey is made of applications of robust control theory to problems of flight control, control of flexible space structures, and engine control which have appeared in recent conferences and journals. An analysis is made of which theoretical techniques are most commonly used and what implications this has for graduate and undergraduate education in aerospace engineering.
Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity
Oizumi, Ryo
2014-01-01
Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258
Optimal controller design for structural damage detection
NASA Astrophysics Data System (ADS)
Lew, Jiann-Shiun
2005-03-01
The virtual passive control technique has recently been applied to structural damage detection, where the virtual passive controller only uses the existing control devices, and no additional physical elements are attached to the tested structure. One important task is to design passive controllers that can enhance the sensitivity of the identified parameters, such as natural frequencies, to structural damage. This paper presents a novel study of an optimal controller design for structural damage detection. We apply not only passive controllers but also low-order and fixed-structure controllers, such as PID controllers. In the optimal control design, the performance of structural damage detection is based on the application of a neural network technique, which uses the pattern of the correlation between the natural frequency changes of the tested system and the damaged system.
Linear quadratic optimal controller for cable-driven parallel robots
NASA Astrophysics Data System (ADS)
Abdolshah, Saeed; Shojaei Barjuei, Erfan
2015-12-01
In recent years, various cable-driven parallel robots have been investigated for their advantages, such as low structural weight, high acceleration, and large work-space, over serial and conventional parallel systems. However, the use of cables lowers the stiffness of these robots, which in turn may decrease motion accuracy. A linear quadratic (LQ) optimal controller can provide all the states of a system for the feedback, such as position and velocity. Thus, the application of such an optimal controller in cable-driven parallel robots can result in more efficient and accurate motion compared to the performance of classical controllers such as the proportional- integral-derivative controller. This paper presents an approach to apply the LQ optimal controller on cable-driven parallel robots. To employ the optimal control theory, the static and dynamic modeling of a 3-DOF planar cable-driven parallel robot (Feriba-3) is developed. The synthesis of the LQ optimal control is described, and the significant experimental results are presented and discussed.
Discrete Mechanics and Optimal Control for Space Trajectory Design
NASA Astrophysics Data System (ADS)
Moore, Ashley
Space trajectory design is often achieved through a combination of dynamical systems theory and optimal control. The union of trajectory design techniques utilizing invariant manifolds of the planar circular restricted three-body problem and the optimal control scheme Discrete Mechanics and Optimal Control (DMOC) facilitates the design of low-energy trajectories in the N-body problem. In particular, DMOC is used to optimize a trajectory from the Earth to the Moon in the 4-body problem, removing the mid-course change in velocity, Delta V, usually necessary for such a trajectory while still exploiting the structure from the invariant manifolds. This thesis also focuses on how to adapt DMOC, a method devised with a constant step size, for the highly nonlinear dynamics involved in trajectory design. Mesh refinement techniques that aim to reduce discretization errors in the solution and energy evolution and their effect on DMOC optimization are explored and compared with trajectories created using time adaptive variational integrators. Furthermore, a time adaptive form of DMOC is developed that allows for a variable step size that is updated throughout the optimization process. Time adapted DMOC is based on a discretization of Hamilton's principle applied to the time adapted Lagrangian of the optimal control problem. Variations of the discrete action of the optimal control Lagrangian lead to discrete Euler-Lagrange equations that can be enforced as constraints for a boundary value problem. This new form of DMOC leads to the accurate and efficient solution of optimal control problems with highly nonlinear dynamics. Time adapted DMOC is tested on several space trajectory problems including the elliptical orbit transfer in the 2-body problem and the reconfiguration of a cubesat.
Optimal control of systems with capacity: Related noises
NASA Technical Reports Server (NTRS)
Ruan, Milfang; Choudhury, Ajit K.
1991-01-01
In the ordinary theory of optimal control (LQR and Kalman filter), the variances of the actuators and the sensors are assumed to be known (not related to the capacities of the devices). This assumption is not true in practice. Generally, a device with greater capacity to exert actuating forces and a sensor capable of sensing greater sensing range will generate noise of greater power spectral density. When the ordinary theory of optimal control is used to estimate the errors of the outputs in such cases it will lead to faulty results, because the capacities of such devices are unknown before the system is designed. The performance of the system designed by the ordinary theory will not be optimal as the variances of the sensors and the actuators are neither known nor constant. The interaction between the control system and structure could be serious because the ordinary method will lead to greater feedback (Kalman gain) matrices. Methods which can optimize the performance of systems when noises of the actuators and the sensors are related to their capacities are developed. These methods will result in smaller feedback (Kalman gain) matrix.
Modal insensitivity with optimality. [in feedback control
NASA Technical Reports Server (NTRS)
Calise, A. J.; Raman, K. V.
1984-01-01
This paper deals with the design of a constant gain, feedback controller which results in selected modal insensitivity, and at the same time optimizes a quadratic performance index representative of desired system performance for nominal plant parameter values. Both full state and output feedback control are considered. A constraint is established for the feedback gain matrix that results in modal insensitivity, and necessary conditions for optimality subject to this constraint are given. This forms the basis for a numerical algorithm to compute the optimal feedback gain. To illustrate the procedure, a design is carried out using the lateral dynamics of an L-1011 aircraft.
"Cruel Optimism" and Contemporary Australian Critical Theory in Educational Research
ERIC Educational Resources Information Center
Rasmussen, Mary Lou
2015-01-01
"Cruel optimism" is a term coined by Lauren Berlant. In conceptualizing this term, Berlant draws on the resources of critical theory to interrogate people's desires for things they think may improve their lot, but actually act as obstacles to flourishing. This notion may be useful for analysing the current state of education in…
Evaluating Student Assessments: The Use of Optimal Foraging Theory
ERIC Educational Resources Information Center
Whalley, W. Brian
2016-01-01
The concepts of optimal foraging theory and the marginal value theorem are used to investigate possible student behaviour in accruing marks in various forms of assessment. The ideas of predator energy consumption, handling and search times can be evaluated in terms of student behaviour and gaining marks or "attainment". These ideas can…
Stochastic Optimal Control via Bellman's Principle
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Sun, Jian Q.
2003-01-01
This paper presents a method for finding optimal controls of nonlinear systems subject to random excitations. The method is capable to generate global control solutions when state and control constraints are present. The solution is global in the sense that controls for all initial conditions in a region of the state space are obtained. The approach is based on Bellman's Principle of optimality, the Gaussian closure and the Short-time Gaussian approximation. Examples include a system with a state-dependent diffusion term, a system in which the infinite hierarchy of moment equations cannot be analytically closed, and an impact system with a elastic boundary. The uncontrolled and controlled dynamics are studied by creating a Markov chain with a control dependent transition probability matrix via the Generalized Cell Mapping method. In this fashion, both the transient and stationary controlled responses are evaluated. The results show excellent control performances.
Application of the general problem of moments to some optimization problems in elasticity theory
NASA Astrophysics Data System (ADS)
Grigoliuk, E. I.; Fil'Shtinskii, V. A.; Fil'Shtinskii, L. A.
1992-04-01
Several optimization problems in elasticity theory are formulated which are relevant to geomechanics. Methods are then presented for reducing these problems to general moment problems in continuous-function space. By using polynomial approximations of nonstandard moment functions, the general moment problems are reduced to the classical power-law moment problem. This allows an a priori evaluation of the optimal control structure. Theoretical and computational examples are presented.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1986-01-01
The utility of augmenting displays to aid the human operator in controlling high order complex systems is well known. Analytical evaluation of various display designs for a simple k/s sup 2 plant in a compensatory tracking task using an optimal Control Model (OCM) of human behavior is carried out. This analysis reveals that significant improvement in performance should be obtained by skillful integration of key information into the display dynamics. The cooperative control synthesis technique previously developed to design pilot-optimal control augmentation is extended to incorporate the simultaneous design of performance enhancing augmented displays. The application of the cooperative control synthesis technique to the design of augmented displays is discussed for the simple k/s sup 2 plant. This technique is intended to provide a systematic approach to design optimally augmented displays tailored for specific tasks.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1985-01-01
A technique is developed that is intended to provide a systematic approach to synthesizing display augmentation for optimal manual control in complex, closed-loop tasks. A cooperative control synthesis technique, previously developed to design pilot-optimal control augmentation for the plant, is extended to incorporate the simultaneous design of performance enhancing displays. The technique utilizes an optimal control model of the man in the loop. It is applied to the design of a quickening control law for a display and a simple K/s(2) plant, and then to an F-15 type aircraft in a multi-channel task. Utilizing the closed loop modeling and analysis procedures, the results from the display design algorithm are evaluated and an analytical validation is performed. Experimental validation is recommended for future efforts.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Gary, Sanjay; Schmidt, David K.
1987-01-01
A technique is developed that is intended to provide a systematic approach to synthesizing display augmentation for optimal manual control in complex, closed-loop tasks. A cooperative control synthesis technique, previously developed to design pilot-optimal control augmentation for the plant, is extended to incorporate the simultaneous design of performance enhancing displays. The technique utilizes an optimal control model of the man in the loop. It is applied to the design of a quickening control law for a display and a simple K/(s squared) plant, and then to an F-15 type aircraft in a multichannel task. Utilizing the closed-loop modeling and analysis procedures, the results from the display design algorithm are evaluated and an analytical validation is performed. Experimental validation is recommended for future efforts.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1985-01-01
The utility of augmenting displays to aid the human operator in controlling high order complex systems is well known. Analytical evaluations of various display designs for a simple k/s-squared plant in a compensatory tracking task using an Optimal Control Model (OCM) of human behavior is carried out. This analysis reveals that significant improvement in performance should be obtained by skillful integration of key information into the display dynamics. The cooperative control synthesis technique previously developed to design pilot-optimal control augmentation is extended to incorporate the simultaneous design of performance enhancing augmented displays. The application of the cooperative control synthesis technique to the design of augmented displays is discussed for the simple k/s-squared plant. This technique is intended to provide a systematic approach to design optimally augmented displays tailored for specific tasks.
Role of control constraints in quantum optimal control
NASA Astrophysics Data System (ADS)
Zhdanov, Dmitry V.; Seideman, Tamar
2015-11-01
The problems of optimizing the value of an arbitrary observable of a two-level system at both a fixed time and the shortest possible time is theoretically explored. Complete identification and classification along with comprehensive analysis of globally optimal control policies and traps (i.e., policies which are locally but not globally optimal) are presented. The central question addressed is whether the control landscape remains trap-free if control constraints of the inequality type are imposed. The answer is astonishingly controversial: Although the traps are proven always to exist in this case, in practice they become trivially escapable once the control time is fixed and chosen long enough.
Lagrange duality theory for convex control problems
NASA Technical Reports Server (NTRS)
Hager, W. W.; Mitter, S. K.
1976-01-01
The Lagrange dual to a control problem is studied. The principal result based on the Hahn-Banach theorem proves that the dual problem has an optimal solution if there exists an interior point for the constraint set. A complementary slackness condition holds, if the primal problem has an optimal solution. A necessary and sufficient condition for the optimality of solutions to the primal and the dual problem is also presented.
A Danger-Theory-Based Immune Network Optimization Algorithm
Li, Tao; Xiao, Xin; Shi, Yuanquan
2013-01-01
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853
Kalman meets neuron - the intersection of control theory and neuroscience
NASA Astrophysics Data System (ADS)
Schiff, Steven
2009-03-01
Since the 1950s, we have developed mature theories of modern control theory and computational neuroscience with almost no interaction between these disciplines. With the advent of computationally efficient nonlinear Kalman filtering techniques, along with improved neuroscience models which provide increasingly accurate reconstruction of dynamics in a variety of important normal and disease states in the brain, the prospects for a synergistic interaction between these fields are now strong. I will show recent examples of the use of nonlinear control theory for the assimilation and control of single neuron dynamics, a novel framework for dynamic clamp, the modulation of oscillatory wave dynamics in brain cortex, a control framework for Parkinsonian dynamics and seizures, and the use of optimized parameter model networks to assimilate complex network data.
A reliable algorithm for optimal control synthesis
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1992-01-01
In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.
Optimal-transport formulation of electronic density-functional theory
NASA Astrophysics Data System (ADS)
Buttazzo, Giuseppe; De Pascale, Luigi; Gori-Giorgi, Paola
2012-06-01
The most challenging scenario for Kohn-Sham density-functional theory, that is, when the electrons move relatively slowly trying to avoid each other as much as possible because of their repulsion (strong-interaction limit), is reformulated here as an optimal transport (or mass transportation theory) problem, a well-established field of mathematics and economics. In practice, we show that to solve the problem of finding the minimum possible internal repulsion energy for N electrons in a given density ρ(r) is equivalent to find the optimal way of transporting N-1 times the density ρ into itself, with the cost function given by the Coulomb repulsion. We use this link to set the strong-interaction limit of density-functional theory on firm ground and to discuss the potential practical aspects of this reformulation.
OPTIMAL CONTROL THEORY FOR SUSTAINABLE ENVIRONMENTAL MANAGEMENT
With growing world population, diminishing resources, and realization of the harmful effects of various pollutants, research focus in environmental management has shifted towards sustainability. The goal of a sustainable management strategy is to promote the structure and operati...
Control theory for random systems
NASA Technical Reports Server (NTRS)
Bryson, A. E., Jr.
1972-01-01
A survey is presented of the current knowledge available for designing and predicting the effectiveness of controllers for dynamic systems which can be modeled by ordinary differential equations. A short discussion of feedback control is followed by a description of deterministic controller design and the concept of system state. The need for more realistic disturbance models led to the use of stochastic process concepts, in particular the Gauss-Markov process. A compensator controlled system, with random forcing functions, random errors in the measurements, and random initial conditions, is treated as constituting a Gauss-Markov random process; hence the mean-square behavior of the controlled system is readily predicted. As an example, a compensator is designed for a helicopter to maintain it in hover in a gusty wind over a point on the ground.
Time optimal feedback control of discrete systems with bounded inputs
NASA Technical Reports Server (NTRS)
Chen, Xin; Longman, Richard W.; Klein, George
1990-01-01
Deadbeat control theory gives a feedback solution to the time optimal control of discrete time systems. Experience has shown the results to be impractical because they ignore bounds on the actuator strength. This paper develops two algorithms for generating time optimal control in feedback form for discrete systems with bounded controls. The results are also applicable for generating recovery regions and the set of reachable states. For multiple control problems a method of generating sublayers is developed which decreases off-line and on-line computational effort. Two algorithms are presented with somewhat different computational and storage requirements. The algorithms are practical within certain dimension constraints, and are natural for implementation with parallel processing.
Genetic optimization of fuzzy fractional PD+I controllers.
Jesus, Isabel S; Barbosa, Ramiro S
2015-07-01
Fractional order calculus is a powerful emerging mathematical tool in science and engineering. There is currently an increasing interest in generalizing classical control theories and developing novel control strategies. The genetic algorithms (GA) are a stochastic search and optimization methods based on the reproduction processes found in biological systems, used for solving engineering problems. In the context of process control, the fuzzy logic usually means variables that are described by imprecise terms, and represented by quantities that are qualitative and vague. In this article we consider the development of an optimal fuzzy fractional PD+I controller in which the parameters are tuned by a GA. The performance of the proposed fuzzy fractional control is illustrated through some application examples. PMID:25661162
Product Distribution Theory for Control of Multi-Agent Systems
NASA Technical Reports Server (NTRS)
Lee, Chia Fan; Wolpert, David H.
2004-01-01
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.
Control theory meets synthetic biology.
Del Vecchio, Domitilla; Dy, Aaron J; Qian, Yili
2016-07-01
The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology. PMID:27440256
Control theory meets synthetic biology
2016-01-01
The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology. PMID:27440256
OPTIMIZATION OF COMBINED SEWER OVERFLOW CONTROL SYSTEMS
The highly variable and intermittent pollutant concentrations and flowrates associated with wet-weather events in combined sewersheds necessitates the use of storage-treatment systems to control pollution.An optimized combined-sewer-overflow (CSO) control system requires a manage...
Centralized Stochastic Optimal Control of Complex Systems
Malikopoulos, Andreas
2015-01-01
In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
Algorithm For Optimal Control Of Large Structures
NASA Technical Reports Server (NTRS)
Salama, Moktar A.; Garba, John A..; Utku, Senol
1989-01-01
Cost of computation appears competitive with other methods. Problem to compute optimal control of forced response of structure with n degrees of freedom identified in terms of smaller number, r, of vibrational modes. Article begins with Hamilton-Jacobi formulation of mechanics and use of quadratic cost functional. Complexity reduced by alternative approach in which quadratic cost functional expressed in terms of control variables only. Leads to iterative solution of second-order time-integral matrix Volterra equation of second kind containing optimal control vector. Cost of algorithm, measured in terms of number of computations required, is of order of, or less than, cost of prior algoritms applied to similar problems.
Geometrically constrained observability. [control theory
NASA Technical Reports Server (NTRS)
Brammer, R. F.
1974-01-01
This paper deals with observed processes in situations in which observations are available only when the state vector lies in certain regions. For linear autonomous observed processes, necessary and sufficient conditions are obtained for half-space observation regions. These results are shown to contain a theorem dual to a controllability result proved by the author for a linear autonomous control system whose control restraint set does not contain the origin as an interior point. Observability results relating to continuous observation systems and sampled data systems are presented, and an example of observing the state of an electrical network is given.
Optimization through quantum annealing: theory and some applications
NASA Astrophysics Data System (ADS)
Battaglia, D. A.; Stella, L.
2006-08-01
Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional (classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing highlighting the crucial differences between these two methods by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems (namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.
Monotonically convergent optimization in quantum control using Krotov's method
Reich, Daniel M.; Koch, Christiane P.; Ndong, Mamadou
2012-03-14
The non-linear optimization method developed by A. Konnov and V. Krotov [Autom. Remote Cont. (Engl. Transl.) 60, 1427 (1999)] has been used previously to extend the capabilities of optimal control theory from the linear to the non-linear Schroedinger equation [S. E. Sklarz and D. J. Tannor, Phys. Rev. A 66, 053619 (2002)]. Here we show that based on the Konnov-Krotov method, monotonically convergent algorithms are obtained for a large class of quantum control problems. It includes, in addition to nonlinear equations of motion, control problems that are characterized by non-unitary time evolution, nonlinear dependencies of the Hamiltonian on the control, time-dependent targets, and optimization functionals that depend to higher than second order on the time-evolving states. We furthermore show that the nonlinear (second order) contribution can be estimated either analytically or numerically, yielding readily applicable optimization algorithms. We demonstrate monotonic convergence for an optimization functional that is an eighth-degree polynomial in the states. For the ''standard'' quantum control problem of a convex final-time functional, linear equations of motion and linear dependency of the Hamiltonian on the field, the second-order contribution is not required for monotonic convergence but can be used to speed up convergence. We demonstrate this by comparing the performance of first- and second-order algorithms for two examples.
Applications of fuzzy theories to multi-objective system optimization
NASA Technical Reports Server (NTRS)
Rao, S. S.; Dhingra, A. K.
1991-01-01
Most of the computer aided design techniques developed so far deal with the optimization of a single objective function over the feasible design space. However, there often exist several engineering design problems which require a simultaneous consideration of several objective functions. This work presents several techniques of multiobjective optimization. In addition, a new formulation, based on fuzzy theories, is also introduced for the solution of multiobjective system optimization problems. The fuzzy formulation is useful in dealing with systems which are described imprecisely using fuzzy terms such as, 'sufficiently large', 'very strong', or 'satisfactory'. The proposed theory translates the imprecise linguistic statements and multiple objectives into equivalent crisp mathematical statements using fuzzy logic. The effectiveness of all the methodologies and theories presented is illustrated by formulating and solving two different engineering design problems. The first one involves the flight trajectory optimization and the main rotor design of helicopters. The second one is concerned with the integrated kinematic-dynamic synthesis of planar mechanisms. The use and effectiveness of nonlinear membership functions in fuzzy formulation is also demonstrated. The numerical results indicate that the fuzzy formulation could yield results which are qualitatively different from those provided by the crisp formulation. It is felt that the fuzzy formulation will handle real life design problems on a more rational basis.
Optimal integral controller with sensor failure accommodation
NASA Technical Reports Server (NTRS)
Alberts, T.; Houlihan, T.
1989-01-01
An Optimal Integral Controller that readily accommodates Sensor Failure - without resorting to (Kalman) filter or observer generation - has been designed. The system is based on Navy-sponsored research for the control of high performance aircraft. In conjunction with a NASA developed Numerical Optimization Code, the Integral Feedback Controller will provide optimal system response even in the case of incomplete state feedback. Hence, the need for costly replication of plant sensors is avoided since failure accommodation is effected by system software reconfiguration. The control design has been applied to a particularly ill-behaved, third-order system. Dominant-root design in the classical sense produced an almost 100 percent overshoot for the third-order system response. An application of the newly-developed Optimal Integral Controller - assuming all state information available - produces a response with no overshoot. A further application of the controller design - assuming a one-third sensor failure scenario - produced a slight overshoot response that still preserved the steady state time-point of the full-state feedback response. The control design should have wide application in space systems.
Advanced rotorcraft control using parameter optimization
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1991-01-01
A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.
Solving inverse problems of identification type by optimal control methods
Lenhart, S.; Protopopescu, V.; Yong, J.
1997-05-01
Inverse problems of identification type for nonlinear equations are considered within the framework of optimal control theory. The rigorous solution of any particular problem depends on the functional setting, type of equation, and unknown quantity (or quantities) to be determined. Here we present only the general articulations of the formalism. Compared to classical regularization methods (e.g. Tikhonov coupled with optimization schemes), our approach presents several advantages, namely: (i) a systematic procedure to solve inverse problems of identification type; (ii) an explicit expression for the approximations of the solution; and (iii) a convenient numerical solution of these approximations. {copyright} {ital 1997 American Institute of Physics.}
Solving inverse problems of identification type by optimal control methods
Lenhart, S.; Protopopescu, V.; Jiongmin Yong
1997-06-01
Inverse problems of identification type for nonlinear equations are considered within the framework of optimal control theory. The rigorous solution of any particular problem depends on the functional setting, type of equation, and unknown quantity (or quantities) to be determined. Here the authors present only the general articulations of the formalism. Compared to classical regularization methods (e.g. Tikhonov coupled with optimization schemes), their approach presents several advantages, namely: (i) a systematic procedure to solve inverse problems of identification type; (ii) an explicit expression for the approximations of the solution; and (iii) a convenient numerical solution of these approximations.
Optimal control for Rydberg quantum technology building blocks
NASA Astrophysics Data System (ADS)
Müller, Matthias M.; Pichler, Thomas; Montangero, Simone; Calarco, Tommaso
2016-04-01
We consider a platform for quantum technology based on Rydberg atoms in optical lattices where each atom encodes one qubit of information and external lasers can manipulate their state. We demonstrate how optimal control theory enables the functioning of two specific building blocks on this platform: We engineer an optimal protocol to perform a two-qubit phase gate and to transfer the information within the lattice among specific sites. These two elementary operations allow to design very general operations like storage of atoms and entanglement purification as, for example, needed for quantum repeaters.
Stochastic time-optimal control problems
NASA Technical Reports Server (NTRS)
Zhang, W.; Elliot, D.
1988-01-01
Two types of stochastic time-optimal controls in a one-dimensional setting are considered. Multidimensional problems, in the case of complete state information available and the system modeled by stochastic differential equations, are studied under the formulation of minimizing the expected transient-response time. The necessary condition of optimality is the satisfaction for the value function of a parabolic partial differential equation with boundary conditions. The sufficient condition of optimality is also provided, based on Dynkin's formula. Finally, three examples are given.
Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels
NASA Technical Reports Server (NTRS)
Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.
2011-01-01
We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.
Road map to adaptive optimal control. [jet engine control
NASA Technical Reports Server (NTRS)
Boyer, R.
1980-01-01
A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.
Development of a digital adaptive optimal linear regulator flight controller
NASA Technical Reports Server (NTRS)
Berry, P.; Kaufman, H.
1975-01-01
Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.
Optimal active control for Burgers equations
NASA Technical Reports Server (NTRS)
Ikeda, Yutaka
1994-01-01
A method for active fluid flow control based on control theory is discussed. Dynamic programming and fixed point successive approximations are used to accommodate the nonlinear control problem. The long-term goal of this project is to establish an effective method applicable to complex flows such as turbulence and jets. However, in this report, the method is applied to stochastic Burgers equation as an intermediate step towards this goal. Numerical results are compared with those obtained by gradient search methods.
Multimodel methods for optimal control of aeroacoustics.
Chen, Guoquan; Collis, Samuel Scott
2005-01-01
A new multidomain/multiphysics computational framework for optimal control of aeroacoustic noise has been developed based on a near-field compressible Navier-Stokes solver coupled with a far-field linearized Euler solver both based on a discontinuous Galerkin formulation. In this approach, the coupling of near- and far-field domains is achieved by weakly enforcing continuity of normal fluxes across a coupling surface that encloses all nonlinearities and noise sources. For optimal control, gradient information is obtained by the solution of an appropriate adjoint problem that involves the propagation of adjoint information from the far-field to the near-field. This computational framework has been successfully applied to study optimal boundary-control of blade-vortex interaction, which is a significant noise source for helicopters on approach to landing. In the model-problem presented here, the noise propagated toward the ground is reduced by 12dB.
New optimal polynomial theory for NN-scattering
Rijken, T A; Signell, P
1980-01-01
A new optimal polynomial theory for nucleon-nucleon scattering is presented. For the first time in nucleon-nucleon scattering, the derivative amplitudes originally introduced by Fubini, Furlan, and Rosetti are applied. Based on the properties of these amplitudes we introduce K-matrix functions which have suitable analyticity properties as functions of cos theta, where theta is the center of mass scattering angle. The K-matrix functions enable introduction of a new set of functions for which the optimal mapping techniques of Cutkosky, Deo and Ciulli can be applied. Results are shown for proton-proton phase shift analyses at 210 and 330 MeV.
Quantum optimal control of photoelectron spectra and angular distributions
NASA Astrophysics Data System (ADS)
Goetz, R. Esteban; Karamatskou, Antonia; Santra, Robin; Koch, Christiane P.
2016-01-01
Photoelectron spectra and photoelectron angular distributions obtained in photoionization reveal important information on, e.g., charge transfer or hole coherence in the parent ion. Here we show that optimal control of the underlying quantum dynamics can be used to enhance desired features in the photoelectron spectra and angular distributions. To this end, we combine Krotov's method for optimal control theory with the time-dependent configuration interaction singles formalism and a splitting approach to calculate photoelectron spectra and angular distributions. The optimization target can account for specific desired properties in the photoelectron angular distribution alone, in the photoelectron spectrum, or in both. We demonstrate the method for hydrogen and then apply it to argon under strong XUV radiation, maximizing the difference of emission into the upper and lower hemispheres, in order to realize directed electron emission in the XUV regime.
Optimal control strategy for abnormal innate immune response.
Tan, Jinying; Zou, Xiufen
2015-01-01
Innate immune response plays an important role in control and clearance of pathogens following viral infection. However, in the majority of virus-infected individuals, the response is insufficient because viruses are known to use different evasion strategies to escape immune response. In this study, we use optimal control theory to investigate how to control the innate immune response. We present an optimal control model based on an ordinary-differential-equation system from a previous study, which investigated the dynamics and regulation of virus-triggered innate immune signaling pathways, and we prove the existence of a solution to the optimal control problem involving antiviral treatment or/and interferon therapy. We conduct numerical experiments to investigate the treatment effects of different control strategies through varying the cost function and control efficiency. The results show that a separate treatment, that is, only inhibiting viral replication (u1(t)) or enhancing interferon activity (u2(t)), has more advantages for controlling viral infection than a mixed treatment, that is, controlling both (u1(t)) and (u2(t)) simultaneously, including the smallest cost and operability. These findings would provide new insight for developing effective strategies for treatment of viral infectious diseases. PMID:25949271
Quadratic optimal cooperative control synthesis with flight control application
NASA Technical Reports Server (NTRS)
Schmidt, D. K.; Innocenti, M.
1984-01-01
An optimal control-law synthesis approach is presented that involves simultaneous solution for two cooperating controllers operating in parallel. One controller's structure includes stochastic state estimation and linear feedback of the state estimates, while the other controller involves direct linear feedback of selected system output measurements. This structure is shown to be optimal under the constraint of linear feedback of system outputs in one controller. Furthermore, it is appropriate for flight control synthesis where the full-state optimal stochastic controller can be adjusted to be representative of an optimal control model of the human pilot in a stochastic regulation task. The method is experimentally verified in the case of the selection of pitch-damper gain for optimum pitch tracking, where optimum implies the best subjective pilot rating in the task. Finally, results from application of the method to synthesize a controller for a multivariable fighter aircraft are presented, and implications of the results of this method regarding the optimal plant dynamics for tracking are discussed.
Range optimized theory of electron liquids with application to jellium
NASA Astrophysics Data System (ADS)
Donley, James; Pryor, Craig
2015-03-01
A simple optimization scheme is used to compute the density-density response function of the 3-D homogeneous electron gas at zero temperature. Higher order terms in the perturbation expansion beyond the random phase approximation are summed approximately by enforcing the constraint that the spin density radial distribution functions be positive. Quantitative comparison is made with previous theory and data from quantum Monte Carlo simulation. Agreement with the available simulation data is good for the entire paramagnetic region. Generalization of the theory to inhomogeneous electron liquids such as in semiconductors will be discussed.
An information theory account of cognitive control
Fan, Jin
2014-01-01
Our ability to efficiently process information and generate appropriate responses depends on the processes collectively called cognitive control. Despite a considerable focus in the literature on the cognitive control of information processing, neural mechanisms underlying control are still unclear, and have not been characterized by considering the quantity of information to be processed. A novel and comprehensive account of cognitive control is proposed using concepts from information theory, which is concerned with communication system analysis and the quantification of information. This account treats the brain as an information-processing entity where cognitive control and its underlying brain networks play a pivotal role in dealing with conditions of uncertainty. This hypothesis and theory article justifies the validity and properties of such an account and relates experimental findings to the frontoparietal network under the framework of information theory. PMID:25228875
Integration of Large-Scale Optimization and Game Theory for Sustainable Water Quality Management
NASA Astrophysics Data System (ADS)
Tsao, J.; Li, J.; Chou, C.; Tung, C.
2009-12-01
Sustainable water quality management requires total mass control in pollutant discharge based on both the principles of not exceeding assimilative capacity in a river and equity among generations. The stream assimilative capacity is the carrying capacity of a river for the maximum waste load without violating the water quality standard and the spirit of total mass control is to optimize the waste load allocation in subregions. For the goal of sustainable watershed development, this study will use large-scale optimization theory to optimize the profit, and find the marginal values of loadings as reference of the fair price and then the best way to get the equilibrium by water quality trading for the whole of watershed will be found. On the other hand, game theory plays an important role to maximize both individual and entire profits. This study proves the water quality trading market is available in some situation, and also makes the whole participants get a better outcome.
Mathematical theory of a relaxed design problem in structural optimization
NASA Technical Reports Server (NTRS)
Kikuchi, Noboru; Suzuki, Katsuyuki
1990-01-01
Various attempts have been made to construct a rigorous mathematical theory of optimization for size, shape, and topology (i.e. layout) of an elastic structure. If these are represented by a finite number of parametric functions, as Armand described, it is possible to construct an existence theory of the optimum design using compactness argument in a finite dimensional design space or a closed admissible set of a finite dimensional design space. However, if the admissible design set is a subset of non-reflexive Banach space such as L(sup infinity)(Omega), construction of the existence theory of the optimum design becomes suddenly difficult and requires to extend (i.e. generalize) the design problem to much more wider class of design that is compatible to mechanics of structures in the sense of variational principle. Starting from the study by Cheng and Olhoff, Lurie, Cherkaev, and Fedorov introduced a new concept of convergence of design variables in a generalized sense and construct the 'G-Closure' theory of an extended (relaxed) optimum design problem. A similar attempt, but independent in large extent, can also be found in Kohn and Strang in which the shape and topology optimization problem is relaxed to allow to use of perforated composites rather than restricting it to usual solid structures. An identical idea is also stated in Murat and Tartar using the notion of the homogenization theory. That is, introducing possibility of micro-scale perforation together with the theory of homogenization, the optimum design problem is relaxed to construct its mathematical theory. It is also noted that this type of relaxed design problem is perfectly matched to the variational principle in structural mechanics.
Integrated control-system design via generalized LQG (GLQG) theory
NASA Technical Reports Server (NTRS)
Bernstein, Dennis S.; Hyland, David C.; Richter, Stephen; Haddad, Wassim M.
1989-01-01
Thirty years of control systems research has produced an enormous body of theoretical results in feedback synthesis. Yet such results see relatively little practical application, and there remains an unsettling gap between classical single-loop techniques (Nyquist, Bode, root locus, pole placement) and modern multivariable approaches (LQG and H infinity theory). Large scale, complex systems, such as high performance aircraft and flexible space structures, now demand efficient, reliable design of multivariable feedback controllers which optimally tradeoff performance against modeling accuracy, bandwidth, sensor noise, actuator power, and control law complexity. A methodology is described which encompasses numerous practical design constraints within a single unified formulation. The approach, which is based upon coupled systems or modified Riccati and Lyapunov equations, encompasses time-domain linear-quadratic-Gaussian theory and frequency-domain H theory, as well as classical objectives such as gain and phase margin via the Nyquist circle criterion. In addition, this approach encompasses the optimal projection approach to reduced-order controller design. The current status of the overall theory will be reviewed including both continuous-time and discrete-time (sampled-data) formulations.
Sensitivity of optimal control systems with bang-bang control.
NASA Technical Reports Server (NTRS)
Rootenberg, J.; Courtin, P.
1973-01-01
The effects of small parameter variations on the performance index of optimal control systems with initial and final target manifolds, free end time, and bang-bang control are analyzed in this paper. A new approach to the sensitivity equation is presented. This approach takes into account the pulse-shaped variation produced by the parameter change on the bang-bang control. An expression, that relates the variations of the performance index, the trajectory, the final time, and the parameter, is derived. This expression extends to the class of optimal systems with bang-bang control, a result previously obtained by Courtin and Rootenberg (1971).
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. PMID:26407644
Linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1980-01-01
Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.
Optimally Controlled Flexible Fuel Powertrain System
Hakan Yilmaz; Mark Christie; Anna Stefanopoulou
2010-12-31
The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.
RESOURCES ALLOCATION TO OPTIMIZE MINING POLLUTION CONTROL
A comprehensive model for mine drainage simulation and optimization of resource allocation to control mine acid pollution in a watershed has been developed. The model is capable of: (a) Producing a time trace of acid load and flow from acid drainage sources as a function of clima...
Optimal decentralized control for multimachine power systems--
Quali, A. ); Fantin, J. )
1989-01-01
This paper provides a method for determining an optimal decentralized control for multimachine power systems with quadratic performance measure. An iterative algorithm is developed whereby a local minimum is attained. The constraint of decentralization is tackled with in minimization algorithm by using the method of feasible directions. An example of three synchronous machines is given to illustrate the proposed algorithm.
Optimal control solutions to sodic soil reclamation
NASA Astrophysics Data System (ADS)
Mau, Yair; Porporato, Amilcare
2016-05-01
We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang-bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang-bang solution is also shown to work for the reclamation of other soil conditions, such as saline-sodic soils. The novelty in our modeling approach is the capability of searching the entire "strategy space" for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities.
Research on optimal control, stabilization and computational algorithms for aerospace applications
NASA Technical Reports Server (NTRS)
Athans, M.
1985-01-01
The research carried out in the areas of optimal control and estimation theory and its applications under this grant is reviewed. A listing of the 257 publications that document the research results is presented.
Research on optimal control, stabilization and computational algorithms for aerospace applications
NASA Technical Reports Server (NTRS)
Athans, M.
1984-01-01
The research carried out in the areas of optimal control and estimation theory and its applications under this grant is reviewed. A listing of the 257 publications that document the research results is presented.
Optimal singular control for nonlinear semistabilisation
NASA Astrophysics Data System (ADS)
L'Afflitto, Andrea; Haddad, Wassim M.
2016-06-01
The singular optimal control problem for asymptotic stabilisation has been extensively studied in the literature. In this paper, the optimal singular control problem is extended to address a weaker version of closed-loop stability, namely, semistability, which is of paramount importance for consensus control of network dynamical systems. Three approaches are presented to address the nonlinear semistable singular control problem. Namely, a singular perturbation method is presented to construct a state-feedback singular controller that guarantees closed-loop semistability for nonlinear systems. In this approach, we show that for a non-negative cost-to-go function the minimum cost of a nonlinear semistabilising singular controller is lower than the minimum cost of a singular controller that guarantees asymptotic stability of the closed-loop system. In the second approach, we solve the nonlinear semistable singular control problem by using the cost-to-go function to cancel the singularities in the corresponding Hamilton-Jacobi-Bellman equation. For this case, we show that the minimum value of the singular performance measure is zero. Finally, we provide a framework based on the concepts of state-feedback linearisation and feedback equivalence to solve the singular control problem for semistabilisation of nonlinear dynamical systems. For this approach, we also show that the minimum value of the singular performance measure is zero. Three numerical examples are presented to demonstrate the efficacy of the proposed singular semistabilisation frameworks.
Application of modern control theory to the design of optimum aircraft controllers
NASA Technical Reports Server (NTRS)
Power, L. J.
1973-01-01
A procedure is described for synthesis of optimal aircraft control systems by application of the concepts of optimal control theory to time-invariant linear systems with quadratic performance criteria. Essential in this synthesis procedure is the solution of the Riccati matrix equation which results in a constant linear feedback control law for an output regulator which maintains a plant in an equilibrium in the presence of impulse disturbances. An algorithm is derived for designing maneuverable output regulators with selected state variables for feedback.
Optimization for efficient structure-control systems
NASA Technical Reports Server (NTRS)
Oz, Hayrani; Khot, Narendra S.
1993-01-01
The efficiency of a structure-control system is a nondimensional parameter which indicates the fraction of the total control power expended usefully in controlling a finite-dimensional system. The balance of control power is wasted on the truncated dynamics serving no useful purpose towards the control objectives. Recently, it has been demonstrated that the concept of efficiency can be used to address a number of control issues encountered in the control of dynamic systems such as the spillover effects, selection of a good input configuration and obtaining reduced order control models. Reference (1) introduced the concept and presented analyses of several Linear Quadratic Regulator designs on the basis of their efficiencies. Encouraged by the results of Ref. (1), Ref. (2) introduces an efficiency modal analysis of a structure-control system which gives an internal characterization of the controller design and establishes the link between the control design and the initial disturbances to affect efficient structure-control system designs. The efficiency modal analysis leads to identification of principal controller directions (or controller modes) distinct from the structural natural modes. Thus ultimately, many issues of the structure-control system revolve around the idea of insuring compatibility of the structural modes and the controller modes with each other, the better the match the higher the efficiency. A key feature in controlling a reduced order model of a high dimensional (or infinity-dimensional distributed parameter system) structural dynamic system must be to achieve high efficiency of the control system while satisfying the control objectives and/or constraints. Formally, this can be achieved by designing the control system and structural parameters simultaneously within an optimization framework. The subject of this paper is to present such a design procedure.
Optimal control of a low wing-loading STOL aircraft
NASA Technical Reports Server (NTRS)
Cunningham, T. B.
1976-01-01
Linear optimal quadratic control theory is applied to a low wing-loading STOL aircraft for ride quality and flight path following. Design criteria include minimum rms response to wind turbulence and desired transient response characteristics. Design techniques include proper choosing of design versus evaluation models, choosing appropriate performance index responses, and use of classical evaluation techniques. Results are obtained through a combination of frequency response shaping and gust observation. Effects of control rate and authority saturation are examined with a new rapid calculation of random input describing functions. Parameter sensitivity is also evaluated using a Liapunov type matrix equation.
Active control of combustion for optimal performance
Jackson, M.D.; Agrawal, A.K.
1999-07-01
Combustion-zone stoichiometry and fuel-air premixing were actively controlled to optimize the combustor performance over a range of operating conditions. The objective was to maximize the combustion temperature, while maintaining NO{sub x} within a specified limit. The combustion system consisted of a premixer located coaxially near the inlet of a water-cooled shroud. The equivalence ratio was controlled by a variable-speed suction fan located downstream. The split between the premixing air and diffusion air was governed by the distance between the premixer and shroud. The combustor performance was characterized by a cost function evaluated from time-averaged measurements of NO{sub x} and oxygen concentrations in products. The cost function was minimized by downhill simplex algorithm employing closed-loop feedback. Experiments were conducted at different fuel flow rates to demonstrate that the controller optimized the performance without prior knowledge of the combustor behavior.
Algorithms for optimizing CT fluence control
NASA Astrophysics Data System (ADS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-03-01
The ability to customize the incident x-ray fluence in CT via beam-shaping filters or mA modulation is known to improve image quality and/or reduce radiation dose. Previous work has shown that complete control of x-ray fluence (ray-by-ray fluence modulation) would further improve dose efficiency. While complete control of fluence is not currently possible, emerging concepts such as dynamic attenuators and inverse-geometry CT allow nearly complete control to be realized. Optimally using ray-by-ray fluence modulation requires solving a very high-dimensional optimization problem. Most optimization techniques fail or only provide approximate solutions. We present efficient algorithms for minimizing mean or peak variance given a fixed dose limit. The reductions in variance can easily be translated to reduction in dose, if the original variance met image quality requirements. For mean variance, a closed form solution is derived. The peak variance problem is recast as iterated, weighted mean variance minimization, and at each iteration it is possible to bound the distance to the optimal solution. We apply our algorithms in simulations of scans of the thorax and abdomen. Peak variance reductions of 45% and 65% are demonstrated in the abdomen and thorax, respectively, compared to a bowtie filter alone. Mean variance shows smaller gains (about 15%).
Simultaneous structure and control optimization of tensegrities
NASA Astrophysics Data System (ADS)
Masic, Milenko; Skelton, Robert E.
2005-05-01
This paper concerns optimization of prestress of a tensegrity structure to achieve the optimal mixed dynamic and control performance. A linearized dynamic model of the structure is derived. The force density variables that parameterize prestress of the structure appear linearly in the model. The feasible region of these parameters is defined in terms of the extreme directions of the prestress cone. Several properties of the problem are established inside the feasible region of the parameters. The problem is solved using a gradient method that provides a monotonic decrease of the objective function inside the feasible region. A numerical example of a cantilevered planar tensegrity beam is shown.
NASA Astrophysics Data System (ADS)
Shu, Chuan-Cun; Ho, Tak-San; Rabitz, Herschel
2016-05-01
We present a monotonic convergent quantum optimal control method that can be utilized to optimize the control field while exactly enforcing multiple equality constraints for steering quantum systems from an initial state towards desired quantum states. For illustration, special consideration is given to finding optimal control fields with (i) exact zero area and (ii) exact zero area along with constant pulse fluence. The method combined with these two types of constraints is successfully employed to maximize the state-to-state transition probability in a model vibrating diatomic molecule.
Perturbation analysis of optimal integral controls
NASA Technical Reports Server (NTRS)
Slater, G. L.
1984-01-01
The application of linear optimal control to the design of systems with integral control action on specified outputs is considered. Using integral terms in a quadratic performance index, an asymptotic analysis is used to determine the effect of variable quadratic weights on the eigenvalues and eigenvectors of the closed loop system. It is shown that for small integral terms the placement of integrator poles and gain calculation can be effectively decoupled from placement of the primary system eigenvalues. This technique is applied to the design of integral controls for a STOL aircraft outer loop guidance system.
Search complexity and resource scaling for the quantum optimal control of unitary transformations
Moore, Katharine W.; Riviello, Gregory; Rabitz, Herschel; Chakrabarti, Raj
2011-01-15
The optimal control of unitary transformations is a fundamental problem in quantum control theory and quantum information processing. The feasibility of performing such optimizations is determined by the computational and control resources required, particularly for systems with large Hilbert spaces. Prior work on unitary transformation control indicates that (i) for controllable systems, local extrema in the search landscape for optimal control of quantum gates have null measure, facilitating the convergence of local search algorithms, but (ii) the required time for convergence to optimal controls can scale exponentially with the Hilbert space dimension. Depending on the control-system Hamiltonian, the landscape structure and scaling may vary. This work introduces methods for quantifying Hamiltonian-dependent and kinematic effects on control optimization dynamics in order to classify quantum systems according to the search effort and control resources required to implement arbitrary unitary transformations.
PDEMOD: Software for control/structures optimization
NASA Technical Reports Server (NTRS)
Taylor, Lawrence W., Jr.; Zimmerman, David
1991-01-01
Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.
Modal methods in optimal control synthesis
NASA Technical Reports Server (NTRS)
Bryson, A. E., Jr.; Hall, W. E., Jr.
1980-01-01
Efficient algorithms for solving linear smoother-follower problems with quadratic criteria are presented. For time-invariant systems, the algorithm consists of one backward integration of a linear vector equation and one forward integration of another linear vector equation. Furthermore, the backward and forward Riccati matrices can be expressed in terms of the eigenvalues and eigenvectors of the Euler-Lagrange equations. Hence, the gains of the forward and backward Kalman-Bucy filters and of the optimal state-feedback regulator can be determined without integration of matrix Riccati equations. A computer program has been developed, based on this method of determining the gains, to synthesize the optimal time-invariant compensator in the presence of random disturbance inputs and random measurement errors. The program also computes the rms state and control variables of the optimal closed-loop system.
Optimal control of multiplicative control systems arising from cancer therapy
NASA Technical Reports Server (NTRS)
Bahrami, K.; Kim, M.
1975-01-01
This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.
Discrete-time neural inverse optimal control for nonlinear systems via passivation.
Ornelas-Tellez, Fernando; Sanchez, Edgar N; Loukianov, Alexander G
2012-08-01
This paper presents a discrete-time inverse optimal neural controller, which is constituted by combination of two techniques: 1) inverse optimal control to avoid solving the Hamilton-Jacobi-Bellman equation associated with nonlinear system optimal control and 2) on-line neural identification, using a recurrent neural network trained with an extended Kalman filter, in order to build a model of the assumed unknown nonlinear system. The inverse optimal controller is based on passivity theory. The applicability of the proposed approach is illustrated via simulations for an unstable nonlinear system and a planar robot. PMID:24807528
Optimal Control via Self-Generated Stochasticity
NASA Technical Reports Server (NTRS)
Zak, Michail
2011-01-01
The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.
Optimization approaches to nonlinear model predictive control
Biegler, L.T. . Dept. of Chemical Engineering); Rawlings, J.B. . Dept. of Chemical Engineering)
1991-01-01
With the development of sophisticated methods for nonlinear programming and powerful computer hardware, it now becomes useful and efficient to formulate and solve nonlinear process control problems through on-line optimization methods. This paper explores and reviews control techniques based on repeated solution of nonlinear programming (NLP) problems. Here several advantages present themselves. These include minimization of readily quantifiable objectives, coordinated and accurate handling of process nonlinearities and interactions, and systematic ways of dealing with process constraints. We motivate this NLP-based approach with small nonlinear examples and present a basic algorithm for optimization-based process control. As can be seen this approach is a straightforward extension of popular model-predictive controllers (MPCs) that are used for linear systems. The statement of the basic algorithm raises a number of questions regarding stability and robustness of the method, efficiency of the control calculations, incorporation of feedback into the controller and reliable ways of handling process constraints. Each of these will be treated through analysis and/or modification of the basic algorithm. To highlight and support this discussion, several examples are presented and key results are examined and further developed. 74 refs., 11 figs.
NASA Astrophysics Data System (ADS)
Bulgakov, V. K.; Strigunov, V. V.
2009-05-01
The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.
A model for HIV/AIDS pandemic with optimal control
NASA Astrophysics Data System (ADS)
Sule, Amiru; Abdullah, Farah Aini
2015-05-01
Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is pandemic. It has affected nearly 60 million people since the detection of the disease in 1981 to date. In this paper basic deterministic HIV/AIDS model with mass action incidence function are developed. Stability analysis is carried out. And the disease free equilibrium of the basic model was found to be locally asymptotically stable whenever the threshold parameter (RO) value is less than one, and unstable otherwise. The model is extended by introducing two optimal control strategies namely, CD4 counts and treatment for the infective using optimal control theory. Numerical simulation was carried out in order to illustrate the analytic results.
Theory of optical spin control in quantum dot microcavities
NASA Astrophysics Data System (ADS)
Smirnov, D. S.; Glazov, M. M.; Ivchenko, E. L.; Lanco, L.
2015-09-01
We present a microscopic theory of optical initialization, control, and detection for a single electron spin in a quantum dot embedded into a zero-dimensional microcavity. The strong coupling regime of the trion and the cavity mode is addressed. We demonstrate that efficient spin orientation by a single circularly polarized pulse is possible in relatively weak transverse magnetic fields. The possibilities for spin control by additional circularly polarized pulse are analyzed. Under optimal conditions the Kerr and Faraday rotation angles induced by the spin polarized electron may reach tens of degrees.
Intermittent locomotion as an optimal control strategy
Paoletti, P.; Mahadevan, L.
2014-01-01
Birds, fish and other animals routinely use unsteady effects to save energy by alternating between phases of active propulsion and passive coasting. Here, we construct a minimal model for such behaviour that can be couched as an optimal control problem via an analogy to travelling with a rechargeable battery. An analytical solution of the optimal control problem proves that intermittent locomotion has lower energy requirements relative to steady-state strategies. Additional realistic hypotheses, such as the assumption that metabolic cost at a given power should be minimal (the fixed gear hypothesis), a nonlinear dependence of the energy storage rate on propulsion and/or a preferred average speed, allow us to generalize the model and demonstrate the flexibility of intermittent locomotion with implications for biological and artificial systems. PMID:24711718
Optimal strategy for controlling the spread of Plasmodium Knowlesi malaria: Treatment and culling
NASA Astrophysics Data System (ADS)
Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini
2015-05-01
Plasmodium Knowlesi malaria is a parasitic mosquito-borne disease caused by a eukaryotic protist of genus Plasmodium Knowlesi transmitted by mosquito, Anopheles leucosphyrus to human and macaques. We developed and analyzed a deterministic Mathematical model for the transmission of Plasmodium Knowlesi malaria in human and macaques. The optimal control theory is applied to investigate optimal strategies for controlling the spread of Plasmodium Knowlesi malaria using treatment and culling as control strategies. The conditions for optimal control of the Plasmodium Knowlesi malaria are derived using Pontryagin's Maximum Principle. Finally, numerical simulations suggested that the combination of the control strategies is the best way to control the disease in any community.
Optimal shape control of a beam using piezoelectric actuators with low control voltage
NASA Astrophysics Data System (ADS)
Yu, Y.; Zhang, X. N.; Xie, S. L.
2009-09-01
This paper deals with the shape control of a cantilever beam structure by using laminated piezoelectric actuators (LPAs) with a low control voltage. The shape control equation of the cantilever beam partially covered with LPAs is derived based on the constitutive relations of the elastic material and piezoelectric material and shear deformation beam theory (Timoshenko theory). The actuating forces produced by the LPAs are formulated as well. It reveals how the actuating forces depend on the number of piezoelectric layers, the thickness of piezoelectric layers and the position of the actuators. The driving voltages of the LPAs are then determined by a genetic optimization algorithm. The shape control of the cantilever beam from applying the optimal voltage to the LPAs is simulated. The simulation results show that an LPA of large layer number is able to diminish effectively the pre-deflection of the beam under a low control voltage. The voltage applied to the LPA of five layers was almost five times smaller than that of one layer. In addition, increasing the number of LPA layers can significantly improve the control performance as the acting forces of the LPA are a quadratic function of the LPA layer number. The L2 norm of the displacement array of all nodes is diminished about 30% after optimization. Also with the same low control voltage, the LPA can obtain a better control performance than the conventional single layer piezoelectric actuator.
Optimal control of plates using incompatible strains
NASA Astrophysics Data System (ADS)
Jones, G. W.; Mahadevan, L.
2015-09-01
A flat plate will bend into a curved shell if it experiences an inhomogeneous growth field or if constrained appropriately at a boundary. While the forward problem associated with this process is well studied, the inverse problem of designing the boundary conditions or growth fields to achieve a particular shape is much less understood. We use ideas from variational optimization theory to formulate a well posed version of this inverse problem to determine the optimal growth field or boundary condition that will give rise to an arbitrary target shape, optimizing for both closeness to the target shape and for smoothness of the growth field. We solve the resulting system of PDE numerically using finite element methods with examples for both the fully non-symmetric case as well as for simplified one-dimensional and axisymmetric geometries. We also show that the system can also be solved semi-analytically by positing an ansatz for the deformation and growth fields in a circular disk with given thickness profile, leading to paraboloidal, cylindrical and saddle-shaped target shapes, and show how a soft mode can arise from a non-axisymmetric deformation of a structure with axisymmetric material properties.
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
Adaptive dynamic programming as a theory of sensorimotor control.
Jiang, Yu; Jiang, Zhong-Ping
2014-08-01
Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment. PMID:24962078
Control theory for scanning probe microscopy revisited.
Stirling, Julian
2014-01-01
We derive a theoretical model for studying SPM feedback in the context of control theory. Previous models presented in the literature that apply standard models for proportional-integral-derivative controllers predict a highly unstable feedback environment. This model uses features specific to the SPM implementation of the proportional-integral controller to give realistic feedback behaviour. As such the stability of SPM feedback for a wide range of feedback gains can be understood. Further consideration of mechanical responses of the SPM system gives insight into the causes of exciting mechanical resonances of the scanner during feedback operation. PMID:24778957
Control theory for scanning probe microscopy revisited
2014-01-01
Summary We derive a theoretical model for studying SPM feedback in the context of control theory. Previous models presented in the literature that apply standard models for proportional-integral-derivative controllers predict a highly unstable feedback environment. This model uses features specific to the SPM implementation of the proportional-integral controller to give realistic feedback behaviour. As such the stability of SPM feedback for a wide range of feedback gains can be understood. Further consideration of mechanical responses of the SPM system gives insight into the causes of exciting mechanical resonances of the scanner during feedback operation. PMID:24778957
Optimal Control of Quantum Measurement for Superconducting Phase Qubits
NASA Astrophysics Data System (ADS)
Wilhelm, Frank; Egger, Daniel
2015-03-01
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution towards a target unitary process, sometimes also in the presence of non-controllable incoherent processes. Here we show how to extend the GRAPE algorithm in the case where the incoherent processes are controllable and the target time evolution is a non-unitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a phase qubit measurement pulse. We show how this technique can lead to large measurement contrast close to 99%. We also show, within the validity of our model, that this algorithm can produce short 1.4 ns pulses with 98.2% contrast. Work posted at arXiv:1408.6086, in press at Physical Review A Supported by the EU through SCALEQIT.
Primer Vector Optimization: Survey of Theory, new Analysis and Applications
NASA Astrophysics Data System (ADS)
Guzman
This paper presents a preliminary study in developing a set of optimization tools for orbit rendezvous, transfer and station keeping. This work is part of a large scale effort undergoing at NASA Goddard Space Flight Center and a.i. solutions, Inc. to build generic methods, which will enable missions with tight fuel budgets. Since no single optimization technique can solve efficiently all existing problems, a library of tools where the user could pick the method most suited for the particular mission is envisioned. The first trajectory optimization technique explored is Lawden's primer vector theory [Ref. 1]. Primer vector theory can be considered as a byproduct of applying Calculus of Variations (COV) techniques to the problem of minimizing the fuel usage of impulsive trajectories. For an n-impulse trajectory, it involves the solution of n-1 two-point boundary value problems. In this paper, we look at some of the different formulations of the primer vector (dependent on the frame employed and on the force model). Also, the applicability of primer vector theory is examined in effort to understand when and why the theory can fail. Specifically, since COV is based on "small variations", singularities in the linearized (variational) equations of motion along the arcs must be taken into account. These singularities are a recurring problem in analyzes that employ "small variations" [Refs. 2, 3]. For example, singularities in the (2-body problem) variational equations along elliptic arcs occur when [Ref. 4], 1) the difference between the initial and final times is a multiple of the reference orbit period, 2) the difference between the initial and final true anomalies are given by k, for k= 0, 1, 2, 3,..., note that this cover the 3) the time of flight is a minimum for the given difference in true anomaly. For the N-body problem, the situation is more complex and is still under investigation. Several examples, such as the initialization of an orbit (ascent trajectory) and
Design, optimization, and control of tensegrity structures
NASA Astrophysics Data System (ADS)
Masic, Milenko
The contributions of this dissertation may be divided into four categories. The first category involves developing a systematic form-finding method for general and symmetric tensegrity structures. As an extension of the available results, different shape constraints are incorporated in the problem. Methods for treatment of these constraints are considered and proposed. A systematic formulation of the form-finding problem for symmetric tensegrity structures is introduced, and it uses the symmetry to reduce both the number of equations and the number of variables in the problem. The equilibrium analysis of modular tensegrities exploits their peculiar symmetry. The tensegrity similarity transformation completes the contributions in the area of enabling tools for tensegrity form-finding. The second group of contributions develops the methods for optimal mass-to-stiffness-ratio design of tensegrity structures. This technique represents the state-of-the-art for the static design of tensegrity structures. It is an extension of the results available for the topology optimization of truss structures. Besides guaranteeing that the final design satisfies the tensegrity paradigm, the problem constrains the structure from different modes of failure, which makes it very general. The open-loop control of the shape of modular tensegrities is the third contribution of the dissertation. This analytical result offers a closed form solution for the control of the reconfiguration of modular structures. Applications range from the deployment and stowing of large-scale space structures to the locomotion-inducing control for biologically inspired structures. The control algorithm is applicable regardless of the size of the structures, and it represents a very general result for a large class of tensegrities. Controlled deployments of large-scale tensegrity plates and tensegrity towers are shown as examples that demonstrate the full potential of this reconfiguration strategy. The last
Passive Motion Paradigm: An Alternative to Optimal Control
Mohan, Vishwanathan; Morasso, Pietro
2011-01-01
In the last years, optimal control theory (OCT) has emerged as the leading approach for investigating neural control of movement and motor cognition for two complementary research lines: behavioral neuroscience and humanoid robotics. In both cases, there are general problems that need to be addressed, such as the “degrees of freedom (DoFs) problem,” the common core of production, observation, reasoning, and learning of “actions.” OCT, directly derived from engineering design techniques of control systems quantifies task goals as “cost functions” and uses the sophisticated formal tools of optimal control to obtain desired behavior (and predictions). We propose an alternative “softer” approach passive motion paradigm (PMP) that we believe is closer to the biomechanics and cybernetics of action. The basic idea is that actions (overt as well as covert) are the consequences of an internal simulation process that “animates” the body schema with the attractor dynamics of force fields induced by the goal and task-specific constraints. This internal simulation offers the brain a way to dynamically link motor redundancy with task-oriented constraints “at runtime,” hence solving the “DoFs problem” without explicit kinematic inversion and cost function computation. We argue that the function of such computational machinery is not only restricted to shaping motor output during action execution but also to provide the self with information on the feasibility, consequence, understanding and meaning of “potential actions.” In this sense, taking into account recent developments in neuroscience (motor imagery, simulation theory of covert actions, mirror neuron system) and in embodied robotics, PMP offers a novel framework for understanding motor cognition that goes beyond the engineering control paradigm provided by OCT. Therefore, the paper is at the same time a review of the PMP rationale, as a computational theory, and a perspective presentation of
Use of modern control theory in military command and control
NASA Astrophysics Data System (ADS)
Busch, Timothy E.
2001-09-01
This paper discusses the use of modern control theoretic approaches in military command and control. The military enterprise is a highly dynamic and nonlinear environment. The desire on the part of military commanders to operate at faster operational tempos while still maintaining a stable and robust system, naturally leads to the consideration of a control theoretic approach to providing decision aids. I will present a brief history of the science of command and control of military forces and discuss how modern control theory might be applied to air operations.
Iterative diagonalization for orbital optimization in natural orbital functional theory.
Piris, M; Ugalde, J M
2009-10-01
A challenging task in natural orbital functional theory is to find an efficient procedure for doing orbital optimization. Procedures based on diagonalization techniques have confirmed its practical value since the resulting orbitals are automatically orthogonal. In this work, a new procedure is introduced, which yields the natural orbitals by iterative diagonalization of a Hermitian matrix F. The off-diagonal elements of the latter are determined explicitly from the hermiticity of the matrix of the Lagrange multipliers. An expression for diagonal elements is absent so a generalized Fockian is undefined in the conventional sense, nevertheless, they may be determined from an aufbau principle. Thus, the diagonal elements are obtained iteratively considering as starting values those coming from a single diagonalization of the matrix of the Lagrange multipliers calculated with the Hartree-Fock orbitals after the occupation numbers have been optimized. The method has been tested on the G2/97 set of molecules for the Piris natural orbital functional. To help the convergence, we have implemented a variable scaling factor which avoids large values of the off-diagonal elements of F. The elapsed times of the computations required by the proposed procedure are compared with a full sequential quadratic programming optimization, so that the efficiency of the method presented here is demonstrated. PMID:19219918
Optimal Control of Flows in Moving Domains
NASA Astrophysics Data System (ADS)
Protas, Bartosz; Liao, Wenyuan; Glander, Donn
2006-11-01
This investigation concerns adjoint--based optimization of viscous incompressible flows (the Navier-Stokes problem) coupled with heat conduction involving change of phase (the Stefan problem) and occurring in domains with moving boundaries such as the free and solidification surfaces. This problem is motivated by optimization of advanced welding techniques used in automotive manufacturing. We characterize the sensitivity of a suitable cost functional defined for the system with respect to control (the heat input) using adjoint equations. Given that the shape of the domain is also a dependent variable, characterizing sensitivities necessitates the introduction of ``non-cylindrical'' calculus required to differentiate a cost functional defined on a variable domain. As a result, unlike the forward problem, the adjoint system is defined on a domain with a predetermined evolution in time and also involves ordinary differential equations defined on the domain boundary (``the adjoint transverse system''). We will discuss certain computational issues related to numerical solution of such adjoint problems.
Coherent optimal control of photosynthetic molecules
NASA Astrophysics Data System (ADS)
Caruso, F.; Montangero, S.; Calarco, T.; Huelga, S. F.; Plenio, M. B.
2012-04-01
We demonstrate theoretically that open-loop quantum optimal control techniques can provide efficient tools for the verification of various quantum coherent transport mechanisms in natural and artificial light-harvesting complexes under realistic experimental conditions. To assess the feasibility of possible biocontrol experiments, we introduce the main settings and derive optimally shaped and robust laser pulses that allow for the faithful preparation of specified initial states (such as localized excitation or coherent superposition, i.e., propagating and nonpropagating states) of the photosystem and probe efficiently the subsequent dynamics. With these tools, different transport pathways can be discriminated, which should facilitate the elucidation of genuine quantum dynamical features of photosystems and therefore enhance our understanding of the role that coherent processes may play in actual biological complexes.
Analytical and experimental performance of optimal controller designs for a supersonic inlet
NASA Technical Reports Server (NTRS)
Zeller, J. R.; Lehtinen, B.; Geyser, L. C.; Batterton, P. G.
1973-01-01
The techniques of modern optimal control theory were applied to the design of a control system for a supersonic inlet. The inlet control problem was approached as a linear stochastic optimal control problem using as the performance index the expected frequency of unstarts. The details of the formulation of the stochastic inlet control problem are presented. The computational procedures required to obtain optimal controller designs are discussed, and the analytically predicted performance of controllers designed for several different inlet conditions is tabulated. The experimental implementation of the optimal control laws is described, and the experimental results obtained in a supersonic wind tunnel are presented. The control laws were implemented with analog and digital computers. Comparisons are made between the experimental and analytically predicted performance results. Comparisons are also made between the results obtained with continuous analog computer controllers and discrete digital computer versions.
Optimization and Control of Plasma Doping Processes
Raj, Deven M.; Godet, Ludovic; Chamberlain, Nicholas; Hadidi, Kamal; Singh, Vikram; Papasouliotis, George D.
2011-01-07
Plasma doping (PLAD) is a well characterized alternative to beam-line technology, which has already been adopted in high volume manufacturing in the ultra high dose, low energy regime for advanced DRAM technology nodes. As semiconductor technology evolves, the demand for ever lower energy, higher dose implants will continue to grow, and the requirements for process control will become increasingly stringent. During plasma immersion ion implantation, ionized species present in the plasma are extracted and implanted into the wafer, while other processes, such as deposition, etching and sputtering, are competing in parallel. The dopant profile into the substrate results from contributions of all these mechanisms. Using the hardware and plasma composition control features present in the PLAD system to balance the contributions of the above processes, the dopant profile can be modified and dopant retention can be optimized. In this paper, we detail the process control approach used to optimize process performance for low energy, high dose implants, and validate it with plasma and wafer state data.
Optimal digital control of multirate systems
NASA Technical Reports Server (NTRS)
Amit, N.; Powell, J. D.
1981-01-01
Many digitally controlled aerospace systems have widely separated time constants and thus can benefit from the use of two or more sample rates. In this paper, the analysis and synthesis of multirate systems is accomplished by creating an equivalent single rate system and applying existing techniques. The optimal steady state solution of the single rate system is obtained by eigenvector decomposition and then used to compute the periodic solution to the Riccati equation of the original multirate system. An example shows when multirate analysis is necessary and the penalty of various levels of approximations to the exact multirate solution.
Hybrid intelligent control concepts for optimal data fusion
NASA Astrophysics Data System (ADS)
Llinas, James
1994-02-01
In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.
Finite element solution of optimal control problems with inequality constraints
NASA Technical Reports Server (NTRS)
Bless, Robert R.; Hodges, Dewey H.
1990-01-01
A finite-element method based on a weak Hamiltonian form of the necessary conditions is summarized for optimal control problems. Very crude shape functions (so simple that element numerical quadrature is not necessary) can be used to develop an efficient procedure for obtaining candidate solutions (i.e., those which satisfy all the necessary conditions) even for highly nonlinear problems. An extension of the formulation allowing for discontinuities in the states and derivatives of the states is given. A theory that includes control inequality constraints is fully developed. An advanced launch vehicle (ALV) model is presented. The model involves staging and control constraints, thus demonstrating the full power of the weak formulation to date. Numerical results are presented along with total elapsed computer time required to obtain the results. The speed and accuracy in obtaining the results make this method a strong candidate for a real-time guidance algorithm.
Redmond, J.; Parker, G.
1993-07-01
This paper examines the role of the control objective and the control time in determining fuel-optimal actuator placement for structural vibration suppression. A general theory is developed that can be easily extended to include alternative performance metrics such as energy and time-optimal control. The performance metric defines a convex admissible control set which leads to a max-min optimization problem expressing optimal location as a function of initial conditions and control time. A solution procedure based on a nested Genetic Algorithm is presented and applied to an example problem. Results indicate that the optimal locations vary widely as a function of control time and initial conditions.
Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation
NASA Technical Reports Server (NTRS)
Clifton, C.; Homaifax, A.; Bikdash, M.
1997-01-01
This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.
Biomechanical modeling and optimal control of human posture.
Menegaldo, Luciano Luporini; Fleury, Agenor de Toledo; Weber, Hans Ingo
2003-11-01
The present work describes the biomechanical modeling of human postural mechanics in the saggital plane and the use of optimal control to generate open-loop raising-up movements from a squatting position. The biomechanical model comprises 10 equivalent musculotendon actuators, based on a 40 muscles model, and three links (shank, thigh and HAT-Head, Arms and Trunk). Optimal control solutions are achieved through algorithms based on the Consistent Approximations Theory (Schwartz and Polak, 1996), where the continuous non-linear dynamics is represented in a discrete space by means of a Runge-Kutta integration and the control signals in a spline-coefficient functional space. This leads to non-linear programming problems solved by a sequential quadratic programming (SQP) method. Due to the highly non-linear and unstable nature of the posture dynamics, numerical convergence is difficult, and specific strategies must be implemented in order to allow convergence. Results for control (muscular excitations) and angular trajectories are shown using two final simulation times, as well as specific control strategies are discussed. PMID:14522212
Hypersonic Vehicle Trajectory Optimization and Control
NASA Technical Reports Server (NTRS)
Balakrishnan, S. N.; Shen, J.; Grohs, J. R.
1997-01-01
Two classes of neural networks have been developed for the study of hypersonic vehicle trajectory optimization and control. The first one is called an 'adaptive critic'. The uniqueness and main features of this approach are that: (1) they need no external training; (2) they allow variability of initial conditions; and (3) they can serve as feedback control. This is used to solve a 'free final time' two-point boundary value problem that maximizes the mass at the rocket burn-out while satisfying the pre-specified burn-out conditions in velocity, flightpath angle, and altitude. The second neural network is a recurrent network. An interesting feature of this network formulation is that when its inputs are the coefficients of the dynamics and control matrices, the network outputs are the Kalman sequences (with a quadratic cost function); the same network is also used for identifying the coefficients of the dynamics and control matrices. Consequently, we can use it to control a system whose parameters are uncertain. Numerical results are presented which illustrate the potential of these methods.
An introduction to stochastic control theory, path integrals and reinforcement learning
NASA Astrophysics Data System (ADS)
Kappen, Hilbert J.
2007-02-01
Control theory is a mathematical description of how to act optimally to gain future rewards. In this paper I give an introduction to deterministic and stochastic control theory and I give an overview of the possible application of control theory to the modeling of animal behavior and learning. I discuss a class of non-linear stochastic control problems that can be efficiently solved using a path integral or by MC sampling. In this control formalism the central concept of cost-to-go becomes a free energy and methods and concepts from statistical physics can be readily applied.
Optimal haptic feedback control of artificial muscles
NASA Astrophysics Data System (ADS)
Chen, Daniel; Besier, Thor; Anderson, Iain; McKay, Thomas
2014-03-01
As our population ages, and trends in obesity continue to grow, joint degenerative diseases like osteoarthritis (OA) are becoming increasingly prevalent. With no cure currently in sight, the only effective treatments for OA are orthopaedic surgery and prolonged rehabilitation, neither of which is guaranteed to succeed. Gait retraining has tremendous potential to alter the contact forces in the joints due to walking, reducing the risk of one developing hip and knee OA. Dielectric Elastomer Actuators (DEAs) are being explored as a potential way of applying intuitive haptic feedback to alter a patient's walking gait. The main challenge with the use of DEAs in this application is producing large enough forces and strains to induce sensation when coupled to a patient's skin. A novel controller has been proposed to solve this issue. The controller uses simultaneous capacitive self-sensing and actuation which will optimally apply a haptic sensation to the patient's skin independent of variability in DEAs and patient geometries.
Xu, Hao; Jagannathan, Sarangapani
2015-03-01
The stochastic optimal control of nonlinear networked control systems (NNCSs) using neuro-dynamic programming (NDP) over a finite time horizon is a challenging problem due to terminal constraints, system uncertainties, and unknown network imperfections, such as network-induced delays and packet losses. Since the traditional iteration or time-based infinite horizon NDP schemes are unsuitable for NNCS with terminal constraints, a novel time-based NDP scheme is developed to solve finite horizon optimal control of NNCS by mitigating the above-mentioned challenges. First, an online neural network (NN) identifier is introduced to approximate the control coefficient matrix that is subsequently utilized in conjunction with the critic and actor NNs to determine a time-based stochastic optimal control input over finite horizon in a forward-in-time and online manner. Eventually, Lyapunov theory is used to show that all closed-loop signals and NN weights are uniformly ultimately bounded with ultimate bounds being a function of initial conditions and final time. Moreover, the approximated control input converges close to optimal value within finite time. The simulation results are included to show the effectiveness of the proposed scheme. PMID:25720004
Induction factor optimization through variable lift control
NASA Astrophysics Data System (ADS)
Cooney, John; Corke, Thomas; Nelson, Robert; Williams, Theodore
2011-11-01
Due to practical design limitations coupled with the detrimental effects posed by complex wind regimes, modern wind turbines struggle to maintain or even reach ideal operational states. With additional gains through traditional approaches becoming more difficult and costly, active lift control represents a more attractive option for future designs. Here, plasma actuators have been explored experimentally in trailing edge applications for use in attached flow regimes. This authority would be used to drive the axial induction factor toward the ideal given by the Betz limit through distributed lift control thereby enhancing energy capture. Predictions of power improvement achievable by this methodology are made with blade - element momentum theory but will eventually be demonstrated in the field at the Laboratory for Enhanced Wind Energy Design, currently under construction at the University of Notre Dame.
ERIC Educational Resources Information Center
Penningroth, Suzanna L.; Scott, Walter D.
2012-01-01
Two prominent theories of lifespan development, socioemotional selectivity theory and selection, optimization, and compensation theory, make similar predictions for differences in the goal representations of younger and older adults. Our purpose was to test whether the goals of younger and older adults differed in ways predicted by these two…
Hiraishi, Kunihiko
2014-01-01
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766
Optimal Feedback Controlled Assembly of Perfect Crystals.
Tang, Xun; Rupp, Bradley; Yang, Yuguang; Edwards, Tara D; Grover, Martha A; Bevan, Michael A
2016-07-26
Perfectly ordered states are targets in diverse molecular to microscale systems involving, for example, atomic clusters, protein folding, protein crystallization, nanoparticle superlattices, and colloidal crystals. However, there is no obvious approach to control the assembly of perfectly ordered global free energy minimum structures; near-equilibrium assembly is impractically slow, and faster out-of-equilibrium processes generally terminate in defective states. Here, we demonstrate the rapid and robust assembly of perfect crystals by navigating kinetic bottlenecks using closed-loop control of electric field mediated crystallization of colloidal particles. An optimal policy is computed with dynamic programming using a reaction coordinate based dynamic model. By tracking real-time stochastic particle configurations and adjusting applied fields via feedback, the evolution of unassembled particles is guided through polycrystalline states into single domain crystals. This approach to controlling the assembly of a target structure is based on general principles that make it applicable to a broad range of processes from nano- to microscales (where tuning a global thermodynamic variable yields temporal control over thermal sampling of different states via their relative free energies). PMID:27387146
Optimal Control of Distributed Energy Resources using Model Predictive Control
Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen
2012-07-22
In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.
A fuzzy-based optimal reactive power control
Abdul-Rahman, K.H.; Shahidehpour, S.M. . Dept. of Electrical and Computer Engineering)
1993-05-01
This paper presents a mathematical formulation for the optimal reactive power control problem using the fuzzy set theory. The objectives are to minimize real power losses and improve the voltage profile of a given system. Transmission loses are expressed in terms of voltage increments by relating the control variables, i.e., tap positions of transformers and reactive power injections of VAR sources, to the voltage increments in a modified Jacobian matrix. This specific formulation of the problem does not require the Jacobian matrix inversion, and hence it will save computation time and memory space. The objective function and the constraints are modeled by fuzzy sets. Linear membership functions of the fuzzy sets are defined and the fuzzy linear optimization problem is formulated. The solution space in this case is defined as the intersection of the fuzzy sets describing the constraints and the objective functions. Each solution is characterized by a parameter that determines the degree of satisfaction with the solution. The optimal solution is the one with the maximum value for the satisfaction parameter. Results for the application of this approach on test systems reveal its numerous advantages.
Optimal control and cold war dynamics between plant and herbivore.
Low, Candace; Ellner, Stephen P; Holden, Matthew H
2013-08-01
Herbivores eat the leaves that a plant needs for photosynthesis. However, the degree of antagonism between plant and herbivore may depend critically on the timing of their interactions and the intrinsic value of a leaf. We present a model that investigates whether and when the timing of plant defense and herbivore feeding activity can be optimized by evolution so that their interactions can move from antagonistic to neutral. We assume that temporal changes in environmental conditions will affect intrinsic leaf value, measured as potential carbon gain. Using optimal-control theory, we model herbivore evolution, first in response to fixed plant strategies and then under coevolutionary dynamics in which the plant also evolves in response to the herbivore. In the latter case, we solve for the evolutionarily stable strategies of plant defense induction and herbivore hatching rate under different ecological conditions. Our results suggest that the optimal strategies for both plant and herbivore are to avoid direct conflict. As long as the plant has the capability for moderately lethal defense, the herbivore will modify its hatching rate to avoid plant defenses, and the plant will never have to use them. Insights from this model offer a possible solution to the paradox of sublethal defenses and provide a mechanism for stable plant-herbivore interactions without the need for natural enemy control. PMID:23852361
Application of queuing theory in production-inventory optimization
NASA Astrophysics Data System (ADS)
Rashid, Reza; Hoseini, Seyed Farzad; Gholamian, M. R.; Feizabadi, Mohammad
2015-07-01
This paper presents a mathematical model for an inventory control system in which customers' demands and suppliers' service time are considered as stochastic parameters. The proposed problem is solved through queuing theory for a single item. In this case, transitional probabilities are calculated in steady state. Afterward, the model is extended to the case of multi-item inventory systems. Then, to deal with the complexity of this problem, a new heuristic algorithm is developed. Finally, the presented bi-level inventory-queuing model is implemented as a case study in Electroestil Company.
Optimal control of a delayed SLBS computer virus model
NASA Astrophysics Data System (ADS)
Chen, Lijuan; Hattaf, Khalid; Sun, Jitao
2015-06-01
In this paper, a delayed SLBS computer virus model is firstly proposed. To the best of our knowledge, this is the first time to discuss the optimal control of the SLBS model. By using the optimal control strategy, we present an optimal strategy to minimize the total number of the breakingout computers and the cost associated with toxication or detoxication. We show that an optimal control solution exists for the control problem. Some examples are presented to show the efficiency of this optimal control.
Computational methods to obtain time optimal jet engine control
NASA Technical Reports Server (NTRS)
Basso, R. J.; Leake, R. J.
1976-01-01
Dynamic Programming and the Fletcher-Reeves Conjugate Gradient Method are two existing methods which can be applied to solve a general class of unconstrained fixed time, free right end optimal control problems. New techniques are developed to adapt these methods to solve a time optimal control problem with state variable and control constraints. Specifically, they are applied to compute a time optimal control for a jet engine control problem.
Optimal control of thermally coupled Navier Stokes equations
NASA Technical Reports Server (NTRS)
Ito, Kazufumi; Scroggs, Jeffrey S.; Tran, Hien T.
1994-01-01
The optimal boundary temperature control of the stationary thermally coupled incompressible Navier-Stokes equation is considered. Well-posedness and existence of the optimal control and a necessary optimality condition are obtained. Optimization algorithms based on the augmented Lagrangian method with second order update are discussed. A test example motivated by control of transport process in the high pressure vapor transport (HVPT) reactor is presented to demonstrate the applicability of our theoretical results and proposed algorithm.
Optimal control of Bose-Einstein condensates in three dimensions
NASA Astrophysics Data System (ADS)
Mennemann, J.-F.; Matthes, D.; Weishäupl, R.-M.; Langen, T.
2015-11-01
Ultracold gases promise many applications in quantum metrology, simulation and computation. In this context, optimal control theory (OCT) provides a versatile framework for the efficient preparation of complex quantum states. However, due to the high computational cost, OCT of ultracold gases has so far mostly been applied to one-dimensional (1D) problems. Here, we realize computationally efficient OCT of the Gross-Pitaevskii equation to manipulate Bose-Einstein condensates in all three spatial dimensions. We study various realistic experimental applications where 1D simulations can only be applied approximately or not at all. Moreover, we provide a stringent mathematical footing for our scheme and carefully study the creation of elementary excitations and their minimization using multiple control parameters. The results are directly applicable to recent experiments and might thus be of immediate use in the ongoing effort to employ the properties of the quantum world for technological applications.
Optimized exposure control in digital mammography
NASA Astrophysics Data System (ADS)
Shramchenko, Nataliya; Blin, Philippe; Mathey, Claude; Klausz, Remy
2004-05-01
A method for the determination of optimal operating points of digital mammography systems is described. The digital mammography equipment uses a flat panel detector and a bi-metal molybdenum/rhodium x-ray tube. An operating point is defined by the selection of the x-ray tube target material, x-ray filtration, kVp and detector entrance dose. Breast thickness and composition are estimated from a low dose pre-exposure, then used to index tables containing sets of operating points. The operating points are determined using a model of the image chain, which computes contrast to noise ratio (CNR) and average glandular dose (AGD) for all possible exposure conditions and breast thickness and composition combinations. The selected operating points are those which provide the required CNR for the lowest AGD. An AGD reduction of 30% to 50% can be achieved for comparable Image Quality, relative to current operating points. Resulting from the optimization process, the rhodium target is used in more than 75% of cases. Measurements of CNR and AGD have been performed on various tissue equivalent materials with good agreement between calculated and measured values. The proposed method provides full Image Quality benefit of digital mammography while minimizing dose to patients in a controlled and predictive way.
Towards Quantum Cybernetics:. Optimal Feedback Control in Quantum Bio Informatics
NASA Astrophysics Data System (ADS)
Belavkin, V. P.
2009-02-01
A brief account of the quantum information dynamics and dynamical programming methods for the purpose of optimal control in quantum cybernetics with convex constraints and cońcave cost and bequest functions of the quantum state is given. Consideration is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme with continuous observations we exploit the separation theorem of filtering and control aspects for quantum stochastic micro-dynamics of the total system. This allows to start with the Belavkin quantum filtering equation and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to only Hamiltonian terms in the filtering equation. A controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.
Quantum demolition filtering and optimal control of unstable systems.
Belavkin, V P
2012-11-28
A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one. PMID:23091216
Modelling Optimal Control of Cholera in Communities Linked by Migration.
Njagarah, J B H; Nyabadza, F
2015-01-01
A mathematical model for the dynamics of cholera transmission with permissible controls between two connected communities is developed and analysed. The dynamics of the disease in the adjacent communities are assumed to be similar, with the main differences only reflected in the transmission and disease related parameters. This assumption is based on the fact that adjacent communities often have different living conditions and movement is inclined toward the community with better living conditions. Community specific reproduction numbers are given assuming movement of those susceptible, infected, and recovered, between communities. We carry out sensitivity analysis of the model parameters using the Latin Hypercube Sampling scheme to ascertain the degree of effect the parameters and controls have on progression of the infection. Using principles from optimal control theory, a temporal relationship between the distribution of controls and severity of the infection is ascertained. Our results indicate that implementation of controls such as proper hygiene, sanitation, and vaccination across both affected communities is likely to annihilate the infection within half the time it would take through self-limitation. In addition, although an infection may still break out in the presence of controls, it may be up to 8 times less devastating when compared with the case when no controls are in place. PMID:26246850
Modelling Optimal Control of Cholera in Communities Linked by Migration
Njagarah, J. B. H.; Nyabadza, F.
2015-01-01
A mathematical model for the dynamics of cholera transmission with permissible controls between two connected communities is developed and analysed. The dynamics of the disease in the adjacent communities are assumed to be similar, with the main differences only reflected in the transmission and disease related parameters. This assumption is based on the fact that adjacent communities often have different living conditions and movement is inclined toward the community with better living conditions. Community specific reproduction numbers are given assuming movement of those susceptible, infected, and recovered, between communities. We carry out sensitivity analysis of the model parameters using the Latin Hypercube Sampling scheme to ascertain the degree of effect the parameters and controls have on progression of the infection. Using principles from optimal control theory, a temporal relationship between the distribution of controls and severity of the infection is ascertained. Our results indicate that implementation of controls such as proper hygiene, sanitation, and vaccination across both affected communities is likely to annihilate the infection within half the time it would take through self-limitation. In addition, although an infection may still break out in the presence of controls, it may be up to 8 times less devastating when compared with the case when no controls are in place. PMID:26246850
Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints
Kmet', Tibor; Kmet'ova, Maria
2009-09-09
A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.
A new linear quadratic optimal controller for the 34-meter high efficiency antenna position loop
NASA Technical Reports Server (NTRS)
Nickerson, J. A.
1987-01-01
The design of a new position loop controller for the 34-meter High Efficiency Deep Space antennas using linear quadratic (LQ) optimal control techniques is discussed. The LQ optimal control theory is reviewed, and model development and verification are discussed. Families of optimal gain vectors are generated by varying weight parameters. Performance specifications were used to select a final gain vector. Estimator dynamics were selected and the corresponding gain vectors were computed. Final estimator selection was based on position, commanded rate, and estimator error responses.
On a Highly Nonlinear Self-Obstacle Optimal Control Problem
Di Donato, Daniela; Mugnai, Dimitri
2015-10-15
We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.
Skinner Rusk unified formalism for optimal control systems and applications
NASA Astrophysics Data System (ADS)
Barbero-Liñán, María; Echeverría-Enríquez, Arturo; Martín de Diego, David; Muñoz-Lecanda, Miguel C.; Román-Roy, Narciso
2007-10-01
A geometric approach to time-dependent optimal control problems is proposed. This formulation is based on the Skinner and Rusk formalism for Lagrangian and Hamiltonian systems. The corresponding unified formalism developed for optimal control systems allows us to formulate geometrically the necessary conditions given by a weak form of Pontryagin's maximum principle, provided that the differentiability with respect to controls is assumed and the space of controls is open. Furthermore, our method is also valid for implicit optimal control systems and, in particular, for the so-called descriptor systems (optimal control problems including both differential and algebraic equations).
Rear-heavy car control by adaptive linear optimal preview
NASA Astrophysics Data System (ADS)
Thommyppillai, M.; Evangelou, S.; Sharp, R. S.
2010-05-01
Adaptive linear optimal preview control theory is applied to a simple but non-linear car model, with parameters chosen to make the rear axle saturate first in any quasi-steady manoeuvre. The tendency of such a car to spin above a critical speed, which is a function of its running state, causes control to be especially difficult when operating near to the limit of the rear-axle force system. As in previous work, trim states and optimal gains are computed off-line for a given speed and a full range of lateral accelerations. Gain-scheduling with interpolation over trims and gain sets is used to keep the control appropriate to the running conditions, as they change. Simulations of manoeuvres are used to test and demonstrate the system capability. It is shown that utilising the rear-axle lateral-slip ratio as the scheduling variable, in the case of this rear-heavy car, gives excellent tracking, even when the tyres are run close to full saturation. It is implied by this and previous work that the general case can be treated effectively by monitoring both front- and rear-axle slips and scheduling on a worst-case basis.
Optimization and quality control of computed radiography
NASA Astrophysics Data System (ADS)
Willis, Charles E.; Weiser, John C.; Leckie, Robert G.; Romlein, John R.; Norton, Gary S.
1994-05-01
Computed radiography (CR) is a relatively new technique for projection radiography. Few hospitals have CR devices in routine service and only a handful have more than one CR unit. As such, the clinical knowledge base does not yet exist to establish quality control (QC) procedures for CR devices. Without assurance that CR systems are operating within nominal limits, efforts to optimize CR performance are limited in value. A complete CR system includes detector plates that vary in response, cassettes, an electro-optical system for developing the image, computer algorithms for processing the raw image, and a hard copy output device. All of these subsystems are subject to variations in performance that can degrade image quality. Using CR manufacturer documentation, we have defined acceptance protocols for two different Fuji CR devices, the FCR 7000 and the AC1+, and have applied these tests to ten individual machines. We have begun to establish baseline performance measures and to determine measurement frequencies. CR QC is only one component of the overall quality control for totally digital radiology departments.
Optimal and suboptimal control technique for aircraft spin recovery
NASA Technical Reports Server (NTRS)
Young, J. W.
1974-01-01
An analytic investigation has been made of procedures for effecting recovery from equilibrium spin conditions for three assumed aircraft configurations. Three approaches which utilize conventional aerodynamic controls are investigated. Included are a constant control recovery mode, optimal recoveries, and a suboptimal control logic patterned after optimal recovery results. The optimal and suboptimal techniques are shown to yield a significant improvement in recovery performance over that attained by using a constant control recovery procedure.
Optimal control of a supersonic inlet to minimize frequency of inlet unstart
NASA Technical Reports Server (NTRS)
Lehtinen, B.; Zeller, J. R.; Geyser, L. C.
1978-01-01
A preliminary investigation into the use of modern control theory for the design of controls for a supersonic inlet is described. In particular, the task of controlling a mixed-compression supersonic inlet is formulated as a linear optimal stochastic control and estimation problem. An inlet can exhibit an undesirable instability due to excessive inlet normal shock motion. For the optimal control formulation of the inlet problem, a non quadratic performance index, which is equal to the expected frequency of inlet unstarts, is used. This physically meaningful performance index is minimized for a range of inlet disturbance and measurement noise covariances.
The role of modern control theory in the design of controls for aircraft turbine engines
NASA Technical Reports Server (NTRS)
Zeller, J.; Lehtinen, B.; Merrill, W.
1982-01-01
The development, applications, and current research in modern control theory (MCT) are reviewed, noting the importance for fuel-efficient operation of turbines with variable inlet guide vanes, compressor stators, and exhaust nozzle area. The evolution of multivariable propulsion control design is examined, noting a basis in a matrix formulation of the differential equations defining the process, leading to state space formulations. Reports and papers which appeared from 1970-1982 which dealt with problems in MCT applications to turbine engine control design are outlined, including works on linear quadratic regulator methods, frequency domain methods, identification, estimation, and model reduction, detection, isolation, and accommodation, and state space control, adaptive control, and optimization approaches. Finally, NASA programs in frequency domain design, sensor failure detection, computer-aided control design, and plant modeling are explored
Optimally controlling the human connectome: the role of network topology
Betzel, Richard F.; Gu, Shi; Medaglia, John D.; Pasqualetti, Fabio; Bassett, Danielle S.
2016-01-01
To meet ongoing cognitive demands, the human brain must seamlessly transition from one brain state to another, in the process drawing on different cognitive systems. How does the brain’s network of anatomical connections help facilitate such transitions? Which features of this network contribute to making one transition easy and another transition difficult? Here, we address these questions using network control theory. We calculate the optimal input signals to drive the brain to and from states dominated by different cognitive systems. The input signals allow us to assess the contributions made by different brain regions. We show that such contributions, which we measure as energy, are correlated with regions’ weighted degrees. We also show that the network communicability, a measure of direct and indirect connectedness between brain regions, predicts the extent to which brain regions compensate when input to another region is suppressed. Finally, we identify optimal states in which the brain should start (and finish) in order to minimize transition energy. We show that the optimal target states display high activity in hub regions, implicating the brain’s rich club. Furthermore, when rich club organization is destroyed, the energy cost associated with state transitions increases significantly, demonstrating that it is the richness of brain regions that makes them ideal targets. PMID:27468904
Optimally controlling the human connectome: the role of network topology.
Betzel, Richard F; Gu, Shi; Medaglia, John D; Pasqualetti, Fabio; Bassett, Danielle S
2016-01-01
To meet ongoing cognitive demands, the human brain must seamlessly transition from one brain state to another, in the process drawing on different cognitive systems. How does the brain's network of anatomical connections help facilitate such transitions? Which features of this network contribute to making one transition easy and another transition difficult? Here, we address these questions using network control theory. We calculate the optimal input signals to drive the brain to and from states dominated by different cognitive systems. The input signals allow us to assess the contributions made by different brain regions. We show that such contributions, which we measure as energy, are correlated with regions' weighted degrees. We also show that the network communicability, a measure of direct and indirect connectedness between brain regions, predicts the extent to which brain regions compensate when input to another region is suppressed. Finally, we identify optimal states in which the brain should start (and finish) in order to minimize transition energy. We show that the optimal target states display high activity in hub regions, implicating the brain's rich club. Furthermore, when rich club organization is destroyed, the energy cost associated with state transitions increases significantly, demonstrating that it is the richness of brain regions that makes them ideal targets. PMID:27468904
Gradient Optimization for Analytic conTrols - GOAT
NASA Astrophysics Data System (ADS)
Assémat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank
Quantum optimal control becomes a necessary step in a number of studies in the quantum realm. Recent experimental advances showed that superconducting qubits can be controlled with an impressive accuracy. However, most of the standard optimal control algorithms are not designed to manage such high accuracy. To tackle this issue, a novel quantum optimal control algorithm have been introduced: the Gradient Optimization for Analytic conTrols (GOAT). It avoids the piecewise constant approximation of the control pulse used by standard algorithms. This allows an efficient implementation of very high accuracy optimization. It also includes a novel method to compute the gradient that provides many advantages, e.g. the absence of backpropagation or the natural route to optimize the robustness of the control pulses. This talk will present the GOAT algorithm and a few applications to transmons systems.
A Transformation Approach to Optimal Control Problems with Bounded State Variables
NASA Technical Reports Server (NTRS)
Hanafy, Lawrence Hanafy
1971-01-01
A technique is described and utilized in the study of the solutions to various general problems in optimal control theory, which are converted in to Lagrange problems in the calculus of variations. This is accomplished by mapping certain properties in Euclidean space onto closed control and state regions. Nonlinear control problems with a unit m cube as control region and unit n cube as state region are considered.
ERIC Educational Resources Information Center
Thrasher, James F.; Campbell, Marci Kramish; Oates, Veronica
2004-01-01
This study used data from 850 African Americans to test optimal matching theory (OMT). OMT predicts that (1) the most important dimensions of social support depend on the controllability of the behavior and (2) different network members often provide support across health behaviors. Data were gathered on social support source for physical…
Decentralized optimal control of dynamical systems under uncertainty
NASA Astrophysics Data System (ADS)
Gabasov, R.; Dmitruk, N. M.; Kirillova, F. M.
2011-07-01
The problem of optimal control of a group of interconnected dynamical objects under uncertainty is considered. The cases are examined in which the centralized control of the group of objects is impossible due to delay in the channel for information exchange between the group members. Optimal self-control algorithms in real time for each dynamical object are proposed. Various types of a priori and current information about the behavior of the group members and about uncertainties in the system are examined. The proposed methods supplement the earlier developed optimal control methods for an individual dynamical system and the methods of decentralized optimal control of deterministic objects. The results are illustrated with examples.
A Multiobjective Optimization Framework for Stochastic Control of Complex Systems
Malikopoulos, Andreas; Maroulas, Vasileios; Xiong, Professor Jie
2015-01-01
This paper addresses the problem of minimizing the long-run expected average cost of a complex system consisting of subsystems that interact with each other and the environment. We treat the stochastic control problem as a multiobjective optimization problem of the one-stage expected costs of the subsystems, and we show that the control policy yielding the Pareto optimal solution is an optimal control policy that minimizes the average cost criterion for the entire system. For practical situations with constraints consistent to those we study here, our results imply that the Pareto control policy may be of value in deriving online an optimal control policy in complex systems.
NASA Astrophysics Data System (ADS)
Kim, Yoonsoo
This dissertation focuses on cooperative control between multiple agents (e.g., spacecraft, UAVs). In particular, motivated by future NASA's multiple spacecraft missions, we have been guided to consider fundamental aspects of spacecraft formation flying, including collision avoidance issues; constraints on the relative position and attitude. In this venue, we have realized that one of the main challenges is dealing with nonconvex state constraints. In this dissertation, we will address such complications using classical control theory, heuristic techniques, and more recent semidefinite programming-based approaches. We then proceed to consider communication and interspacecraft sensing issues in multiple agent dynamic system setting. In this direction, we will study (1) how conventional control techniques should be augmented to meet our design objectives when the information flow between multiple agents is taken into account; (2) which information structures (e.g., information graphs) yield best performance guarantees in terms of stability, robustness, or fast agreement. In this work, we provide theoretical answers to these problems. Moreover, as many design problems involving information networks and graphs lead to combinatorial problems, which can be formulated as rank optimization problems over matrices, we consider these class of problems in this dissertation. Rank optimization problems also arise in system theory and are considered to be of paramount importance in modern control synthesis problems.
NASA Astrophysics Data System (ADS)
Viola, Lorenza; Tannor, David
2011-08-01
, quantum control of chemical reactions or high-resolution magnetic resonance spectroscopy); on the other hand, an unprecedented demand for close coupling between theory and experiment, with theoretical developments becoming more and more attuned to and driven by experimental advances as different quantum technologies continue to evolve at an impressive pace in the laboratory. Altogether, these two trends account for several of the recurrent themes in this volume, as well as in the current quantum control literature as a whole: namely, the quest for control strategies that can attain the highest degree of precision and robustness possible, while striving for efficiency and, ultimately, optimality in achieving the intended control task under realistic operational constraints. From a theory standpoint, this makes it imperative to take into account increasingly more realistic control settings; to assess the quantitative impact of limited control resources and/or system knowledge; and to provide a rigorous and general foundation for existing experimental approaches in order to further enhance applicability and performance. From an experimental standpoint, renewed emphasis is in turn placed on validating theoretical predictions and benchmarking performance, so that the limiting constraints can be singled out for additional theoretical analysis and guidance. This ongoing cross-talk is clearly reflected in this collection, which brings together theoreticians and experimentalists, with a significant fraction of the papers reporting on combined quantum control theory-experiment efforts. While a precise categorization would neither be possible nor desirable, contributions to this volume have been loosely grouped into five broad sections. This grouping has been made in the hope that connections between different problems and/or technical approaches will become more transparent, facilitating the transfer of concepts and methods. The special issue opens with a section devoted to open
Optimal spacecraft attitude control using collocation and nonlinear programming
NASA Astrophysics Data System (ADS)
Herman, A. L.; Conway, B. A.
1992-10-01
Direct collocation with nonlinear programming (DCNLP) is employed to find the optimal open-loop control histories for detumbling a disabled satellite. The controls are torques and forces applied to the docking arm and joint and torques applied about the body axes of the OMV. Solutions are obtained for cases in which various constraints are placed on the controls and in which the number of controls is reduced or increased from that considered in Conway and Widhalm (1986). DCLNP works well when applied to the optimal control problem of satellite attitude control. The formulation is straightforward and produces good results in a relatively small amount of time on a Cray X/MP with no a priori information about the optimal solution. The addition of joint acceleration to the controls significantly reduces the control magnitudes and optimal cost. In all cases, the torques and acclerations are modest and the optimal cost is very modest.
Optimality of incompletely measurable active and passive attitude control systems. [for satellites
NASA Technical Reports Server (NTRS)
Schiehlen, W.; Popp, K.
1973-01-01
Passive attitude control systems and active systems with incomplete state measurements are only suboptimal systems in the sense of optimal control theory, since optimal systems require complete state measurements or state estimations. An optimal system, then, requires additional hardware (especially in the case of flexible spacecraft) which results in higher costs. Therefore, it is a real engineering problem to determine how much an optimal system exceeds the suboptimal system, or in other words, what is the suboptimal system's degree of optimality. The problem will be treated in three steps: (1) definition of the degree of optimality for linear, time-invariant systems; (2) a computation method using the quadratic cost functional; (3) application to a gravity-gradient stabilized three-body satellite and a spinning flexible satellite.
Optimal control of nonlinear continuous-time systems in strict-feedback form.
Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani
2015-10-01
This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results. PMID:26111400
Optimal stochastic control in natural resource management: Framework and examples
Williams, B.K.
1982-01-01
A framework is presented for the application of optimal control methods to natural resource problems. An expression of the optimal control problem appropriate for renewable natural resources is given and its application to Markovian systems is presented in some detail. Three general approaches are outlined for determining optimal control of infinite time horizon systems and three examples from the natural resource literature are used for illustration.
Application of control theory to dynamic systems simulation
NASA Technical Reports Server (NTRS)
Auslander, D. M.; Spear, R. C.; Young, G. E.
1982-01-01
The application of control theory is applied to dynamic systems simulation. Theory and methodology applicable to controlled ecological life support systems are considered. Spatial effects on system stability, design of control systems with uncertain parameters, and an interactive computing language (PARASOL-II) designed for dynamic system simulation, report quality graphics, data acquisition, and simple real time control are discussed.
Optimizing the controllability of arbitrary networks with genetic algorithm
NASA Astrophysics Data System (ADS)
Li, Xin-Feng; Lu, Zhe-Ming
2016-04-01
Recently, as the controllability of complex networks attracts much attention, how to optimize networks' controllability has become a common and urgent problem. In this paper, we develop an efficient genetic algorithm oriented optimization tool to optimize the controllability of arbitrary networks consisting of both state nodes and control nodes under Popov-Belevitch-Hautus rank condition. The experimental results on a number of benchmark networks show the effectiveness of this method and the evolution of network topology is captured. Furthermore, we explore how network structure affects its controllability and find that the sparser a network is, the more control nodes are needed to control it and the larger the differences between node degrees, the more control nodes are needed to achieve the full control. Our framework provides an alternative to controllability optimization and can be applied to arbitrary networks without any limitations.
Optimizing Computer Assisted Instruction By Applying Principles of Learning Theory.
ERIC Educational Resources Information Center
Edwards, Thomas O.
The development of learning theory and its application to computer-assisted instruction (CAI) are described. Among the early theoretical constructs thought to be important are E. L. Thorndike's concept of learning connectisms, Neal Miller's theory of motivation, and B. F. Skinner's theory of operant conditioning. Early devices incorporating those…
Factorization and reduction methods for optimal control of distributed parameter systems
NASA Technical Reports Server (NTRS)
Burns, J. A.; Powers, R. K.
1985-01-01
A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.
Research on Air Flow Measurement and Optimization of Control Algorithm in Air Disinfection System
NASA Astrophysics Data System (ADS)
Bing-jie, Li; Jia-hong, Zhao; Xu, Wang; Amuer, Mohamode; Zhi-liang, Wang
2013-01-01
As the air flow control system has the characteristics of delay and uncertainty, this research designed and achieved a practical air flow control system by using the hydrodynamic theory and the modern control theory. Firstly, the mathematical model of the air flow distribution of the system is analyzed from the hydrodynamics perspective. Then the model of the system is transformed into a lumped parameter state space expression by using the Galerkin method. Finally, the air flow is distributed more evenly through the estimation of the system state and optimal control. The simulation results show that this algorithm has good robustness and anti-interference ability
A Nonlinear Physics-Based Optimal Control Method for Magnetostrictive Actuators
NASA Technical Reports Server (NTRS)
Smith, Ralph C.
1998-01-01
This paper addresses the development of a nonlinear optimal control methodology for magnetostrictive actuators. At moderate to high drive levels, the output from these actuators is highly nonlinear and contains significant magnetic and magnetomechanical hysteresis. These dynamics must be accommodated by models and control laws to utilize the full capabilities of the actuators. A characterization based upon ferromagnetic mean field theory provides a model which accurately quantifies both transient and steady state actuator dynamics under a variety of operating conditions. The control method consists of a linear perturbation feedback law used in combination with an optimal open loop nonlinear control. The nonlinear control incorporates the hysteresis and nonlinearities inherent to the transducer and can be computed offline. The feedback control is constructed through linearization of the perturbed system about the optimal system and is efficient for online implementation. As demonstrated through numerical examples, the combined hybrid control is robust and can be readily implemented in linear PDE-based structural models.
NASA Astrophysics Data System (ADS)
Kim, C. H.; Park, H. J.; Lee, J.; Lee, H. W.; Lee, K. D.
2015-05-01
This paper develops a discrete optimal control based on the multi-rate observer method for electromagnetic suspension systems in order to levitate the vehicle, maintaining the desired gap. The proposed multi-rate compensator consists of two parts which are the discrete Kalman filter and the optimal control law. The Kalman filter estimates all states with fast sampling rate time, using a slowly measured output from the gap sensor. The optimal control law is determined by linear matrix inequality optimization for the discrete time multiple input system obtained by the lifting operator. The proposed multi-rate controller has the advantages to guarantee the stability of the slow-rate optimal control and maintain the performance of fast-rate control. The simulation and experiment show the effectiveness of the proposed control method.
A multiple objective optimization approach to aircraft control systems design
NASA Technical Reports Server (NTRS)
Tabak, D.; Schy, A. A.; Johnson, K. G.; Giesy, D. P.
1979-01-01
The design of an aircraft lateral control system, subject to several performance criteria and constraints, is considered. While in the previous studies of the same model a single criterion optimization, with other performance requirements expressed as constraints, has been pursued, the current approach involves a multiple criteria optimization. In particular, a Pareto optimal solution is sought.
Optimal control of blending and melting of copper concentrates
NASA Astrophysics Data System (ADS)
Imanbekova, Ulzhan; Hotra, Oleksandra; Koshimbayev, Shamil; Popiel, Piotr; Tanaś, Jacek
2015-09-01
The mathematical models of the melting process, the optimization criterion and constraints on the input and controlling variables and the values of the conductivities of the melt under the electrodes and the phase voltages are used to solve the optimization problem of the electrical regime of the electric furnace. In this paper the optimal variant of the electrical regime of the furnace for the electromelting and blending processing of copper concentrates is considered, which can be provided by the optimal immersion of electrodes. The optimal parameters of the technological process of electromelting and blending are calculated. The proposed mathematical model could be applied for melting process optimization.
Control theory based airfoil design for potential flow and a finite volume discretization
NASA Technical Reports Server (NTRS)
Reuther, J.; Jameson, A.
1994-01-01
This paper describes the implementation of optimization techniques based on control theory for airfoil design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for two-dimensional profiles in which the shape is determined by a conformal transformation from a unit circle, and the control is the mapping function. The goal of our present work is to develop a method which does not depend on conformal mapping, so that it can be extended to treat three-dimensional problems. Therefore, we have developed a method which can address arbitrary geometric shapes through the use of a finite volume method to discretize the potential flow equation. Here the control law serves to provide computationally inexpensive gradient information to a standard numerical optimization method. Results are presented, where both target speed distributions and minimum drag are used as objective functions.
Optimal control of a boiling water reactor load-following operation
Lin, C.; Lin, Z.P.; Jiang, W.J. . Dept. of Nuclear Engineering)
1989-06-01
The authors describe a method based on a forward dynamic programming technique applied to load-following control of a boiling water reactor. The control strategy obtained is optimal and satisfies operation constraints. A course-mesh, one-dimensional model using the two-group diffusion theory with Doppler, void, and xenon feedbacks is developed to reduce computer time. The control rods are assumed to be fixed during load maneuvers, and variations in core power are accomplished through core flow.
Theory and Computation of Optimal Low- and Medium- Thrust Orbit Transfers
NASA Technical Reports Server (NTRS)
Goodson, Troy D.; Chuang, Jason C. H.; Ledsinger, Laura A.
1996-01-01
This report presents new theoretical results which lead to new algorithms for the computation of fuel-optimal multiple-burn orbit transfers of low and medium thrust. Theoretical results introduced herein show how to add burns to an optimal trajectory and show that the traditional set of necessary conditions may be replaced with a much simpler set of equations. Numerical results are presented to demonstrate the utility of the theoretical results and the new algorithms. Two indirect methods from the literature are shown to be effective for the optimal orbit transfer problem with relatively small numbers of burns. These methods are the Minimizing Boundary Condition Method (MBCM) and BOUNDSCO. Both of these methods make use of the first-order necessary conditions exactly as derived by optimal control theory. Perturbations due to Earth's oblateness and atmospheric drag are considered. These perturbations are of greatest interest for transfers that take place between low Earth orbit altitudes and geosynchronous orbit altitudes. Example extremal solutions including these effects and computed by the aforementioned methods are presented. An investigation is also made into a suboptimal multiple-burn guidance scheme. The FORTRAN code developed for this study has been collected together in a package named ORBPACK. ORBPACK's user manual is provided as an appendix to this report.
Ruiz-Cruz, Riemann; Sanchez, Edgar N; Ornelas-Tellez, Fernando; Loukianov, Alexander G; Harley, Ronald G
2013-12-01
In this paper, the authors propose a particle swarm optimization (PSO) for a discrete-time inverse optimal control scheme of a doubly fed induction generator (DFIG). For the inverse optimal scheme, a control Lyapunov function (CLF) is proposed to obtain an inverse optimal control law in order to achieve trajectory tracking. A posteriori, it is established that this control law minimizes a meaningful cost function. The CLFs depend on matrix selection in order to achieve the control objectives; this matrix is determined by two mechanisms: initially, fixed parameters are proposed for this matrix by a trial-and-error method and then by using the PSO algorithm. The inverse optimal control scheme is illustrated via simulations for the DFIG, including the comparison between both mechanisms. PMID:24273145
Identification-free adaptive optimal control based on switching predictive models
NASA Astrophysics Data System (ADS)
Luo, Wenguang; Pan, Shenghui; Ma, Zhaomin; Lan, Hongli
2008-10-01
An identification-free adaptive optimal control based on switching predictive models is proposed for the systems with big inertia, long time delay and multi models. Multi predictive models are set in the identification-free adaptive predictive control, and switched according to the optimal switching instants in control of the switching law along with the system running situations in real time. The switching law is designed based on the most important character parameter of the systems, and the optimal switching instants are computed out with the optimal theory for switched systems. The simulation test results show the proposed method is suitable to the systems, such as superheated steam temperature systems of electric power plants, can provide excellent control performance, improve rejecting disturbance ability and self-adaptability, and has lower demand on the predictive model precision.
Nonlinear model predictive control based on collective neurodynamic optimization.
Yan, Zheng; Wang, Jun
2015-04-01
In general, nonlinear model predictive control (NMPC) entails solving a sequential global optimization problem with a nonconvex cost function or constraints. This paper presents a novel collective neurodynamic optimization approach to NMPC without linearization. Utilizing a group of recurrent neural networks (RNNs), the proposed collective neurodynamic optimization approach searches for optimal solutions to global optimization problems by emulating brainstorming. Each RNN is guaranteed to converge to a candidate solution by performing constrained local search. By exchanging information and iteratively improving the starting and restarting points of each RNN using the information of local and global best known solutions in a framework of particle swarm optimization, the group of RNNs is able to reach global optimal solutions to global optimization problems. The essence of the proposed collective neurodynamic optimization approach lies in the integration of capabilities of global search and precise local search. The simulation results of many cases are discussed to substantiate the effectiveness and the characteristics of the proposed approach. PMID:25608315
Stochastic Optimal Control for Series Hybrid Electric Vehicles
Malikopoulos, Andreas
2013-01-01
Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.
A Framework for Optimal Control Allocation with Structural Load Constraints
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc
2010-01-01
Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.
Optimizing Sensor and Actuator Arrays for ASAC Noise Control
NASA Technical Reports Server (NTRS)
Palumbo, Dan; Cabell, Ran
2000-01-01
This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.
Application of modern control theory to the design of optimum aircraft controllers
NASA Technical Reports Server (NTRS)
Power, L. J.
1973-01-01
The synthesis procedure presented is based on the solution of the output regulator problem of linear optimal control theory for time-invariant systems. By this technique, solution of the matrix Riccati equation leads to a constant linear feedback control law for an output regulator which will maintain a plant in a particular equilibrium condition in the presence of impulse disturbances. Two simple algorithms are presented that can be used in an automatic synthesis procedure for the design of maneuverable output regulators requiring only selected state variables for feedback. The first algorithm is for the construction of optimal feedforward control laws that can be superimposed upon a Kalman output regulator and that will drive the output of a plant to a desired constant value on command. The second algorithm is for the construction of optimal Luenberger observers that can be used to obtain feedback control laws for the output regulator requiring measurement of only part of the state vector. This algorithm constructs observers which have minimum response time under the constraint that the magnitude of the gains in the observer filter be less than some arbitrary limit.
Optimal speech motor control and token-to-token variability: a Bayesian modeling approach.
Patri, Jean-François; Diard, Julien; Perrier, Pascal
2015-12-01
The remarkable capacity of the speech motor system to adapt to various speech conditions is due to an excess of degrees of freedom, which enables producing similar acoustical properties with different sets of control strategies. To explain how the central nervous system selects one of the possible strategies, a common approach, in line with optimal motor control theories, is to model speech motor planning as the solution of an optimality problem based on cost functions. Despite the success of this approach, one of its drawbacks is the intrinsic contradiction between the concept of optimality and the observed experimental intra-speaker token-to-token variability. The present paper proposes an alternative approach by formulating feedforward optimal control in a probabilistic Bayesian modeling framework. This is illustrated by controlling a biomechanical model of the vocal tract for speech production and by comparing it with an existing optimal control model (GEPPETO). The essential elements of this optimal control model are presented first. From them the Bayesian model is constructed in a progressive way. Performance of the Bayesian model is evaluated based on computer simulations and compared to the optimal control model. This approach is shown to be appropriate for solving the speech planning problem while accounting for variability in a principled way. PMID:26497359
Finding Optimal Gains In Linear-Quadratic Control Problems
NASA Technical Reports Server (NTRS)
Milman, Mark H.; Scheid, Robert E., Jr.
1990-01-01
Analytical method based on Volterra factorization leads to new approximations for optimal control gains in finite-time linear-quadratic control problem of system having infinite number of dimensions. Circumvents need to analyze and solve Riccati equations and provides more transparent connection between dynamics of system and optimal gain.
EFFICIENCY OPTIMIZATION CONTROL OF AC INDUCTION MOTORS: INITIAL LABORATORY RESULTS
The report discusses the development of a fuzzy logic, energy-optimizing controller to improve the efficiency of motor/drive combinations that operate at varying loads and speeds. his energy optimizer is complemented by a sensorless speed controller that maintains motor shaft rev...
A criterion for joint optimization of identification and robust control
NASA Technical Reports Server (NTRS)
Bayard, D. S.; Yam, Y.; Mettler, E.
1992-01-01
A criterion for system identification is developed that is consistent with the intended used of the fitted model for modern robust control synthesis. Specifically, a joint optimization problem is posed which simultaneously solves the plant model estimate and control design, so as to optimize robust performance over the set of plants consistent with a specified experimental data set.
A quadratic weight selection algorithm. [for optimal flight control
NASA Technical Reports Server (NTRS)
Broussard, J. R.
1981-01-01
A new numerical algorithm is presented which determines a positive semi-definite state weighting matrix in the linear-quadratic optimal control design problem. The algorithm chooses the weighting matrix by placing closed-loop eigenvalues and eigenvectors near desired locations using optimal feedback gains. A simplified flight control design example is used to illustrate the algorithms capabilities.
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
ERIC Educational Resources Information Center
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
Attitude Control Optimization for ROCSAT-2 Operation
NASA Astrophysics Data System (ADS)
Chern, Jeng-Shing; Wu, A.-M.
one revolution. The purpose of this paper is to present the attitude control design optimization such that the maximum solar energy is ingested while minimum maneuvering energy is dissipated. The strategy includes the maneuvering sequence design, the minimization of angular path, the sizing of three magnetic torquers, and the trade-off of the size, number and orientations arrangement of momentum wheels.
Application of optimal estimation and control concepts to a bank-to-turn missile
NASA Astrophysics Data System (ADS)
Ohlmeyer, E. J.
1987-07-01
The design and evaluation of optimal estimators and optimal control laws for application to bank-to-turn missiles was addressed. Two guidance laws, one based on modern control theory and the other on an augmented form of proportional navigation, were compared to the classical implementation of proportional navigation. The former two control laws require the use of a state estimator. An extended Kalman filter was devised for that purpose. Performance of the three guidance laws was compared on the basis of average miss distance achieved for a number of engagement scenarios.
Edge orientation for optimizing controllability of complex networks.
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009)], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects. PMID:25375546
Edge orientation for optimizing controllability of complex networks
NASA Astrophysics Data System (ADS)
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009), 10.1103/PhysRevLett.103.228702], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects.
Matching trajectory optimization and nonlinear tracking control for HALE
NASA Astrophysics Data System (ADS)
Lee, Sangjong; Jang, Jieun; Ryu, Hyeok; Lee, Kyun Ho
2014-11-01
This paper concerns optimal trajectory generation and nonlinear tracking control for stratospheric airship platform of VIA-200. To compensate for the mismatch between the point-mass model of optimal trajectory and the 6-DOF model of the nonlinear tracking problem, a new matching trajectory optimization approach is proposed. The proposed idea reduces the dissimilarity of both problems and reduces the uncertainties in the nonlinear equations of motion for stratospheric airship. In addition, its refined optimal trajectories yield better results under jet stream conditions during flight. The resultant optimal trajectories of VIA-200 are full three-dimensional ascent flight trajectories reflecting the realistic constraints of flight conditions and airship performance with and without a jet stream. Finally, 6-DOF nonlinear equations of motion are derived, including a moving wind field, and the vectorial backstepping approach is applied. The desirable tracking performance is demonstrated that application of the proposed matching optimization method enables the smooth linkage of trajectory optimization to tracking control problems.
Optimization and Control of Electric Power Systems
Lesieutre, Bernard C.; Molzahn, Daniel K.
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Information spread in networks: Games, optimal control, and stabilization
NASA Astrophysics Data System (ADS)
Khanafer, Ali
This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack
Anderson, D.R.
1975-01-01
Optimal exploitation strategies were studied for an animal population in a Markovian (stochastic, serially correlated) environment. This is a general case and encompasses a number of important special cases as simplifications. Extensive empirical data on the Mallard (Anas platyrhynchos) were used as an example of general theory. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. A general mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. The literature and analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, two hypotheses were explored: (1) exploitation mortality represents a largely additive form of mortality, and (2) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under the rather general conditions. Direct feedback control was an integral component in the optimal decision-making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. If we assume that exploitation is largely an additive force of mortality in Mallards, then optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slight concave function of the environmental conditions. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the Mallard breeding population. Dynamic programming is suggested as a very general
Exact optimal solution for a class of dual control problems
NASA Astrophysics Data System (ADS)
Cao, Suping; Qian, Fucai; Wang, Xiaomei
2016-07-01
This paper considers a discrete-time stochastic optimal control problem for which only measurement equation is partially observed with unknown constant parameters taking value in a finite set of stochastic systems. Because of the fact that the cost-to-go function at each stage contains variance and the non-separability of the variance is so complicated that the dynamic programming cannot be successfully applied, the optimal solution has not been found. In this paper, a new approach to the optimal solution is proposed by embedding the original non-separable problem into a separable auxiliary problem. The theoretical condition on which the optimal solution of the original problem can be attained from a set of solutions of the auxiliary problem is established. In addition, the optimality of the interchanging algorithm is proved and the analytical solution of the optimal control is also obtained. The performance of this controller is illustrated with a simple example.
A pseudospectral method for optimal control of open quantum systems.
Li, Jr-Shin; Ruths, Justin; Stefanatos, Dionisis
2009-10-28
In this paper, we present a unified computational method based on pseudospectral approximations for the design of optimal pulse sequences in open quantum systems. The proposed method transforms the problem of optimal pulse design, which is formulated as a continuous-time optimal control problem, to a finite-dimensional constrained nonlinear programming problem. This resulting optimization problem can then be solved using existing numerical optimization suites. We apply the Legendre pseudospectral method to a series of optimal control problems on open quantum systems that arise in nuclear magnetic resonance spectroscopy in liquids. These problems have been well studied in previous literature and analytical optimal controls have been found. We find an excellent agreement between the maximum transfer efficiency produced by our computational method and the analytical expressions. Moreover, our method permits us to extend the analysis and address practical concerns, including smoothing discontinuous controls as well as deriving minimum-energy and time-optimal controls. The method is not restricted to the systems studied in this article and is applicable to optimal manipulation of both closed and open quantum systems. PMID:19894930
A mathematical basis for the design and design optimization of adaptive trusses in precision control
NASA Technical Reports Server (NTRS)
Das, S. K.; Utku, S.; Chen, G.-S.; Wada, B. K.
1991-01-01
A mathematical basis for the optimal design of adaptive trusses to be used in supporting precision equipment is provided. The general theory of adaptive structures is introduced, and the global optimization problem of placing a limited number, q, of actuators, so as to maximally achieve precision control and provide prestress, is stated. Two serialized optimization problems, namely, optimal actuator placement for prestress and optimal actuator placement for precision control, are addressed. In the case of prestressing, the computation of a 'desired' prestress is discussed, the interaction between actuators and redundants in conveying the prestress is shown in its mathematical form, and a methodology for arriving at the optimal placement of actuators and additional redundants is discussed. With regard to precision control, an optimal placement scheme (for q actuators) for maximum 'authority' over the precision points is suggested. The results of the two serialized optimization problems are combined to give a suboptimal solution to the global optimization problem. A method for improving this suboptimal actuator placement scheme by iteration is presented.
Optimized perturbation theory applied to factorization scheme dependence
NASA Astrophysics Data System (ADS)
Stevenson, P. M.; Politzer, H. David
We reconsider the application of the "optimization" procedure to the problem of factorization scheme dependence in finite-order QCD calculations. The main difficulty encountered in a previous analysis disappears once an algebraic error is corrected.
NASA Technical Reports Server (NTRS)
Banks, H. T.; Kunisch, K.
1982-01-01
Approximation results from linear semigroup theory are used to develop a general framework for convergence of approximation schemes in parameter estimation and optimal control problems for nonlinear partial differential equations. These ideas are used to establish theoretical convergence results for parameter identification using modal (eigenfunction) approximation techniques. Results from numerical investigations of these schemes for both hyperbolic and parabolic systems are given.
Optimal control for a tuberculosis model with undetected cases in Cameroon
NASA Astrophysics Data System (ADS)
Moualeu, D. P.; Weiser, M.; Ehrig, R.; Deuflhard, P.
2015-03-01
This paper considers the optimal control of tuberculosis through education, diagnosis campaign and chemoprophylaxis of latently infected. A mathematical model which includes important components such as undiagnosed infectious, diagnosed infectious, latently infected and lost-sight infectious is formulated. The model combines a frequency dependent and a density dependent force of infection for TB transmission. Through optimal control theory and numerical simulations, a cost-effective balance of two different intervention methods is obtained. Seeking to minimize the amount of money the government spends when tuberculosis remain endemic in the Cameroonian population, Pontryagin's maximum principle is used to characterize the optimal control. The optimality system is derived and solved numerically using the forward-backward sweep method (FBSM). Results provide a framework for designing cost-effective strategies for diseases with multiple intervention methods. It comes out that combining chemoprophylaxis and education, the burden of TB can be reduced by 80% in 10 years.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1989-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1990-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
Weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1991-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
Frequency domain synthesis of optimal inputs for adaptive identification and control
NASA Technical Reports Server (NTRS)
Fu, Li-Chen; Sastry, Shankar
1987-01-01
The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
1975-01-01
Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.
Polyhedral Interpolation for Optimal Reaction Control System Jet Selection
NASA Technical Reports Server (NTRS)
Gefert, Leon P.; Wright, Theodore
2014-01-01
An efficient algorithm is described for interpolating optimal values for spacecraft Reaction Control System jet firing duty cycles. The algorithm uses the symmetrical geometry of the optimal solution to reduce the number of calculations and data storage requirements to a level that enables implementation on the small real time flight control systems used in spacecraft. The process minimizes acceleration direction errors, maximizes control authority, and minimizes fuel consumption.
Reliability of the Optimized Perturbation Theory for scalar fields at finite temperature
Farias, R. L.; Teixeira, D. L. Jr.; Ramos, R. O.
2013-03-25
The thermodynamics of a massless scalar field with a quartic interaction is studied up to third order in the Optimized Perturbation Theory (OPT) method. A comparison with other nonperturbative approaches is performed such that the reliability of OPT is accessed.
Datta, Saurav; Biswas, Ajay; Bhaumik, Swapan; Majumdar, Gautam
2011-01-17
Multi-objective optimization problem has been solved in order to estimate an optimal process environment consisting of optimal parametric combination to achieve desired quality indicators (related to bead geometry) of submerged arc weld of mild steel. The quality indicators selected in the study were bead height, penetration depth, bead width and percentage dilution. Taguchi method followed by utility concept has been adopted to evaluate the optimal process condition achieving multiple objective requirements of the desired quality weld.
Control strategy optimization of HVAC plants
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Optimal control of Atlantic population Canada geese
Hauser, C.E.; Runge, M.C.; Cooch, E.G.; Johnson, F.A.; Harvey, W.F., IV
2007-01-01
Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy.
Multiobjective decision theory for computational optimization in radiation therapy.
Yu, Y
1997-09-01
Machine-guided iterative optimization in radiation oncology requires ordinal or cardinal ranking of competing treatment plans. When the clinical objectives are multifaceted and incommensurable, the ranking formalism must take into account the decision maker's tradeoff strategies in a multidimensional decision space. To capture the decision processes in treatment planning, a multiobjective decision-theoretic scheme is formulated. Ranking among a group of candidate plans is based on a generalized distance metric. A dynamic metric weighting function is defined based on the state energy of the decision system, which is assumed to undergo thermodynamic cooling with iteration time. The decision maker is required to specify a baseline ranking of the objectives, which is taken to be the ground state of the decision system. This decision-theoretic formalism was applied to idealized cases in stereotactic radiosurgery and prostatic implantation, using the genetic algorithm as the optimization engine. The optimization pathways and the outcome at limited horizons indicated that the combined scheme of decision-theoretic steering and iterative optimization was robust and produced treatment plans consistent with the user's expectation. The effect of treatment uncertainties was simulated using imperfect objectives; however, certain recurring plans could be identified as optimized baseline solutions. Overall, the present formalism provides a realistic alternative to complete utility assessment or human-guided exploration of the efficient solution set. PMID:9304573
Multi-host transmission dynamics of schistosomiasis and its optimal control.
Ding, Chunxiao; Qiu, Zhipeng; Zhu, Huaiping
2015-10-01
In this paper we formulate a dynamical model to study the transmission dynamics of schistosomiasis in humans and snails. We also incorporate bovines in the model to study their impact on transmission and controlling the spread of Schistosoma japonicum in humans in China. The dynamics of the model is rigorously analyzed by using the theory of dynamical systems. The theoretical results show that the disease free equilibrium is globally asymptotically stable if R0 < 1, and if R0 > 1 the system has only one positive equilibrium. The local stability of the unique positive equilibrium is investigated and sufficient conditions are also provided for the global stability of the positive equilibrium. The optimal control theory are further applied to the model to study the corresponding optimal control problem. Both analytical and numerical results suggest that: (a) the infected bovines play an important role in the spread of schistosomiasis among humans, and killing the infected bovines will be useful to prevent transmission of schistosomiasis among humans; (b) optimal control strategy performs better than the constant controls in reducing the prevalence of the infected human and the cost for implementing optimal control is much less than that for constant controls; and PMID:26280190
Theory of automatic control of airplanes
NASA Technical Reports Server (NTRS)
Weiss, Herbert K
1939-01-01
Methods of automatically controlling the airplane are reviewed. Equations for the controlled motion including inertia effects of the control are developed and methods of investigating the stability of the resulting fifth and higher order equations are presented. The equations for longitudinal and lateral motion with both ideal and non-ideal controls are developed in dimensionless form in terms of control parameters based on simple dynamic tests of the isolated control unit.
Studies on controllability of directed networks with extremal optimization
NASA Astrophysics Data System (ADS)
Ding, Jin; Lu, Yong-Zai; Chu, Jian
2013-12-01
Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and attractive subjects for both network and control communities. In this paper, based on a given directed-weighted network with both state and control nodes, a novel optimization tool with extremal dynamics to generate an optimal network topology with minimum control nodes and complete controllability under Kalman’s rank condition has been developed. The experimental results on a number of popular benchmark networks show the proposed tool is effective to identify the minimum control nodes which are sufficient to guide the whole network’s dynamics and provide the evolution of network topology during the optimization process. We also find the conclusion: “the sparse networks need more control nodes than the dense, and the homogeneous networks need fewer control nodes compared to the heterogeneous” (Liu et al., 2011 [18]), is also applicable to network complete controllability. These findings help us to understand the network dynamics and make a real-world network under the desired control. Moreover, compared with the relevant research results on structural controllability with minimum driver nodes, the proposed solution methodology may also be applied to other constrained network optimization problems beyond complete controllability with minimum control nodes.
Relationships between digital signal processing and control and estimation theory
NASA Technical Reports Server (NTRS)
Willsky, A. S.
1978-01-01
Research directions in the fields of digital signal processing and modern control and estimation theory are discussed. Stability theory, linear prediction and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing are considered in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the disciplines.
Time-optimal maneuvering control of a rigid spacecraft
NASA Astrophysics Data System (ADS)
Lai, Li-Chun; Yang, Chi-Ching; Wu, Chia-Ju
2007-05-01
The time-optimal rest-to-rest maneuvering control problem of a rigid spacecraft is studied in this paper. By utilizing an iterative procedure, this problem is formulated and solved as a constrained nonlinear programming (NLP) one. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. The optimization object is to minimize the sampling period below a specific minimum value, which is set in advance considering the accuracy of discretization. To generate initial feasible solutions of the NLP problem, a genetic-algorithm-based is also proposed such that the optimization process can be started from many different points to find the globally optimal solution. With the proposed method, one can find a time-optimal rest-to-rest maneuver of the rigid spacecraft between two attitudes. To show the feasibility of the proposed method, simulation results are included for illustration.
Time-optimal control of the magnetically levitated photolithography platen
Redmond, J.; Tucker, S.
1995-01-01
This report summarizes two approaches to time-optimal control of a nonlinear magnetically levitated platen. The system of interest is a candidate technology for next-generation photolithography machines used in the manufacture of integrated circuits. The dynamics and the variable peak control force of the electro-magnetic actuators preclude the direct application of classical time-optimal control methodologies for determining optimal rest-to-rest maneuver strategies. Therefore, this study explores alternate approaches using a previously developed computer simulation. In the first approach, conservative estimates of the available control forces are used to generate suboptimal switching curves. In the second approach, exact solutions are determined iteratively and used as a training set for an artificial neural network. The trained network provides optimal actuator switching times that incorporate the full nonlinearities of the magnetic levitation actuators. Sample problems illustrate the effectiveness of these techniques as compared to traditional proportional-derivative control.
Optimal Control Modification for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
Cost benefit theory and optimal design of gene regulation functions
NASA Astrophysics Data System (ADS)
Kalisky, Tomer; Dekel, Erez; Alon, Uri
2007-12-01
Cells respond to the environment by regulating the expression of genes according to environmental signals. The relation between the input signal level and the expression of the gene is called the gene regulation function. It is of interest to understand the shape of a gene regulation function in terms of the environment in which it has evolved and the basic constraints of biological systems. Here we address this by presenting a cost-benefit theory for gene regulation functions that takes into account temporally varying inputs in the environment and stochastic noise in the biological components. We apply this theory to the well-studied lac operon of E. coli. The present theory explains the shape of this regulation function in terms of temporal variation of the input signals, and of minimizing the deleterious effect of cell-cell variability in regulatory protein levels. We also apply the theory to understand the evolutionary tradeoffs in setting the number of regulatory proteins and for selection of feed-forward loops in genetic circuits. The present cost-benefit theory can be used to understand the shape of other gene regulatory functions in terms of environment and noise constraints.
Novel multireceiver communication systems configurations based on optimal estimation theory
NASA Technical Reports Server (NTRS)
Kumar, Rajendra
1992-01-01
A novel multireceiver configuration for carrier arraying and/or signal arraying is presented. The proposed configuration is obtained by formulating the carrier and/or signal arraying problem as an optimal estimation problem, and it consists of two stages. The first stage optimally estimates various phase processes received at different receivers with coupled phase-locked loops wherein the individual loops acquire and track their respective receivers' phase processes but are aided by each other in an optimal manner via LF error signals. The proposed configuration results in the minimization of the the effective radio loss at the combiner output, and thus maximization of energy per bit to noise power spectral density ratio is achieved. A novel adaptive algorithm for the estimator of the signal model parameters when these are not known a priori is also presented.
Time dependent optimal switching controls in online selling models
Bradonjic, Milan; Cohen, Albert
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
Optimal control of a harmonic oscillator: Economic interpretations
NASA Astrophysics Data System (ADS)
Janová, Jitka; Hampel, David
2013-10-01
Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derive online the optimal control policy in complex systems.
Bridging developmental systems theory and evolutionary psychology using dynamic optimization.
Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H
2013-07-01
Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach. PMID:23786476
Deterministic methods for multi-control fuel loading optimization
NASA Astrophysics Data System (ADS)
Rahman, Fariz B. Abdul
We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.
Optimal actuator location of minimum norm controls for heat equation with general controlled domain
NASA Astrophysics Data System (ADS)
Guo, Bao-Zhu; Xu, Yashan; Yang, Dong-Hui
2016-09-01
In this paper, we study optimal actuator location of the minimum norm controls for a multi-dimensional heat equation with control defined in the space L2 (Ω × (0 , T)). The actuator domain is time-varying in the sense that it is only required to have a prescribed Lebesgue measure for any moment. We select an optimal actuator location so that the optimal control takes its minimal norm over all possible actuator domains. We build a framework of finding the Nash equilibrium so that we can develop a sufficient and necessary condition to characterize the optimal relaxed solutions for both actuator location and corresponding optimal control of the open-loop system. The existence and uniqueness of the optimal classical solutions are therefore concluded. As a result, we synthesize both optimal actuator location and corresponding optimal control into a time-varying feedbacks.
Stability analysis and optimal control of an epidemic model with awareness programs by media.
Misra, A K; Sharma, Anupama; Shukla, J B
2015-12-01
The impact of awareness campaigns and behavioral responses on epidemic outbreaks has been reported at times. However, to what extent does the provision of awareness and behavioral changes affect the epidemic trajectory is unknown, but important from the public health standpoint. To address this question, we formulate a mathematical model to study the effect of awareness campaigns by media on the outbreak of an epidemic. The awareness campaigns are treated as an intervention for the emergent disease. These awareness campaigns divide the whole populations into two subpopulation; aware and unaware, by inducing behavioral changes amongst them. The awareness campaigns are included explicitly as a separate dynamic variable in the modeling process. The model is analyzed qualitatively using stability theory of differential equations. We have also identified an optimal implementation rate of awareness campaigns so that disease can be controlled with minimal possible expenditure on awareness campaigns, using optimal control theory. The control setting is investigated analytically using optimal control theory, and the numerical solutions illustrating the optimal regimens under various assumptions are also shown. PMID:26551557
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
NASA Technical Reports Server (NTRS)
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
ERIC Educational Resources Information Center
Boman, John H., IV; Krohn, Marvin D.; Gibson, Chris L.; Stogner, John M.
2012-01-01
While associations with deviant peers are well understood to impact individual development, less is understood about the relationship between friendship quality and delinquency. Two criminological theories--social control theory and self-control theory--are able to offer an explanation for the latter relationship. Social control and self-control…
The Role of Optimism in the Interpersonal-Psychological Theory of Suicidal Behavior
ERIC Educational Resources Information Center
Rasmussen, Kathy A.; Wingate, LaRicka R.
2011-01-01
A possible relationship between Joiner's (2005) interpersonal-psychological theory of suicidal behavior and optimism was investigated by examining the ability of optimism to act as a moderator of perceived burdensomeness, thwarted belongingness, and acquired capability to engage in self-injury in the prediction of suicidal ideation. Results…
Stevenson's optimized perturbation theory applied to factorization and mass scheme dependence
NASA Astrophysics Data System (ADS)
David Politzer, H.
1982-01-01
The principles of the optimized perturbation theory proposed by Stevenson to deal with coupling constant scheme dependence are applied to the problem of factorization scheme dependence in inclusive hadron reactions. Similar considerations allow the optimization of problems with mass dependence. A serious shortcoming of the procedure, common to all applications, is discussed.
Pierre Contensou (1914-1987) and the optimization theory and applications
NASA Astrophysics Data System (ADS)
Marec, J.-P.
The outstanding contribution of Pierre Contensou in the field of optimization theory and applications is recalled, showing how the basic concepts of manoeuvrability and reachable domains can be fruitfully applied in particular to the optimization of atmospheric trajectories and orbital transfers.
NASA Astrophysics Data System (ADS)
Dovgalenko, George E.; Onischenko, Yuri I.; Loutchkina, Irina I.; Bakhtin, V.
1995-09-01
Vector tensor theory results have been applied to optimization of selfdiffraction phenomena in photorefractive crystals of symmetry 23. The giant diffraction efficiency of 77% in doped and radiate BTO crystal is observed. The signal to noise ratio was 600. Optimization algorithm for improving this ratio is proposed. These results are applied to small size sensors for some engineering applications.
A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers
NASA Technical Reports Server (NTRS)
Woodard, Stanley E.; Garg, Devendra P.
1998-01-01
This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.
Optimal Control of the Parametric Oscillator
ERIC Educational Resources Information Center
Andresen, B.; Hoffmann, K. H.; Nulton, J.; Tsirlin, A.; Salamon, P.
2011-01-01
We present a solution to the minimum time control problem for a classical harmonic oscillator to reach a target energy E[subscript T] from a given initial state (q[subscript i], p[subscript i]) by controlling its frequency [omega], [omega][subscript min] less than or equal to [omega] less than or equal to [omega][subscript max]. A brief synopsis…
Towards fault-tolerant optimal control
NASA Technical Reports Server (NTRS)
Chizeck, H. J.; Willsky, A. S.
1979-01-01
The paper considers the design of fault-tolerant controllers that may endow systems with dynamic reliability. Results for jump linear quadratic Gaussian control problems are extended to include random jump costs, trajectory discontinuities, and a simple case of non-Markovian mode transitions.
NASA Technical Reports Server (NTRS)
Mehra, R. K.; Washburn, R. B.; Sajan, S.; Carroll, J. V.
1979-01-01
A hierarchical real time algorithm for optimal three dimensional control of aircraft is described. Systematic methods are developed for real time computation of nonlinear feedback controls by means of singular perturbation theory. The results are applied to a six state, three control variable, point mass model of an F-4 aircraft. Nonlinear feedback laws are presented for computing the optimal control of throttle, bank angle, and angle of attack. Real Time capability is assessed on a TI 9900 microcomputer. The breakdown of the singular perturbation approximation near the terminal point is examined Continuation methods are examined to obtain exact optimal trajectories starting from the singular perturbation solutions.
Optimized synthesis of concurrently checked controllers
Leveugle, R.; Saucier, G. )
1990-04-01
Dedicated controllers (or FSM's) with concurrent checking capabilities are of prime importance in highly dependable applications. This paper presents a new method for introducing on-line test facilities in a controller with a very low overhead. This on-line test consists in detecting illegal paths in the control flow graph. These illegal paths may be due either to permanent faults or to transient errors. The state code flow is compacted through polynomial division. An implicit justifying signature method is applied at the state code level and ensures identical signatures before each join node of the control flow graph. The signatures are then independent of the path followed previously in the graph and the comparison to reference data is greatly facilitated. This property is obtained by a clever state assignment, nearly without area overhead. The controllers can then be checked by signature analysis, either by a built-in monitor or by an external checker.
Optimize control of natural gas plants
Treiber, S.; Walker, J.; Tremblay, M. de ); Delgadillo, R.L.; Velasquez, R.N.; Valarde, M.J.G. )
1994-04-01
Multivariable constraint control (MCS) has a very beneficial and profitable impact on the operation of natural gas plants. The applications described operate completely within a distributed control system (DCS) or programmable logic controllers (PLCs). That makes MCS accessible to almost all gas plant operators. The technology's relative ease of use, low maintenance effort and software sensor,'' make it possible to operate these control applications without increasing technical support staff. MCS improves not only profitability but also regulatory compliance of gas plants. It has been applied to fractionation units, cryogenic units, amine treaters, sulfur recovery units and utilities. The application typically pay for the cost of software and engineering in less than one month. If a DCS is installed within such a project the advanced control applications can generate a payout in less than one year. In the case here (an application on the deethanizers of a 500 MMscfd gas plant) product revenue increased by over $2 million/yr.
Multi-Objective Optimization of Green EDM: An Integrated Theory
NASA Astrophysics Data System (ADS)
Jagadish; Ray, A.
2015-01-01
Electrical Discharge Machining (EDM) generates toxic substances, results in serious occupational health, and environmental issues, which influence the process parameters of EDM. These process parameters are multi-response parameters. The aim of this research is to solve the multi-response optimization problems and selection of optimum process parameters of green EDM using an integrated methodology comprising of entropy and Grey Relational Analysis (GRA). In this work, initially, an experiment was performed using Taguchi experimental technique. Thereafter, Entropy-GRA has been used to convert the multi-response parameters into single response parameter. Finally, the ranking of the parameter decides the best experimental set up and optimizes the input process parameters. In this work, Entropy method has been used to extract the precise value of each of the output parameters, which influences the gray relational grades for finding the optimal experimental set up. The justification of optimal input process parameters has been made using Analysis of Variance (ANOVA) analysis. An attempt has been made to compare the proposed methodology with the Fuzzy-TOPSIS and Taguchi-VIKOR methodology. The numerical result shows that the optimum process parameters are peak current (4.5 A), pulse duration (261 μs), dielectric level (80 mm) and flushing pressure (0.3 kg/cm2).
Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization
ERIC Educational Resources Information Center
Frankenhuis, Willem E.; Panchanathan, Karthik; Clark Barrett, H.
2013-01-01
Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic…
Optimized perturbation theory applied to jet cross sections in e + e - annihilation
NASA Astrophysics Data System (ADS)
Kramer, G.; Lampe, B.
1988-03-01
The optimized perturbation theory proposed by Stevenson to deal with coupling constant scheme dependence is applied to the calculation of π tot and jet multiplicities in e + e - annihilation. The results are compared with those of simple perturbation theory and with recent experimental cluster multiplicities.
Case Study: Optimality Theory and the Assessment and Treatment of Phonological Disorders.
ERIC Educational Resources Information Center
Barlow, Jessica A.
2001-01-01
A case study of a 3-year-old with a phonological disorder is used to demonstrate the application of optimality theory to the assessment and treatment. A tutorial of the theory is provided and then several prototypical error patterns evident in the child's productions are analyzed within the framework. (Contains references.) (Author/CR)
OPTIMIZATION OF INTEGRATED URBAN WET-WEATHER CONTROL STRATEGIES
An optimization method for urban wet weather control (WWC) strategies is presented. The developed optimization model can be used to determine the most cost-effective strategies for the combination of centralized storage-release systems and distributed on-site WWC alternatives. T...
Optimization of RMP Coils for ELM Control
NASA Astrophysics Data System (ADS)
Dutta, Someswar; Evans, T. E.; Orlov, D. M.
2015-11-01
Advanced DIII-D RMP coils with improved capabilities are studied using a vacuum island overlap width (VIOW) criterion. Changes in characteristics of the RMP field produced by different geometrical parameters using both ex-vessel (C- and O-) and in-vessel (I- and CP-) coils are discussed. By reducing the poloidal span of each coil, the spacing between them and varying the geometric angle between the coils and the plasma, the resonant field can be adjusted to optimize the edge VIOW criterion while minimizing core resonances. Three separate phase scans using a combination of the as built I-coils and proposed CP-coils are compared for three different equilibria. Two of these equilibria have different edge safety factors and the third one has a different gap between plasma and wall than the standard equilibrium scenario of DIII D. The scan results show that the VIOW correlation criterion is well satisfied in all three cases, resulting in a new way to optimize the RMP coils for the future reactors in order to achieve the ELM suppression criterion over a significantly wider range of fusion plasma operating scenarios. Work supported by the U.S. DOE under DE-FG02-05ER54809 and DE-FC02-04ER54698.
Shape Optimization for Trailing Edge Noise Control
NASA Astrophysics Data System (ADS)
Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz
2001-11-01
Noise generated by turbulent boundary layers near the trailing edge of lifting surfaces continues to pose a challenge for many applications. In this study, we explore noise reduction strategies through shape optimization. A gradient based shape design method is formulated and implemented for use with large eddy simulation of the flow over an airfoil. The cost function gradient is calculated using the method of incomplete sensitivities (Mohammadi and Pironneau 2001 ph Applied shape Optimization for Fluids, Oxford Univ. Press). This method has the advantage that effects of geometry changes on the flow field can be neglected when computing the gradient of the cost function, making it far more cost effective than solving the full adjoint problem. Validation studies are presented for a model problem of the unsteady laminar flow over an acoustically compact airfoil. A section of the surface is allowed to deform and the cost function is derived based on aeroacoustic theroy. Rapid convergence of the trailing-edge shape and significant reduction of the noise due to vortex shedding and wake instability have been achieved. The addition of constraints and issues of extension to fully turbulent flows past an acoustically noncompact airfoil are also discussed.
Information spread in networks: Games, optimal control, and stabilization
NASA Astrophysics Data System (ADS)
Khanafer, Ali
This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack
Dual structural-control optimization of large space structures
NASA Technical Reports Server (NTRS)
Messac, A.; Turner, J.
1984-01-01
A new approach is proposed for solving dual structural-control optimization problems for high-order flexible space structures where reduced-order structural models are employed. For a given initial structural dessign, a quadratic control cost is minimized subject to a constant-mass constraint. The sensitivity of the optimal control cost with respect to the stuctural design variables is then determined and used to obtain successive structural redesigns using a contrained gradient optimization algorithm. This process is repeated until the constrained control cost sensitivity becomes negligible. A numerical example is presented which demonstrates that this new approach effectively addresses the problem of dual optimization for potentially very high-order structures.
NASA Technical Reports Server (NTRS)
Boland, J. S., III
1973-01-01
The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.
Optimal feedback control of turbulent channel flow
NASA Technical Reports Server (NTRS)
Bewley, Thomas; Choi, Haecheon; Temam, Roger; Moin, Parviz
1993-01-01
Feedback control equations were developed and tested for computing wall normal control velocities to control turbulent flow in a channel with the objective of reducing drag. The technique used is the minimization of a 'cost functional' which is constructed to represent some balance of the drag integrated over the wall and the net control effort. A distribution of wall velocities is found which minimizes this cost functional some time shortly in the future based on current observations of the flow near the wall. Preliminary direct numerical simulations of the scheme applied to turbulent channel flow indicates it provides approximately 17 percent drag reduction. The mechanism apparent when the scheme is applied to a simplified flow situation is also discussed.
Formal optimization of hovering performance using free wake lifting surface theory
NASA Technical Reports Server (NTRS)
Chung, S. Y.
1986-01-01
Free wake techniques for performance prediction and optimization of hovering rotor are discussed. The influence functions due to vortex ring, vortex cylinder, and source or vortex sheets are presented. The vortex core sizes of rotor wake vortices are calculated and their importance is discussed. Lifting body theory for finite thickness body is developed for pressure calculation, and hence performance prediction of hovering rotors. Numerical optimization technique based on free wake lifting line theory is presented and discussed. It is demonstrated that formal optimization can be used with the implicit and nonlinear objective or cost function such as the performance of hovering rotors as used in this report.
Optimization of Airfoil Design for Flow Control with Plasma Actuators
NASA Astrophysics Data System (ADS)
Williams, Theodore; Corke, Thomas; Cooney, John
2011-11-01
Using computer simulations and design optimization methods, this research examines the implementation of active flow control devices on wind turbine blades. Through modifications to blade geometry in order to maximize the effectiveness of flow control devices, increases in aerodynamic performance and control of aerodynamic performance are expected. Due to this compliant flow, an increase in the power output of wind turbines is able to be realized with minimal modification and investment to existing turbine blades. This is achieved through dynamic lift control via virtual camber control. Methods using strategic flow separation near the trailing edge are analyzed to obtain desired aerodynamic performance. FLUENT is used to determine the aerodynamic performance of potential turbine blade design, and the post-processing uses optimization techniques to determine an optimal blade geometry and plasma actuator operating parameters. This work motivates the research and development of novel blade designs with flow control devices that will be tested at Notre Dame's Laboratory for Enhanced Wind Energy Design.
Cost-effectiveness analysis of optimal control measures for tuberculosis.
Rodrigues, Paula; Silva, Cristiana J; Torres, Delfim F M
2014-10-01
We propose and analyze an optimal control problem where the control system is a mathematical model for tuberculosis that considers reinfection. The control functions represent the fraction of early latent and persistent latent individuals that are treated. Our aim was to study how these control measures should be implemented, for a certain time period, in order to reduce the number of active infected individuals, while minimizing the interventions implementation costs. The optimal intervention is compared along different epidemiological scenarios, by varying the transmission coefficient. The impact of variation of the risk of reinfection, as a result of acquired immunity to a previous infection for treated individuals on the optimal controls and associated solutions, is analyzed. A cost-effectiveness analysis is done, to compare the application of each one of the control measures, separately or in combination. PMID:25245395
Fully efficient time-parallelized quantum optimal control algorithm
NASA Astrophysics Data System (ADS)
Riahi, M. K.; Salomon, J.; Glaser, S. J.; Sugny, D.
2016-04-01
We present a time-parallelization method that enables one to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation, and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of applications of this numerical scheme.
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn
2001-10-29
This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs.
Theory of the optimally coupled Q-switched laser
NASA Technical Reports Server (NTRS)
Degnan, John J.
1989-01-01
The general equations describing Q-switched laser operation are transcendental in nature and require numerical solutions, which greatly complicates the optimization of real devices. Here, it is shown that, using the mathematical technique of Lagrange multipliers, one can derive simple analytic expressions for all of the key parameters of the optimally coupled laser, i.e., one which uses an optimum reflector to obtain maximum laser efficiency for a given pump level. These parameters can all be expressed as functions of a single dimensionless variable z, defined as the ratio of the unsaturated small-signal gain to the dissipative (nonuseful) optical loss, multiplied by a few simple constants. Laser design tradeoff studies and performance projections can be accomplished quickly with the help of several graphs and a simple hand calculator. Sample calculations for a high-gain Nd:YAG and a low-gain alexandrite laser are presented as illustrations of the technique.
Malikopoulos, Andreas
2015-01-01
The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion. Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.
Malikopoulos, Andreas
2015-01-01
The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.more » Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.« less
Information fusion based optimal control for large civil aircraft system.
Zhen, Ziyang; Jiang, Ju; Wang, Xinhua; Gao, Chen
2015-03-01
Wind disturbance has a great influence on landing security of Large Civil Aircraft. Through simulation research and engineering experience, it can be found that PID control is not good enough to solve the problem of restraining the wind disturbance. This paper focuses on anti-wind attitude control for Large Civil Aircraft in landing phase. In order to improve the riding comfort and the flight security, an information fusion based optimal control strategy is presented to restrain the wind in landing phase for maintaining attitudes and airspeed. Data of Boeing707 is used to establish a nonlinear mode with total variables of Large Civil Aircraft, and then two linear models are obtained which are divided into longitudinal and lateral equations. Based on engineering experience, the longitudinal channel adopts PID control and C inner control to keep longitudinal attitude constant, and applies autothrottle system for keeping airspeed constant, while an information fusion based optimal regulator in the lateral control channel is designed to achieve lateral attitude holding. According to information fusion estimation, by fusing hard constraint information of system dynamic equations and the soft constraint information of performance index function, optimal estimation of the control sequence is derived. Based on this, an information fusion state regulator is deduced for discrete time linear system with disturbance. The simulation results of nonlinear model of aircraft indicate that the information fusion optimal control is better than traditional PID control, LQR control and LQR control with integral action, in anti-wind disturbance performance in the landing phase. PMID:25440950
Design of turbofan engine controls using output feedback regulator theory
NASA Technical Reports Server (NTRS)
Merrill, W. C.
1977-01-01
A multivariable control design procedure based on output feedback regulator (OFR) theory is applied to the F100 turbofan engine. Results for the OFR design are compared to a design based on linear quadratic regulator (LQR) theory. The OFR feedback control is designed in the full order state space and thus eliminates any need for model reduction techniques. Using the performance measure and control structure of the LQR design, an equivalent OFR feedback control is obtained. The flexibility of the OFR as a control design procedure is demonstrated, and differing feedback control structures are evaluated.
Shape Optimization for Aerodynamic Noise Control
NASA Astrophysics Data System (ADS)
Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz
2002-11-01
The objective of this work is to develop optimal shape design methods for reducing airfoil trailing-edge noise. Accurate evaluation of the cost function gradient via classical methods is expensive in unsteady turbulent flow simulations. We have evaluated the method of incomplete sensitivities (Mohammadi and Pironneau), which is inexpensive, and has been successful in previous applications. Gradients are approximated by neglecting changes in the flow field relative to geometrical contributions at each time step. Initial tests applied to a model problem seemed promising, however, in some cases the method was found to break down. A systematic evaluation of the incomplete sensitivities method as applied to the present problem has been carried out by comparison with the full gradient. The contribution to the gradient from changes in the flow field were found to be important. The underlying physical reasoning will be discussed and alternative methods including adjoint approaches and evolutionary algorithms will be explored.
A comparison of frequency domain design and l1-optimal control
NASA Technical Reports Server (NTRS)
Jayasuriya, Suhada; Sobhani, Massoud; Zentgraf, Peter
1991-01-01
A frequency-domain design methodology is applied to a DC motor-speed control system and the results are compared to those obtained using l1-optimal control theory (Pearson and Bamieh, 1990). Both methods synthesize controllers that maximize the allowable size of an unknown-but-bounded disturbance while satisfying prespecified constraints on the control, the control rate, and the outputs. The frequency-domain design technique in general results in much lower-order compensators than those required by the l1-optimal method for a given size of disturbance. Also, the design trade-offs regarding the bandwidth of the system, the size of the disturbance input, and the structural complexity of the controller transfer function become quite transparent.
Optimization of a fluidic temperature control device
NASA Technical Reports Server (NTRS)
Zabsky, J. M.; Rask, D. R.; Starr, J. B.
1970-01-01
Refinements are described to an existing fluidic temperature control system developed under a prior study which modulated temperature at the inlet to the liquid-cooled garment by using existing liquid supply and return lines to transmit signals to a fluidic controller located in the spacecraft. This earlier system produced a limited range of garment inlet temperatures, requiring some bypassing of flow around the suit to make the astronaut comfortable at rest conditions. Refinements were based on a flow visualization study of the key element in the fluidic controller: the fluidic mixing valve. The valve's mixing-ratio range was achieved by making five key changes: (1) geometrical changes to the valve; (2) attenuation of noise generated in proportional amplifier cascades; (3) elimination of vortices at the exit of the fluidic mixing valve; (4) reduction of internal heat transfer; and (5) flow balancing through venting. As a result, the refined system is capable of modulating garment inlet temperature from 45 F to 70 F with a single manual control valve in series with the garment. This control valve signals without changing or bypassing flow through the garment.
Proper Orthogonal Decomposition in Optimal Control of Fluids
NASA Technical Reports Server (NTRS)
Ravindran, S. S.
1999-01-01
In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.
Computerized optimal control system design for reusable and expendable boost vehicles.
NASA Technical Reports Server (NTRS)
Connor, C. L.; Trautwein, W.; Livingston, J. M.
1972-01-01
An optimization technique has been developed which combines the practical features of hybrid simulation of the dynamic system under study with the systematic approach of modern control theory where a mathematically formulated design criterion is optimized by functional minimization. Standard hybrid computer optimization methods using high-speed repetitive simulations and gradient minimization schemes have been extended to obtain time-varying optimal gain schedules and reduce the sensitivity of the optimized system to parameter and disturbance uncertainties. In this approach the performance index is expressed in meaningful engineering terms that reflect the interactions among all major disciplines, structures, control/actuation system design, aerodynamics and performance. The basic optimization technique is developed and its application to current aerospace control problems including the space shuttle is presented in detail. In the discussion of the application, the controllers resulting from the technique are compared with controllers developed by conventional methods. The paper concludes with a review of the advantages and disadvantages of the technique and plans for future applications.
Preconception optimization of glycaemic control in diabetes.
Islam, Najmul
2016-09-01
The prevalence of Diabetes Mellitus is increasing worldwide. In developing countries 25% of adult females with diabetes are in the reproductive age. Thus in developing countries increased number of pregnancies are complicated by diabetes. Uncontrolled diabetes in pregnancy is associated with increased risk for both mother and foetus. These risks can be minimized by good control of diabetes before and during pregnancy. Management in the preconception period is discussed in this review article. Detailed management involves general advice of lifestyle modification followed by specific details of screening for complications of diabetes. Changes in the drugs for both glycaemic control and other co-morbid conditions are discussed. The recommended insulin regimen in the preconception period and monitoring of glycaemic control by self-monitoring of blood glucose (SMBG) and HbA1C has also been highlighted. PMID:27582143
NASA Astrophysics Data System (ADS)
Tsuchiya, Takeshi; Ishii, Hirokazu; Uchida, Junichi; Gomi, Hiromi; Matayoshi, Naoki; Okuno, Yoshinori
This study aims to obtain the optimal flights of a helicopter that reduce ground noise during landing approach with an optimization technique, and to conduct flight tests for confirming the effectiveness of the optimal solutions. Past experiments of Japan Aerospace Exploration Agency (JAXA) show that the noise of a helicopter varies significantly according to its flight conditions, especially depending on the flight path angle. We therefore build a simple noise model for a helicopter, in which the level of the noise generated from a point sound source is a function only of the flight path angle. Using equations of motion for flight in a vertical plane, we define optimal control problems for minimizing noise levels measured at points on the ground surface, and obtain optimal controls for specified initial altitudes, flight constraints, and wind conditions. The obtained optimal flights avoid the flight path angle which generates large noise and decrease the flight time, which are different from conventional flight. Finally, we verify the validity of the optimal flight patterns through flight experiments. The actual flights following the optimal paths resulted in noise reduction, which shows the effectiveness of the optimization.
First line nurse managers: optimizing the span of control.
Alidina, S; Funke-Furber, J
1988-05-01
Span of control, the number of people reporting to a manager, is an important management concept. It determines the structure of an organization and has financial, human resource, and quality of care implications. In nursing, the first line manager fills one of the most critical roles in the administration of nursing services. For this manager to perform her responsibilities effectively, an optimal span of control is necessary. Span of control is influenced by a number of factors. By understanding these factors, we can influence them to optimize the span of control of the nurse manager. PMID:3367230
Mechanisms of Molecular Response in the Optimal Control of Photoisomerization
Dietzek, Benjamin; Brueggemann, Ben; Pascher, Torbjoern; Yartsev, Arkady
2006-12-22
We report on adaptive feedback control of photoinduced barrierless isomerization of 1,1'-diethyl-2,2'-cyanine in solution. We compare the effect of different fitness parameters and show that optimal control of the absolute yield of isomerization (photoisomer concentration versus excitation photons) can be achieved, while the relative isomerization yield (photoisomer concentration versus number of relaxed excited-state molecules) is unaffected by adaptive feedback control. The temporal structure of the optimized excitation pulses allows one to draw clear mechanistic conclusions showing the critical importance of coherent nuclear motion for the control of isomerization.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Hydro- abrasive jet machining modeling for computer control and optimization
NASA Astrophysics Data System (ADS)
Groppetti, R.; Jovane, F.
1993-06-01
Use of hydro-abrasive jet machining (HAJM) for machining a wide variety of materials—metals, poly-mers, ceramics, fiber-reinforced composites, metal-matrix composites, and bonded or hybridized mate-rials—primarily for two- and three-dimensional cutting and also for drilling, turning, milling, and deburring, has been reported. However, the potential of this innovative process has not been explored fully. This article discusses process control, integration, and optimization of HAJM to establish a plat-form for the implementation of real-time adaptive control constraint (ACC), adaptive control optimiza-tion (ACO), and CAD/CAM integration. It presents the approach followed and the main results obtained during the development, implementation, automation, and integration of a HAJM cell and its computer-ized controller. After a critical analysis of the process variables and models reported in the literature to identify process variables and to define a process model suitable for HAJM real-time control and optimi-zation, to correlate process variables and parameters with machining results, and to avoid expensive and time-consuming experiments for determination of the optimal machining conditions, a process predic-tion and optimization model was identified and implemented. Then, the configuration of the HAJM cell, architecture, and multiprogramming operation of the controller in terms of monitoring, control, process result prediction, and process condition optimization were analyzed. This prediction and optimization model for selection of optimal machining conditions using multi-objective programming was analyzed. Based on the definition of an economy function and a productivity function, with suitable constraints relevant to required machining quality, required kerfing depth, and available resources, the model was applied to test cases based on experimental results.
Propulsion control and control theory: A new research focus
NASA Technical Reports Server (NTRS)
Zeller, J. R.
1980-01-01
Technological developments necessary for the implementation of advanced digital control concepts for aircraft propulsion are identified and discussed. Developments associated with the replacement analog controllers with digital control systems, sensors and actuators, and control modes and software are reported.
NASA Astrophysics Data System (ADS)
Paasche, H.; Tronicke, J.
2012-04-01
In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto
Reproducibility, Controllability, and Optimization of Lenr Experiments
NASA Astrophysics Data System (ADS)
Nagel, David J.
2006-02-01
Low-energy nuclear reaction (LENR) measurements are significantly and increasingly reproducible. Practical control of the production of energy or materials by LENR has yet to be demonstrated. Minimization of costly inputs and maximization of desired outputs of LENR remain for future developments.
Linear stochastic optimal control and estimation
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1976-01-01
Digital program has been written to solve the LSOCE problem by using a time-domain formulation. LSOCE problem is defined as that of designing controls for linear time-invariant system which is disturbed by white noise in such a way as to minimize quadratic performance index.
Reengineering for optimized control of DC networks
NASA Astrophysics Data System (ADS)
Vintea, Adela; Schiopu, Paul
2015-02-01
The management of the Independent Power Grids is the global body/structure with flexible technological support for Command-Control-Communications and Informatized Management having the responsibility for providing the conditions and information (the informational flux of decision) for the decision-maker aiming at predictable and harmonic administration of the situations (crises) and for generating the harmonic situations (results).
OPTIMAL COST CONTROL STRATEGIES FOR ATTACHED ALGAE
This paper presents a cost-benefit analysis for alternative programs intended for the control of the nuisance growth of an attached alga (Cladophora). Such analyses require that changes in water quality be quantitatively related to the cost of implementation for specific manageme...
Microstructurally Controlled Composites with Optimal Elastodynamic Properties
NASA Astrophysics Data System (ADS)
Sadeghi, Hossein
Periodic composites (PCs) are artificial materials with specially designed microstructure to manage stress waves. The objective of this dissertation is to study various techniques for microstructural design of PCs for a desired elastodynamic response. A mixed variational formulation is studied for band structure calculation of PCs. Dynamic homogenization is studied for calculation of the frequency dependent effective properties of PCs. Optimization techniques are used together with mixed variational formulation and dynamic homogenization to make a computational platform for microstructural design of PCs. Several PCs are designed and fabricated, and various tests are performed for experimental verification. First, band-gap in one- and two-dimensional PCs is investigated experimentally. Mixed variational formulation is used to design samples with band-gaps at frequencies convenient to conduct experiment. Samples are fabricated and their transmission coefficient is measured. Experimental data are compared with theoretical results for evaluation of the band structure. Using constituent materials with temperature dependent material properties, it is also shown that band structure of PCs can be tuned by changing the ambient temperature. Furthermore, dynamic homogenization is used to design a one-dimensional PC for acoustic impedance matching. As a result, the reflection of stress waves at the interface of two impedance matched media becomes zero. Samples are fabricated and ultrasound tests are performed to measure the reflection coefficient for experimental verification. In addition, a one-dimensional PC with metamaterial response is designed to achieve a composite with both high stiffness-to-density ratio and high attenuation at low frequency regime. Samples are fabricated and the attenuation coefficient is measured for experimental verification. Moreover, optimal design of PCs for shock wave mitigation is investigated. A genetic algorithm is used to design the
NASA Astrophysics Data System (ADS)
Wei, Changzhu; Park, Sang-Young; Park, Chandeok
2014-09-01
A two degree-of-freedom signal-based optimal H∞ robust output feedback controller is designed for satellite formation in an arbitrary elliptical reference orbit. Based on high-fidelity linearized dynamics of relative motion, uncertainties introduced by non-zero eccentricity and gravitational J2 perturbation are separated to construct a robust control model. Furthermore, a distributed robust control model is derived by modifying the perturbed robust control model of each satellite with the eigenvalues of the Laplacian matrix of the communication graph, which represent uncertainty in the communication topology. A signal-based optimal H∞ robust controller is then designed primarily. Considering that the uncertainties involved in the distributed robust control model have a completely diagonal structure, the corresponding analyses are made through structured singular value theory to reduce the conservativeness. Based on simulation results, further designs including increasing the degrees of freedom of the controller, modifying the performance and control weighted functions, adding a post high-pass filter according to the dynamic characteristics, and reducing the control model are made to improve the control performance. Nonlinear simulations demonstrate that the resultant optimal H∞ robust output feedback controller satisfies the robust performance requirements under uncertainties caused by non-zero eccentricity, J2 perturbation, and varying communication topology, and that 5 m accuracy in terms of stable desired formation configuration can be achieved by the presented optimal H∞ robust controller. In addition to considering the widely discussed uncertainties caused by the orbit of each satellite in a formation, the optimal H∞ robust output feedback control model presented in the current work considers the uncertainties caused by varying communication topology in the satellite formation that works in a cooperative way. Other new improvements include adopting a
Kalman meets neuron: the emerging intersection of control theory with neuroscience.
Schiff, Steven J
2009-01-01
Since the 1950s, we have developed mature theories of modern control theory and computational neuroscience with almost no interaction between these disciplines. With the advent of computationally efficient nonlinear Kalman filtering techniques, along with improved neuroscience models that provide increasingly accurate reconstruction of dynamics in a variety of important normal and disease states in the brain, the prospects for a synergistic interaction between these fields are now strong. I show recent examples of the use of nonlinear control theory for the assimilation and control of single neuron dynamics, the modulation of oscillatory wave dynamics in brain cortex, a control framework for Parkinsonian dynamics and seizures, and the use of optimized parameter model networks to assimilate complex network data - the 'consensus set'. PMID:19964302
Kalman Meets Neuron: The Emerging Intersection of Control Theory with Neuroscience
Schiff, Steven J.
2013-01-01
Since the 1950s, we have developed mature theories of modern control theory and computational neuroscience with almost no interaction between these disciplines. With the advent of computationally efficient nonlinear Kalman filtering techniques, along with improved neuroscience models that provide increasingly accurate reconstruction of dynamics in a variety of important normal and disease states in the brain, the prospects for a synergistic interaction between these fields are now strong. I show recent examples of the use of nonlinear control theory for the assimilation and control of single neuron dynamics, the modulation of oscillatory wave dynamics in brain cortex, a control framework for Parkinsonian dynamics and seizures, and the use of optimized parameter model networks to assimilate complex network data – the ‘consensus set’. PMID:19964302
Integrated structure/control law design by multilevel optimization
NASA Technical Reports Server (NTRS)
Gilbert, Michael G.; Schmidt, David K.
1989-01-01
A new approach to integrated structure/control law design based on multilevel optimization is presented. This new approach is applicable to aircraft and spacecraft and allows for the independent design of the structure and control law. Integration of the designs is achieved through use of an upper level coordination problem formulation within the multilevel optimization framework. The method requires the use of structure and control law design sensitivity information. A general multilevel structure/control law design problem formulation is given, and the use of Linear Quadratic Gaussian (LQG) control law design and design sensitivity methods within the formulation is illustrated. Results of three simple integrated structure/control law design examples are presented. These results show the capability of structure and control law design tradeoffs to improve controlled system performance within the multilevel approach.
Total energy control system autopilot design with constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher
1990-01-01
A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.
Theory of optimal weighting of data to detect climatic change
NASA Technical Reports Server (NTRS)
Bell, T. L.
1986-01-01
A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.
Parametric optimal bounded feedback control for smart parameter-controllable composite structures
NASA Astrophysics Data System (ADS)
Ying, Z. G.; Ni, Y. Q.; Duan, Y. F.
2015-03-01
Deterministic and stochastic parametric optimal bounded control problems are presented for smart composite structures such as magneto-rheological visco-elastomer based sandwich beam with controllable bounded parameters subjected to initial disturbances and stochastic excitations. The parametric controls by actively adjusting system parameters differ from the conventional additive controls by systemic external inputs. The dynamical programming equations for the optimal parametric controls are derived based on the deterministic and stochastic dynamical programming principles. The optimal bounded functions of controls are firstly obtained from the equations with the bounded control constraints based on the bang-bang control strategy. Then the optimal bounded parametric control laws are obtained by the inversion of the nonlinear functions. The stability of the optimally controlled systems is proved according to the Lyapunov method. Finally, the proposed optimal bounded parametric feedback control strategy is applied to single-degree-of-freedom and two-degree-of-freedom dynamic systems with nonlinear parametric bounded control terms under initial disturbances and earthquake excitations and then to a magneto-rheological visco-elastomer based sandwich beam system with nonlinear parametric bounded control terms under stochastic excitations. The effective vibration suppression is illustrated with numerical results. The proposed optimal parametric control strategy is applicable to other smart composite structures with nonlinear controllable parameters.
Satellite tracking by combined optimal estimation and control techniques.
NASA Technical Reports Server (NTRS)
Dressler, R. M.; Tabak, D.
1971-01-01
Combined optimal estimation and control techniques are applied for the first time to satellite tracking systems. Both radio antenna and optical tracking systems of NASA are considered. The optimal estimation is accomplished using an extended Kalman filter resulting in an estimated state of the satellite and of the tracking system. This estimated state constitutes an input to the optimal controller. The optimal controller treats a linearized system with a quadratic performance index. The maximum principle is applied and a steady-state approximation to the resulting Riccati equation is obtained. A computer program, RATS, implementing this algorithm is described. A feasibility study of real-time implementation, tracking simulations, and parameter sensitivity studies are also reported.
Optimal charge control strategies for stationary photovoltaic battery systems
NASA Astrophysics Data System (ADS)
Li, Jiahao; Danzer, Michael A.
2014-07-01
Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.
Optimizing and controlling the operation of heat-exchanger networks
Aguilera, N.; Marchetti, J.L.
1998-05-01
A procedure was developed for on-line optimization and control systems of heat-exchanger networks, which features a two-level control structure, one for a constant configuration control system and the other for a supervisor on-line optimizer. The coordination between levels is achieved by adjusting the formulation of the optimization problem to meet requirements of the adopted control system. The general goal is always to work without losing stream temperature targets while keeping the highest energy integration. The operation constraints used for heat-exchanger and utility units emphasize the computation of heat-exchanger duties rather than intermediate stream temperatures. This simplifies the modeling task and provides clear links with the limits of the manipulated variables. The optimal condition is determined using LP or NLP, depending on the final problem formulation. Degrees of freedom for optimization and equation constraints for considering simple and multiple bypasses are rigorously discussed. An example used shows how the optimization problem can be adjusted to a specific network design, its expected operating space, and the control configuration. Dynamic simulations also show benefits and limitations of this procedure.
Random matrix theory and portfolio optimization in Moroccan stock exchange
NASA Astrophysics Data System (ADS)
El Alaoui, Marwane
2015-09-01
In this work, we use random matrix theory to analyze eigenvalues and see if there is a presence of pertinent information by using Marčenko-Pastur distribution. Thus, we study cross-correlation among stocks of Casablanca Stock Exchange. Moreover, we clean correlation matrix from noisy elements to see if the gap between predicted risk and realized risk would be reduced. We also analyze eigenvectors components distributions and their degree of deviations by computing the inverse participation ratio. This analysis is a way to understand the correlation structure among stocks of Casablanca Stock Exchange portfolio.
Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory
He, Dayi; Li, Ran; Huang, Qi; Lei, Ping
2014-01-01
In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods. PMID:25137239
OCTBEC—A Matlab toolbox for optimal quantum control of Bose-Einstein condensates
NASA Astrophysics Data System (ADS)
Hohenester, Ulrich
2014-01-01
OCTBEC is a Matlab toolbox designed for optimal quantum control, within the framework of optimal control theory (OCT), of Bose-Einstein condensates (BEC). The systems we have in mind are ultracold atoms in confined geometries, where the dynamics takes place in one or two spatial dimensions, and the confinement potential can be controlled by some external parameters. Typical experimental realizations are atom chips, where the currents running through the wires produce magnetic fields that allow to trap and manipulate nearby atoms. The toolbox provides a variety of Matlab classes for simulations based on the Gross-Pitaevskii equation, the multi-configurational Hartree method for bosons, and on generic few-mode models, as well as optimization problems. These classes can be easily combined, which has the advantage that one can adapt the simulation programs flexibly for various applications.
Optimizing wind turbine control system parameters
Schluter, L.L.; Vachon, W.A.
1993-08-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Optimizing wind turbine control system parameters
NASA Astrophysics Data System (ADS)
Schluter, Larry L.; Vachon, William A.
1993-05-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Lyapunov optimal feedback control of a nonlinear inverted pendulum
NASA Technical Reports Server (NTRS)
Grantham, W. J.; Anderson, M. J.
1989-01-01
Liapunov optimal feedback control is applied to a nonlinear inverted pendulum in which the control torque was constrained to be less than the nonlinear gravity torque in the model. This necessitates a control algorithm which 'rocks' the pendulum out of its potential wells, in order to stabilize it at a unique vertical position. Simulation results indicate that a preliminary Liapunov feedback controller can successfully overcome the nonlinearity and bring almost all trajectories to the target.
A task control theory of mirror-touch synesthesia.
Heyes, Cecilia; Catmur, Caroline
2015-01-01
Ward and Banissy's illuminating discussion of mirror-touch synesthesia (MTS) encourages research testing two alternatives to Threshold Theory: Their own Self-Other Theory, and "Task Control Theory". MTS may be due to abnormal mirror activity plus a domain-general, rather than a specifically social, impairment in the ability to privilege processing of task-relevant over task-irrelevant information. PMID:26114543
Utilizing Control Theory in Business Classrooms.
ERIC Educational Resources Information Center
Morrison, Pamela Porter
1988-01-01
In the formal school setting, the control of learning has typically been placed with the wrong person--the teacher. By modifying the control mechanism in the educational process and elevating the student to a position of "determining individual destiny," a catalyst for motivated learning may evolve. (JOW)
Theory of the optimally coupled Q-switched laser
Degnan, J.J.
1989-02-01
The general equations describing Q-switched laser operation are transcendental in nature and require numerical solutions. This greatly complicates the optimization of real devices. In this paper, we demonstrate that, using the mathematical technique of Lagrange multipliers, one can derive simple analytic expressions for all of the key parameters of the optimally coupled laser, i.e., one which uses an optimum reflector to obtain maximum laser efficiency for a given pump level. These parameters (which include the optimum reflectivity, output energy, extraction efficiency, pulsewidth, peak power, etc.) can all be expressed as functions of a single dimensionless variable z, defined as the ratio of the unsaturated small-signal gain to the dissipative (non-useful) optical loss, multiplied by a few simple constants. Laser design tradeoff studies and performance projections can be accomplished quickly with the help of several graphs and a simple hand calculator. Sample calculations for a high-gain Nd:YAG and a low-gain alexandrite laser are presented as illustrations of the technique.
Theory of optimal information transmission in E. coli chemotaxis pathway
NASA Astrophysics Data System (ADS)
Micali, Gabriele; Endres, Robert G.
Bacteria live in complex microenvironments where they need to make critical decisions fast and reliably. These decisions are inherently affected by noise at all levels of the signaling pathway, and cells are often modeled as an input-output device that transmits extracellular stimuli (input) to internal proteins (channel), which determine the final behavior (output). Increasing the amount of transmitted information between input and output allows cells to better infer extracellular stimuli and respond accordingly. However, in contrast to electronic devices, the separation into input, channel, and output is not always clear in biological systems. Output might feed back into the input, and the channel, made by proteins, normally interacts with the input. Furthermore, a biological channel is affected by mutations and can change under evolutionary pressure. Here, we present a novel approach to maximize information transmission: given cell-external and internal noise, we analytically identify both input distributions and input-output relations that optimally transmit information. Using E. coli chemotaxis as an example, we conclude that its pathway is compatible with an optimal information transmission device despite the ultrasensitive rotary motors.
Objective reduction in evolutionary multiobjective optimization: theory and applications.
Brockhoff, Dimo; Zitzler, Eckart
2009-01-01
Many-objective problems represent a major challenge in the field of evolutionary multiobjective optimization--in terms of search efficiency, computational cost, decision making, visualization, and so on. This leads to various research questions, in particular whether certain objectives can be omitted in order to overcome or at least diminish the difficulties that arise when many, that is, more than three, objective functions are involved. This study addresses this question from different perspectives. First, we investigate how adding or omitting objectives affects the problem characteristics and propose a general notion of conflict between objective sets as a theoretical foundation for objective reduction. Second, we present both exact and heuristic algorithms to systematically reduce the number of objectives, while preserving as much as possible of the dominance structure of the underlying optimization problem. Third, we demonstrate the usefulness of the proposed objective reduction method in the context of both decision making and search for a radar waveform application as well as for well-known test functions. PMID:19413486
Robust Optimal Adaptive Control Method with Large Adaptive Gain
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2009-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Optimally Controlled Flexible Fuel Powertrain System
Duncan Sheppard; Bruce Woodrow; Paul Kilmurray; Simon Thwaite
2011-06-30
A multi phase program was undertaken with the stated goal of using advanced design and development tools to create a unique combination of existing technologies to create a powertrain system specification that allowed minimal increase of volumetric fuel consumption when operating on E85 relative to gasoline. Although on an energy basis gasoline / ethanol blends typically return similar fuel economy to straight gasoline, because of its lower energy density (gasoline ~ 31.8MJ/l and ethanol ~ 21.1MJ/l) the volume based fuel economy of gasoline / ethanol blends are typically considerably worse. This project was able to define an initial engine specification envelope, develop specific hardware for the application, and test that hardware in both single and multi-cylinder test engines to verify the ability of the specified powertrain to deliver reduced E85 fuel consumption. Finally, the results from the engine testing were used in a vehicle drive cycle analysis tool to define a final vehicle level fuel economy result. During the course of the project, it was identified that the technologies utilized to improve fuel economy on E85 also enabled improved fuel economy when operating on gasoline. However, the E85 fueled powertrain provided improved vehicle performance when compared to the gasoline fueled powertrain due to the improved high load performance of the E85 fuel. Relative to the baseline comparator engine and considering current market fuels, the volumetric fuel consumption penalty when running on E85 with the fully optimized project powertrain specification was reduced significantly. This result shows that alternative fuels can be utilized in high percentages while maintaining or improving vehicle performance and with minimal or positive impact on total cost of ownership to the end consumer. The justification for this project was two-fold. In order to reduce the US dependence on crude oil, much of which is imported, the US Environmental Protection Agency (EPA
Solving Optimal Control Problems by Exploiting Inherent Dynamical Systems Structures
NASA Astrophysics Data System (ADS)
Flaßkamp, Kathrin; Ober-Blöbaum, Sina; Kobilarov, Marin
2012-08-01
Computing globally efficient solutions is a major challenge in optimal control of nonlinear dynamical systems. This work proposes a method combining local optimization and motion planning techniques based on exploiting inherent dynamical systems structures, such as symmetries and invariant manifolds. Prior to the optimal control, the dynamical system is analyzed for structural properties that can be used to compute pieces of trajectories that are stored in a motion planning library. In the context of mechanical systems, these motion planning candidates, termed primitives, are given by relative equilibria induced by symmetries and motions on stable or unstable manifolds of e.g. fixed points in the natural dynamics. The existence of controlled relative equilibria is studied through Lagrangian mechanics and symmetry reduction techniques. The proposed framework can be used to solve boundary value problems by performing a search in the space of sequences of motion primitives connected using optimized maneuvers. The optimal sequence can be used as an admissible initial guess for a post-optimization. The approach is illustrated by two numerical examples, the single and the double spherical pendula, which demonstrates its benefit compared to standard local optimization techniques.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
NASA Astrophysics Data System (ADS)
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
The Application of Layer Theory to Design: The Control Layer
ERIC Educational Resources Information Center
Gibbons, Andrew S.; Langton, Matthew B.
2016-01-01
A theory of design layers proposed by Gibbons ("An Architectural Approach to Instructional Design." Routledge, New York, 2014) asserts that each layer of an instructional design is related to a body of theory closely associated with the concerns of that particular layer. This study focuses on one layer, the control layer, examining…
Design of flight control systems via robust decoupled servomechanism theory
NASA Technical Reports Server (NTRS)
Wang, S.-H.; Davison, E. J.
1979-01-01
Decoupling theory and robust servomechanism theory are applied to the design of linear multivariable systems with large parameter variations. In addition to being approximately decoupled in the transient period, the over-all system achieves tracking and disturbance rejection robustly in the steady state. An example in flight control system is given.
Client-Controlled Case Information: A General System Theory Perspective
ERIC Educational Resources Information Center
Fitch, Dale
2004-01-01
The author proposes a model for client control of case information via the World Wide Web built on principles of general system theory. It incorporates the client into the design, resulting in an information structure that differs from traditional human services information-sharing practices. Referencing general system theory, the concepts of…
Relationships between digital signal processing and control and estimation theory
NASA Technical Reports Server (NTRS)
Willsky, A. S.
1978-01-01
Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.
Exploring quantum control landscapes: Topology, features, and optimization scaling
Moore, Katharine W.; Rabitz, Herschel
2011-07-15
Quantum optimal control experiments and simulations have successfully manipulated the dynamics of systems ranging from atoms to biomolecules. Surprisingly, these collective works indicate that the effort (i.e., the number of algorithmic iterations) required to find an optimal control field appears to be essentially invariant to the complexity of the system. The present work explores this matter in a series of systematic optimizations of the state-to-state transition probability on model quantum systems with the number of states N ranging from 5 through 100. The optimizations occur over a landscape defined by the transition probability as a function of the control field. Previous theoretical studies on the topology of quantum control landscapes established that they should be free of suboptimal traps under reasonable physical conditions. The simulations in this work include nearly 5000 individual optimization test cases, all of which confirm this prediction by fully achieving optimal population transfer of at least 99.9% on careful attention to numerical procedures to ensure that the controls are free of constraints. Collectively, the simulation results additionally show invariance of required search effort to system dimension N. This behavior is rationalized in terms of the structural features of the underlying control landscape. The very attractive observed scaling with system complexity may be understood by considering the distance traveled on the control landscape during a search and the magnitude of the control landscape slope. Exceptions to this favorable scaling behavior can arise when the initial control field fluence is too large or when the target final state recedes from the initial state as N increases.
Intermittent control: a computational theory of human control.
Gawthrop, Peter; Loram, Ian; Lakie, Martin; Gollee, Henrik
2011-02-01
The paradigm of continuous control using internal models has advanced understanding of human motor control. However, this paradigm ignores some aspects of human control, including intermittent feedback, serial ballistic control, triggered responses and refractory periods. It is shown that event-driven intermittent control provides a framework to explain the behaviour of the human operator under a wider range of conditions than continuous control. Continuous control is included as a special case, but sampling, system matched hold, an intermittent predictor and an event trigger allow serial open-loop trajectories using intermittent feedback. The implementation here may be described as "continuous observation, intermittent action". Beyond explaining unimodal regulation distributions in common with continuous control, these features naturally explain refractoriness and bimodal stabilisation distributions observed in double stimulus tracking experiments and quiet standing, respectively. Moreover, given that human control systems contain significant time delays, a biological-cybernetic rationale favours intermittent over continuous control: intermittent predictive control is computationally less demanding than continuous predictive control. A standard continuous-time predictive control model of the human operator is used as the underlying design method for an event-driven intermittent controller. It is shown that when event thresholds are small and sampling is regular, the intermittent controller can masquerade as the underlying continuous-time controller and thus, under these conditions, the continuous-time and intermittent controller cannot be distinguished. This explains why the intermittent control hypothesis is consistent with the continuous control hypothesis for certain experimental conditions. PMID:21327829
Polynomial method for PLL controller optimization.
Wang, Ta-Chung; Lall, Sanjay; Chiou, Tsung-Yu
2011-01-01
The Phase-Locked Loop (PLL) is a key component of modern electronic communication and control systems. PLL is designed to extract signals from transmission channels. It plays an important role in systems where it is required to estimate the phase of a received signal, such as carrier tracking from global positioning system satellites. In order to robustly provide centimeter-level accuracy, it is crucial for the PLL to estimate the instantaneous phase of an incoming signal which is usually buried in random noise or some type of interference. This paper presents an approach that utilizes the recent development in the semi-definite programming and sum-of-squares field. A Lyapunov function will be searched as the certificate of the pull-in range of the PLL system. Moreover, a polynomial design procedure is proposed to further refine the controller parameters for system response away from the equilibrium point. Several simulation results as well as an experiment result are provided to show the effectiveness of this approach. PMID:22163973
Optimization of structure-control systems with efficiency constraint
NASA Technical Reports Server (NTRS)
Oz, H.; Khot, N. S.
1990-01-01
The structure-control system optimization problem is formulated with constraints on the closed-loop eigenvalues and the efficiency of the reduced order system. The feasibility of the approach is illustrated by designing the ACOSS-FOUR structure with a reduced order system and improving the efficiency characteristics of the structures-control system.
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled, Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components ...
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components o...
Optimal Control of a Dengue Epidemic Model with Vaccination
NASA Astrophysics Data System (ADS)
Rodrigues, Helena Sofia; Teresa, M.; Monteiro, T.; Torres, Delfim F. M.
2011-09-01
We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.
Sensitivity Analysis and Optimal Control of Anthroponotic Cutaneous Leishmania
Zamir, Muhammad; Zaman, Gul; Alshomrani, Ali Saleh
2016-01-01
This paper is focused on the transmission dynamics and optimal control of Anthroponotic Cutaneous Leishmania. The threshold condition R0 for initial transmission of infection is obtained by next generation method. Biological sense of the threshold condition is investigated and discussed in detail. The sensitivity analysis of the reproduction number is presented and the most sensitive parameters are high lighted. On the basis of sensitivity analysis, some control strategies are introduced in the model. These strategies positively reduce the effect of the parameters with high sensitivity indices, on the initial transmission. Finally, an optimal control strategy is presented by taking into account the cost associated with control strategies. It is also shown that an optimal control exists for the proposed control problem. The goal of optimal control problem is to minimize, the cost associated with control strategies and the chances of infectious humans, exposed humans and vector population to become infected. Numerical simulations are carried out with the help of Runge-Kutta fourth order procedure. PMID:27505634
Optimal control of precision paraboloidal shell structronic systems
NASA Astrophysics Data System (ADS)
Tzou, H. S.; Ding, J. H.
2004-09-01
Paraboloidal shells of revolution are commonly used in advanced aerospace, civil and telecommunication structures, e.g., antennas, reflectors, mirrors, rocket fairings, nozzles, solar collectors, dome structures, etc. A structronic shell system is defined as an elastic shell embedded, bonded or laminated with distributed piezoelectric sensors and actuators and it is governed by either in situ or external control electronics. A closed-loop control system of paraboloidal shell structronic system consists of distributed sensors/actuators and controller coupled with an elastic paraboloidal shell. State equation for the paraboloidal shell structronic system is derived and optimal linear quadratic state feedback control is implemented, such that the "best" shell control performance with the least control cost can be achieved. The gain matrix is estimated based on minimizing a performance criterion function. Optimal control effects are compared with controlled responses with other non-optimal control parameters. Control effects of identical-sized sensor/actuator patches at different locations are studied and compared. Modal control effects for different natural modes are also investigated.
Solving the optimal attention allocation problem in manual control
NASA Technical Reports Server (NTRS)
Kleinman, D. L.
1976-01-01
Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.
State-Constrained Optimal Control Problems of Impulsive Differential Equations
Forcadel, Nicolas; Rao Zhiping Zidani, Hasnaa
2013-08-01
The present paper studies an optimal control problem governed by measure driven differential systems and in presence of state constraints. The first result shows that using the graph completion of the measure, the optimal solutions can be obtained by solving a reparametrized control problem of absolutely continuous trajectories but with time-dependent state-constraints. The second result shows that it is possible to characterize the epigraph of the reparametrized value function by a Hamilton-Jacobi equation without assuming any controllability assumption.
Optimization of an Aeroservoelastic Wing with Distributed Multiple Control Surfaces
NASA Technical Reports Server (NTRS)
Stanford, Bret K.
2015-01-01
This paper considers the aeroelastic optimization of a subsonic transport wingbox under a variety of static and dynamic aeroelastic constraints. Three types of design variables are utilized: structural variables (skin thickness, stiffener details), the quasi-steady deflection scheduling of a series of control surfaces distributed along the trailing edge for maneuver load alleviation and trim attainment, and the design details of an LQR controller, which commands oscillatory hinge moments into those same control surfaces. Optimization problems are solved where a closed loop flutter constraint is forced to satisfy the required flight margin, and mass reduction benefits are realized by relaxing the open loop flutter requirements.
Theory based design and optimization of materials for spintronics applications
NASA Astrophysics Data System (ADS)
Xu, Tianyi
The Spintronics industry has developed rapidly in the past decade. Finding the right material is very important for Spintronics applications, which requires good understanding of the physics behind specific phenomena. In this dissertation, we will focus on two types of perpendicular transport phenomena, the current-perpendicular-to-plane giant-magneto-resistance (CPP-GMR) phenomenon and the tunneling phenomenon in the magnetic tunnel junctions. The Valet-Fert model is a very useful semi-classical approach for understanding the transport and spin-flip process in CPP-GMR. We will present a finite element based implementation for the Valet-Fert model which enables a practical way to calculate the electron transport in real CPP-GMR spin valves. It is very important to find high spin polarized materials for CPP-GMR spin valves. The half-metal, due to its full spin polarization, is of interest. We will propose a rational way to find half-metals based on the gap theorem. Then we will focus on the high-MR TMR phenomenon. The tunneling theory of electron transport in mesoscopic systems will be covered. Then we will calculate the transport properties of certain junctions with the help of Green's function under the Landauer-Buttiker formalism, also known as the scattering formalism. The damping constant determines the switching rate of a device. We can calculate it using a method based on the Extended Huckel Tight-Binding theory (EHTB). The symmetry filtering effect is very helpful for finding materials for TMR junctions. Based upon which, we find a good candidate material, MnAl, for TMR applications.
Optimization of robustness of network controllability against malicious attacks
NASA Astrophysics Data System (ADS)
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-11-01
As the controllability of complex networks has attracted much attention recently, how to design and optimize the robustness of network controllability has become a common and urgent problem in the engineering field. In this work, we propose a method that modifies any given network with strict structural perturbation to effectively enhance its robustness against malicious attacks, called dynamic optimization of controllability. Unlike other structural perturbations, the strict perturbation only swaps the links and keeps the in- and out-degree unchanged. A series of extensive experiments show that the robustness of controllability and connectivity can be improved dramatically. Furthermore, the effectiveness of our method is explained from the views of underlying structure. The analysis results indicate that the optimization algorithm makes networks more homogenous and assortative.
Optimal wavefront control for adaptive segmented mirrors
NASA Technical Reports Server (NTRS)
Downie, John D.; Goodman, Joseph W.
1989-01-01
A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.
ERIC Educational Resources Information Center
Cook, Desmond L.
This document, one of a series of reports examining the possible contribution of other disciplines to evaluation methodology, describes the major elements of general systems theory (GST), cybernetics theory (CT) and management control theory (MCT). The author suggests that MCT encapsulates major concerns of evaluation since it reveals that…
Optimal control of information epidemics modeled as Maki Thompson rumors
NASA Astrophysics Data System (ADS)
Kandhway, Kundan; Kuri, Joy
2014-12-01
We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.
Optimal Control of Transitions between Nonequilibrium Steady States
Zulkowski, Patrick R.; Sivak, David A.; DeWeese, Michael R.
2013-01-01
Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines. PMID:24386112
Application of stability theory to laminar flow control
NASA Technical Reports Server (NTRS)
Hefner, J. N.; Bushnell, D. M.
1979-01-01
The paper summarizes the state-of-the-art for application of stability theory to laminar flow control using suction, wall temperature and/or favorable pressure gradient ('natural laminar flow'). Discussions include current LFC problem areas requiring stability analyses, methods of relating stability theory to transition with results from data and theory comparisons available thus far, and a summary of low disturbance data available for theory calibration on swept wings. Critical issues highlighted are problems peculiar to suction LFC on high performance transonic wings and application of the e-to-the-n-power method to both low and high speed flight data.
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
Optimizing Optics For Remotely Controlled Underwater Vehicles
NASA Astrophysics Data System (ADS)
Billet, A. B.
1984-09-01
The past decade has shown a dramatic increase in the use of unmanned tethered vehicles in worldwide marine fields. These vehicles are used for inspection, debris removal and object retrieval. With advanced robotic technology, remotely operated vehicles (ROVs) are now able to perform a variety of jobs previously accomplished only by divers. The ROVs can be used at greater depths and for riskier jobs, and safety to the diver is increased, freeing him for safer, more cost-effective tasks requiring human capabilities. Secondly, the ROV operation becomes more cost effective to use as work depth increases. At 1000 feet a diver's 10 minutes of work can cost over $100,000 including support personnel, while an ROV operational cost might be 1/20 of the diver cost per day, based on the condition that the cost for ROV operation does not change with depth, as it does for divers. In the ROV operation the television lens must be as good as the human eye, with better light gathering capability than the human eye. The RCV-150 system is an example of these advanced technology vehicles. With the requirements of manueuverability and unusual inspection, a responsive, high performance, compact vehicle was developed. The RCV-150 viewing subsystem consists of a television camera, lights, and topside monitors. The vehicle uses a low light level Newvicon television camera. The camera is equipped with a power-down iris that closes for burn protection when the power is off. The camera can pan f 50 degrees and tilt f 85 degrees on command from the surface. Four independently controlled 250 watt quartz halogen flood lamps illuminate the viewing area as required; in addition, two 250 watt spotlights are fitted. A controlled nine inch CRT monitor provides real time camera pictures for the operator. The RCV-150 vehicle component system consists of the vehicle structure, the vehicle electronics, and hydraulic system which powers the thruster assemblies and the manipulator. For this vehicle, a light
Exploring the complexity of quantum control optimization trajectories.
Nanduri, Arun; Shir, Ofer M; Donovan, Ashley; Ho, Tak-San; Rabitz, Herschel
2015-01-01
The control of quantum system dynamics is generally performed by seeking a suitable applied field. The physical objective as a functional of the field forms the quantum control landscape, whose topology, under certain conditions, has been shown to contain no critical point suboptimal traps, thereby enabling effective searches for fields that give the global maximum of the objective. This paper addresses the structure of the landscape as a complement to topological critical point features. Recent work showed that landscape structure is highly favorable for optimization of state-to-state transition probabilities, in that gradient-based control trajectories to the global maximum value are nearly straight paths. The landscape structure is codified in the metric R ≥ 1.0, defined as the ratio of the length of the control trajectory to the Euclidean distance between the initial and optimal controls. A value of R = 1 would indicate an exactly straight trajectory to the optimal observable value. This paper extends the state-to-state transition probability results to the quantum ensemble and unitary transformation control landscapes. Again, nearly straight trajectories predominate, and we demonstrate that R can take values approaching 1.0 with high precision. However, the interplay of optimization trajectories with critical saddle submanifolds is found to influence landscape structure. A fundamental relationship necessary for perfectly straight gradient-based control trajectories is derived, wherein the gradient on the quantum control landscape must be an eigenfunction of the Hessian. This relation is an indicator of landscape structure and may provide a means to identify physical conditions when control trajectories can achieve perfect linearity. The collective favorable landscape topology and structure provide a foundation to understand why optimal quantum control can be readily achieved. PMID:25377547
Strong stabilization servo controller with optimization of performance criteria.
Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor
2011-07-01
Synthesis of a simple robust controller with a pole placement technique and a H(∞) metrics is the method used for control of a servo mechanism with BLDC and BDC electric motors. The method includes solving a polynomial equation on the basis of the chosen characteristic polynomial using the Manabe standard polynomial form and parametric solutions. Parametric solutions are introduced directly into the structure of the servo controller. On the basis of the chosen parametric solutions the robustness of a closed-loop system is assessed through uncertainty models and assessment of the norm ‖•‖(∞). The design procedure and the optimization are performed with a genetic algorithm differential evolution - DE. The DE optimization method determines a suboptimal solution throughout the optimization on the basis of a spectrally square polynomial and Šiljak's absolute stability test. The stability of the designed controller during the optimization is being checked with Lipatov's stability condition. Both utilized approaches: Šiljak's test and Lipatov's condition, check the robustness and stability characteristics on the basis of the polynomial's coefficients, and are very convenient for automated design of closed-loop control and for application in optimization algorithms such as DE. PMID:21501837
Optimized Reactive Power Compensation Using Fuzzy Logic Controller
NASA Astrophysics Data System (ADS)
George, S.; Mini, K. N.; Supriya, K.
2015-03-01
Reactive power flow in a long transmission line plays a vital role in power transfer capability and voltage stability in power system. Traditionally, shunt connected compensators are used to control reactive power in long transmission line. Thyristor controlled reactor is used to control reactive power under lightly loaded condition. By controlling firing angle of thyristor, it is possible to control reactive power in the transmission lines. However, thyristor controlled reactor will inject harmonic current into the system. An attempt to reduce reactive power injection will increase harmonic distortion in the line current and vice versa. Thus, there is a trade-off between reactive power injection and harmonics in current. By optimally controlling the reactive power injection, harmonics in current can be brought within the specified limit. In this paper, a Fuzzy Logic Controller is implemented to obtain optimal control of reactive power of the compensator to maintain voltage and harmonic in current within the limits. An algorithm which optimizes the firing angle in each fuzzy subset by calculating the rank of feasible firing angles is proposed for the construction of rules in Fuzzy Logic Controller. The novelty of the algorithm is that it uses a simple error formula for the calculation of the rank of the feasible firing angles in each fuzzy subset.
Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory
NASA Astrophysics Data System (ADS)
Matsumura, Koki; Kawamoto, Masaru
This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Optimal periodic control for spacecraft pointing and attitude determination
NASA Technical Reports Server (NTRS)
Pittelkau, Mark E.
1993-01-01
A new approach to autonomous magnetic roll/yaw control of polar-orbiting, nadir-pointing momentum bias spacecraft is considered as the baseline attitude control system for the next Tiros series. It is shown that the roll/yaw dynamics with magnetic control are periodically time varying. An optimal periodic control law is then developed. The control design features a state estimator that estimates attitude, attitude rate, and environmental torque disturbances from Earth sensor and sun sensor measurements; no gyros are needed. The state estimator doubles as a dynamic attitude determination and prediction function. In addition to improved performance, the optimal controller allows a much smaller momentum bias than would otherwise be necessary. Simulation results are given.
Optimal Variable-Structure Control Tracking of Spacecraft Maneuvers
NASA Technical Reports Server (NTRS)
Crassidis, John L.; Vadali, Srinivas R.; Markley, F. Landis
1999-01-01
An optimal control approach using variable-structure (sliding-mode) tracking for large angle spacecraft maneuvers is presented. The approach expands upon a previously derived regulation result using a quaternion parameterization for the kinematic equations of motion. This parameterization is used since it is free of singularities. The main contribution of this paper is the utilization of a simple term in the control law that produces a maneuver to the reference attitude trajectory in the shortest distance. Also, a multiplicative error quaternion between the desired and actual attitude is used to derive the control law. Sliding-mode switching surfaces are derived using an optimal-control analysis. Control laws are given using either external torque commands or reaction wheel commands. Global asymptotic stability is shown for both cases using a Lyapunov analysis. Simulation results are shown which use the new control strategy to stabilize the motion of the Microwave Anisotropy Probe spacecraft.
Optimal startup control of a jacketed tubular reactor.
NASA Technical Reports Server (NTRS)
Hahn, D. R.; Fan, L. T.; Hwang, C. L.
1971-01-01
The optimal startup policy of a jacketed tubular reactor, in which a first-order, reversible, exothermic reaction takes place, is presented. A distributed maximum principle is presented for determining weak necessary conditions for optimality of a diffusional distributed parameter system. A numerical technique is developed for practical implementation of the distributed maximum principle. This involves the sequential solution of the state and adjoint equations, in conjunction with a functional gradient technique for iteratively improving the control function.
Solving bi-objective optimal control problems with rectangular framing
NASA Astrophysics Data System (ADS)
Wijaya, Karunia Putra; Götz, Thomas
2016-06-01
Optimization problems, e.g. arising from epidemiology models, often ask for solutions minimizing multi-criteria objective functions. In this paper we discuss a novel approach for solving bi-objective optimal control problems. The set of non-dominated points is constructed via a decreasing sequence of rectangles. Particular attention is paid to a problem with disconnected set of non-dominated points. Several examples from epidemiology are investigated and show the applicability of the method.
NASA Astrophysics Data System (ADS)
Kapur, P. K.; Pham, Hoang; Chanda, Udayan; Kumar, Vijay
2013-09-01
Allocation of efforts to a software development project during the testing phase is a multifaceted task for software managers. The challenges become stiffer when the nature of the development process is considered in the dynamic environment. Many software reliability growth models have been proposed in last decade to minimise the total testing-effort expenditures, but mostly under static assumption. The main purpose of this article is to investigate an optimal resource allocation plan to minimise the cost of software during the testing and operational phase under dynamic condition. An elaborate optimisation policy based on the optimal control theory is proposed and numerical examples are illustrated. This article also studies the optimal resource allocation problems for various conditions by examining the behaviour of the model parameters and also suggests policy for the optimal release time of the software. The experimental results greatly help us to identify the contribution of each selected parameter and its weight.
Optimal control, investment and utilization schemes for energy storage under uncertainty
NASA Astrophysics Data System (ADS)
Mirhosseini, Niloufar Sadat
Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency
Motor control theories and their applications.
Latash, Mark L; Levin, Mindy F; Scholz, John P; Schöner, Gregor
2010-01-01
We describe several influential hypotheses in the field of motor control including the equilibrium-point (referent configuration) hypothesis, the uncontrolled manifold hypothesis, and the idea of synergies based on the principle of motor abundance. The equilibrium-point hypothesis is based on the idea of control with thresholds for activation of neuronal pools; it provides a framework for analysis of both voluntary and involuntary movements. In particular, control of a single muscle can be adequately described with changes in the threshold of motor unit recruitment during slow muscle stretch (threshold of the tonic stretch reflex). Unlike the ideas of internal models, the equilibrium-point hypothesis does not assume neural computations of mechanical variables. The uncontrolled manifold hypothesis is based on the dynamic system approach to movements; it offers a toolbox to analyze synergic changes within redundant sets of elements related to stabilization of potentially important performance variables. The referent configuration hypothesis and the principle of abundance can be naturally combined into a single coherent scheme of control of multi-element systems. A body of experimental data on healthy persons and patients with movement disorders are reviewed in support of the mentioned hypotheses. In particular, movement disorders associated with spasticity are considered as consequences of an impaired ability to shift threshold of the tonic stretch reflex within the whole normal range. Technical details and applications of the mentioned hypo-theses to studies of motor learning are described. We view the mentioned hypotheses as the most promising ones in the field of motor control, based on a solid physical and neurophysiological foundation. PMID:20944446
Optimized feedback control system modeling of resistive wall modes for burning plasmas experiments
NASA Astrophysics Data System (ADS)
Katsuro-Hopkins, Oksana Nikolaevna
A numerical study of active feedback control system performance and optimization for tokamak Resistive Wall Modes (RWM) is the subject of this thesis. The ability to accurately model and predict the performance of an active MHD control systems is critical to present and future advanced confinement scenarios and fusion reactor design studies. The computer code VALEN has been designed to calculate the performance of a MHD feedback control system in an arbitrary geometry. The simulation of realistic effects in feedback systems, such as noise, time delays and filters is of particular importance. In this work realistic measurement noise analysis was added to VALEN and used to design the RWM feedback control amplifier power level for the DIII-D experiment. Modern control theory based on a state-space formulation obtained from VALEN was applied to design an Optimal Controller and Observer based on a reduced VALEN model. A quantitative low order model of the VALEN state space was derived from the high dimensional intrinsic state space structure of the VALEN using methods of a balanced realization and matched DC gain truncation. These techniques for the design of an optimal controller and optimal observer were applied to models of the DIII-D and ITER experiments and showed an order of magnitude reduction of the required control coil current and voltage in the presence of white noise as compared to a traditional, classical PID controller. This optimal controller for the ITER burning plasma experiment was robust from the no-wall pressure limit to a pressure value well above those achieved with a classical PID controller and could approach the ideal wall limit.
Optimal control of switched linear systems based on Migrant Particle Swarm Optimization algorithm
NASA Astrophysics Data System (ADS)
Xie, Fuqiang; Wang, Yongji; Zheng, Zongzhun; Li, Chuanfeng
2009-10-01
The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a major obstacle. In this paper we describe a new approach for solving this problem, which is called Migrant Particle Swarm Optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO applies naturally to both continuous and discrete spaces, in which definitive optimization algorithm and stochastic search method are combined. The efficacy of the proposed algorithm is illustrated via a numerical example.
Optimal control of large space structures via generalized inverse matrix
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Fang, Xiaowen
1987-01-01
Independent Modal Space Control (IMSC) is a control scheme that decouples the space structure into n independent second-order subsystems according to n controlled modes and controls each mode independently. It is well-known that the IMSC eliminates control and observation spillover caused when the conventional coupled modal control scheme is employed. The independent control of each mode requires that the number of actuators be equal to the number of modelled modes, which is very high for a faithful modeling of large space structures. A control scheme is proposed that allows one to use a reduced number of actuators to control all modeled modes suboptimally. In particular, the method of generalized inverse matrices is employed to implement the actuators such that the eigenvalues of the closed-loop system are as closed as possible to those specified by the optimal IMSC. Computer simulation of the proposed control scheme on a simply supported beam is given.
An optimal performance control scheme for a 3D crane
NASA Astrophysics Data System (ADS)
Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.
2016-01-01
This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.
Advanced launch system trajectory optimization using suboptimal control
NASA Technical Reports Server (NTRS)
Shaver, Douglas A.; Hull, David G.
1993-01-01
The maximum-final mass trajectory of a proposed configuration of the Advanced Launch System is presented. A model for the two-stage rocket is given; the optimal control problem is formulated as a parameter optimization problem; and the optimal trajectory is computed using a nonlinear programming code called VF02AD. Numerical results are presented for the controls (angle of attack and velocity roll angle) and the states. After the initial rotation, the angle of attack goes to a positive value to keep the trajectory as high as possible, returns to near zero to pass through the transonic regime and satisfy the dynamic pressure constraint, returns to a positive value to keep the trajectory high and to take advantage of minimum drag at positive angle of attack due to aerodynamic shading of the booster, and then rolls off to negative values to satisfy the constraints. Because the engines cannot be throttled, the maximum dynamic pressure occurs at a single point; there is no maximum dynamic pressure subarc. To test approximations for obtaining analytical solutions for guidance, two additional optimal trajectories are computed: one using untrimmed aerodynamics and one using no atmospheric effects except for the dynamic pressure constraint. It is concluded that untrimmed aerodynamics has a negligible effect on the optimal trajectory and that approximate optimal controls should be able to be obtained by treating atmospheric effects as perturbations.
A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour
NASA Technical Reports Server (NTRS)
Leyland, Jane Anne
1996-01-01
Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.
Demonstration of open-quantum-system optimal control in dynamic nuclear polarization
NASA Astrophysics Data System (ADS)
Sheldon, S.; Cory, D. G.
2015-10-01
Dynamic nuclear polarization (DNP) is used in nuclear magnetic resonance to transfer polarization from electron spins to nuclear spins. The resulting nuclear polarization enhancement can, in theory, be two or three orders of magnitude depending on the sample. In solid-state systems, however, there are competing mechanisms of DNP, which, when occurring simultaneously, reduce the net polarization enhancement of the nuclear spin. We present a simple quantum description of DNP and apply optimal control theory (OCT) with an open-quantum-system framework to design pulses that select one DNP process and suppress the others. We demonstrate experimentally an order of magnitude improvement in the DNP enhancement using OCT pulses.
Design of turbofan engine controls using output feedback regulator theory
NASA Technical Reports Server (NTRS)
Merrill, W. C.
1977-01-01
A multivariable control design procedure based on output feedback regulator (OFR) theory is applied to the F100 turbofan engine. Results for the OFR design are compared to a design based on linear quadratic regulator (LQR) theory. This LQR design was obtained as part of the F100 Multivariable Control Synthesis (MVCS) program. In the MVCS program the LQR feedback control was designed in a reduced dimension state space and then applied to the original system. However, the OFR feedback control is designed in the full order state space and thus eliminates any need for model reduction techniques. Using the performance measure and control structure of the MVCS program LQR design, an equivalent OFR feedback control is obtained. The flexibility of the OFR as a control design procedure is demonstrated and differing feedback control structures are evaluated.
Towards sub-optimal stochastic control of partially observable stochastic systems
NASA Technical Reports Server (NTRS)
Ruzicka, G. J.
1980-01-01
A class of multidimensional stochastic control problems with noisy data and bounded controls encountered in aerospace design is examined. The emphasis is on suboptimal design, the optimality being taken in quadratic mean sense. To that effect the problem is viewed as a stochastic version of the Lurie problem known from nonlinear control theory. The main result is a separation theorem (involving a nonlinear Kalman-like filter) suitable for Lurie-type approximations. The theorem allows for discontinuous characteristics. As a byproduct the existence of strong solutions to a class of non-Lipschitzian stochastic differential equations in dimensions is proven.
Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
NASA Astrophysics Data System (ADS)
Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel
2014-12-01
Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers.
Optimal control for the active above-knee prosthesis.
Popović, D; Oğuztöreli, M N; Stein, R B
1991-01-01
Control of an active above-knee prosthesis has been simulated for a selected gait activity using a hierarchical closed-loop method. An extension of finite-state control, referred to as artificial reflex control, was adopted at the strategic level of control. At the actuator level of control an optimal tracking method, based on dynamic programming, is applied. This deals mainly with the actuator level of control, but considers the interaction of the leg dynamics and the switching effects of artificial reflex control. Optimal tracking at the actuator level of the above-knee prosthesis reduces the on-off effects of finite-state methods, such as artificial reflex control. The proposed method can also be used for the design of prosthetic elements. Specific attention is paid to the limited torque and power in the prosthetic joint actuator, which are imposed by the principle of self-containment in the artificial leg. The hierarchical structure, integrating artificial reflex control and optimal tracking, can be used in real time, as estimated from the number of computer operations required for the suggested method. PMID:2048773
Optimization of temporal dose modulation: Comparison of theory and experiment
Bewes, J. M.; Suchowerska, N.; Cartwright, L.; Ebert, M. A.; McKenzie, D. R.
2012-06-15
Purpose: To compare theoretical predictions and experimental measurements of cell survival after exposure to two different temporally modulated radiation dose patterns that deliver the same dose in the same overall time. Methods: The authors derived an analytic expression for the dose protraction factor G in the Lea-Catcheside formalism for cell survival for 'triangle' and 'V' temporal modulation of dose. These temporal dose patterns were used in experimental clonogenic studies of a melanoma cell line (MM576) and a nonsmall-cell lung cancer line (NCI-H460) that have different alpha, beta, and repair parameters. The overall treatment time and total dose were kept constant. Results: The analytic expressions for G for the two temporal modulations are presented as a function of a single variable, the product of the exposure time, and the repair constant, enabling G to be evaluated for any exposure time and for any cell line. G for the triangle delivery pattern is always the larger. For the MM576 cell line, following a large dose of 6 Gy, a larger survival fraction was found for the V delivery pattern. No difference in survival was observed for lower doses or for the NCI-H460 cell line at any dose. These results are predicted by our theory, using published values of alpha, beta, and repair time within the limits of experimental uncertainty. Conclusions: The study provides evidence to confirm that cell lines having large beta values exhibit a response that is sensitive to the pattern of dose delivery when the delivery time is comparable with the repair time. It is recommended that the dose delivery pattern be considered in hypofractionated treatments.
Application of the Theory of Functional Monte Carlo Algorithms to Optimization of the DSMC Method
NASA Astrophysics Data System (ADS)
Plotnikov, M. Yu.; Shkarupa, E. V.
2008-12-01
Some approaches to error analysis and optimization of the Direct Simulation Monte Carlo method are presented. The main idea of this work is the construction of the relations between the sample size and the number of cells which guarantee the attainment of the given error level on the base of the theory of functional Monte Carlo algorithms. The optimal (in the sense of the obtained upper error bound) values of the sample size and the number of cells are constructed.
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less
The application of quadratic optimal cooperative control synthesis to a CH-47 helicopter
NASA Technical Reports Server (NTRS)
Townsend, Barbara K.
1987-01-01
A control-system design method, quadratic optimal cooperative control synthesis (CCS), is applied to the design of a stability and control augmentation system (SCAS). The CCS design method is different from other design methods in that it does not require detailed a priori design criteria, but instead relies on an explicit optimal pilot-model to create desired performance. The design method, which was developed previously for fixed-wing aircraft, is simplified and modified for application to a Boeing CH-47 helicopter. Two SCAS designs are developed using the CCS design methodology. The resulting CCS designs are then compared with designs obtained using classical/frequency-domain methods and linear quadratic regulator (LQR) theory in a piloted fixed-base simulation. Results indicate that the CCS method, with slight modifications, can be used to produce controller designs which compare favorably with the frequency-domain approach.
Multidisciplinary optimization of controlled space structures with global sensitivity equations
NASA Technical Reports Server (NTRS)
Padula, Sharon L.; James, Benjamin B.; Graves, Philip C.; Woodard, Stanley E.
1991-01-01
A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.
A stochastic optimal feedforward and feedback control methodology for superagility
NASA Technical Reports Server (NTRS)
Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.
1992-01-01
A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.
Optimal periodic controller for formation flying on libration point orbits
NASA Astrophysics Data System (ADS)
Peng, Haijun; Zhao, Jun; Wu, Zhigang; Zhong, Wanxie
2011-09-01
An optimal periodic controller based on continuous low-thrust is proposed for the stabilization missions of spacecraft station-keeping and formation-keeping along periodic Libration point orbits of the Sun-Earth system. Additionally, a new numerical algorithm is proposed for solving the periodic Riccati differential equation in the design of the optimal periodic controller. Practical missions show that the optimal periodic controller (which is designed with the linear periodic time-varying equation of the relative dynamical model) overcomes the problems and limitations of the time-variant LQR controller. Furthermore, nonlinear numerical simulations are presented for the missions of a leader spacecraft station-keeping and three follower spacecraft formation-keeping. Numerical simulations show that the velocity increments for spacecraft control and relative position errors vary little with changes in the altitude of periodic orbits. In addition, the actual trajectories of the leader and the follower spacecraft track the periodic reference orbit with high accuracy under the perturbation of the eccentric nature of the Earth's orbit and the initial injection errors. In particular, the relative position errors obtained by the optimal periodic controller for spacecraft formation-keeping are all in the range of millimeters.
A multiple objective optimization approach to quality control
NASA Technical Reports Server (NTRS)
Seaman, Christopher Michael
1991-01-01
The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios
Quadratic Optimization in the Problems of Active Control of Sound
NASA Technical Reports Server (NTRS)
Loncaric, J.; Tsynkov, S. V.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).
An inverter/controller subsystem optimized for photovoltaic applications
NASA Technical Reports Server (NTRS)
Pickrell, R. L.; Osullivan, G.; Merrill, W. C.
1978-01-01
Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. Optimization of the inverter/controller design is discussed as part of an overall photovoltaic power system designed for maximum energy extraction from the solar array. The special design requirements for the inverter/ controller include: a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy.
Control design variable linking for optimization of structural/control systems
NASA Technical Reports Server (NTRS)
Jin, I. M.; Schmit, L. A.
1991-01-01
In this study a method is presented to integrate the design space of structural/control system optimization problems in the case of state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in the optimization by extending design variable linking concepts to the control gains. Examples which involve a variety of behavior constraints, including dynamic transient response and control force limits, are effectively solved by using the method presented.
Torque-based optimal acceleration control for electric vehicle
NASA Astrophysics Data System (ADS)
Lu, Dongbin; Ouyang, Minggao
2014-03-01
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.
Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives
Wang, Jack M.; Hamner, Samuel R.; Delp, Scott L.; Koltun, Vladlen
2015-01-01
We present a technique for automatically synthesizing walking and running controllers for physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of-freedom are actuated using a set of eight Hill-type musculotendon models in each leg, with biologically-motivated control laws. The parameters of these control laws are set by an optimization procedure that satisfies a number of locomotion task terms while minimizing a biological model of metabolic energy expenditure. We show that the use of biologically-based actuators and objectives measurably increases the realism of gaits generated by locomotion controllers that operate without the use of motion capture data, and that metabolic energy expenditure provides a simple and unifying measurement of effort that can be used for both walking and running control optimization. PMID:26251560
Control and structural optimization for maneuvering large spacecraft
NASA Technical Reports Server (NTRS)
Chun, H. M.; Turner, J. D.; Yu, C. C.
1990-01-01
Presented here are the results of an advanced control design as well as a discussion of the requirements for automating both the structures and control design efforts for maneuvering a large spacecraft. The advanced control application addresses a general three dimensional slewing problem, and is applied to a large geostationary platform. The platform consists of two flexible antennas attached to the ends of a flexible truss. The control strategy involves an open-loop rigid body control profile which is derived from a nonlinear optimal control problem and provides the main control effort. A perturbation feedback control reduces the response due to the flexibility of the structure. Results are shown which demonstrate the usefulness of the approach. Software issues are considered for developing an integrated structures and control design environment.
An application of modern control theory to an elastic spacecraft
NASA Technical Reports Server (NTRS)
Larson, V.; Likins, P. W.
1976-01-01
Results are presented to illustrate the application of established procedures of linear, quadratic, Gaussian optimal estimation and control to a spacecraft with dynamically significant elastic appendages. Interpretations are provided in both time domain and frequency domain, and conclusions are drawn for a wide class of problems of flexible spacecraft attitude control.
Optimal control of underactuated mechanical systems: A geometric approach
NASA Astrophysics Data System (ADS)
Colombo, Leonardo; Martín De Diego, David; Zuccalli, Marcela
2010-08-01
In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.