Phase Constraints Research Articles

The nonlinear-phase design of FBMC prototype filter based on filter coefficient symmetry characteristic

To promote filter bank multicarrier (FBMC) in future communication, a novel design method of nonlinear phase FIR filter (NLPFF) is proposed under the principle of constrained minimax (CMM), by which the designed filter will act as the FBMC prototype filter. In this method, the filter coefficient symmetry characteristic (FCSC) is exploited in replace of the conventional phase response error (PRE), which simplifies the establishment of phase constraint and benefits the construction of direct magnitude constraint. Consequently, the proposed constraints related to FCSC outperform the conventional constraints addressing complex frequency response errors, since the former yields a wider range of controllable PRE as well as the dramatically reduced constraint scale. Moreover, in order to restrict the sampling inter-symbol interference, the Nyquist condition (NYQ) is constrained in the frequency domain, which circumvents the initial nonconvex problem. Simulations confirm the effectiveness of the proposed method, where the FCSC can be sufficiently relaxed to improve the stopband attenuation, making this nonlinear-phase design more flexible than previous designs of FBMC prototype filter. Besides, the bit error rate test demonstrates that the designed NLPFFs are superior to the conventional PHYDYAS filter, therefore, the proposed design can certainly produce high quality prototype filter for FBMC system.

Safe control of SEMS in group interaction

Introduction:In control over a group of interacting smart electromechanical systems (SEMS), situations may arise when the operator’s instructions and/or the automatic control system at a higher level contradict the internal state of the controlled SEMS and/or the environment of choice. Such situations can be prevented by algorithms which check the fulfillment of conditions for the admissibility of movements. These algorithms can be based on modeling the SEMS behavior using logical-probabilistic or logicallinguistic descriptions of situations, and on non-scalar quality criteria when making decisions.Purpose:The development of algorithms for safe control over robots based on SEMS modules with phase constraints, under incomplete certainty of the environment.Results:Algorithms have been developed for safe control over three robots, using a mathematical description of situational control over a group of SEMS and the methodology of organizing the situational control over a group of mobile SEMS. The algorithms move the robots from certain current positions to specified terminal positions, avoiding their collisions with each other. In order to avoid collisions, the decision-making system in a robot’s central nervous system uses robot’s priorities based on the distance between the robots. An approach has been proposed to overcome uncertainty on the way (trajectory) of the robots. Uncertainties in the form of logical-probabilistic and logical-linguistic type constraints are considered. It is shown that these restrictions can be translated into a logical-interval form. This allows you to use standard mathematical programming procedures when searching for the optimal solution.Practical relevance:The obtained algorithms can be used for decision-making in the central nervous system and when controlling robots.

Violation of Object Functional Unimodality and Evolutionary Algorithms for Optimal Control Problem Solution

Some common properties of violation of object function unimodality in optimal control problems are considered. Phase constraints and control object models for special symmetric systems are considered. It is shown that for a control problem of a group of objects, given in the form of a symmetric system of equations, for certain initial and terminal conditions the functional is not unimodal. It is claimed that for optimal control problems with non-unimodal functionals it is efficient to use evolutionary algorithms. An example of an optimal control problem for a group of symmetric objects with phase constraints resolved by evolutionary and gradient algorithms is provided.

The Method of Non-Local Control Improvement in Optimal Control Problems with Constraints

A new approach to solving optimal control problems with terminal and phase constraints is proposed on the basis of constructing and solving a system of conditions for improving admissible control in the form of the fixed point problem for a constructed control operator. This form makes it possible to apply the developed theory and fixed-point methods for the effective search of admissible improving controls. To construct these conditions, we apply the transition to the auxiliary problem of optimizing a regular Lagrange functional without constraints with mixed control functions and parameters. Approbation and comparative analysis of the effectiveness of the proposed approach of fixed points on model and test examples are carried out.

Construction of a solution for optimal control problem with phase and integral constraints

Abstract. A method for solving the Lagrange problem with phase restrictions for processes described by ordinary differential equations without involvement of the Lagrange principle is supposed. Necessary and sufficient conditions for existence of a solution of the variation problem are obtained, feasible control is found and optimal solution is constructed by narrowing the field of feasible controls. The basis of the proposed method for solving the variation problem is an immersion principle. The essence of the immersion principle is that the original variation problem with the boundary conditions with phase and integral constraints is replaced by equivalent optimal control problem with a free right end of the trajectory. This approach is made possible by finding the general solution of a class of Fredholm integral equations of the first order. The scientific novelty of the results is that: there is no need to introduce additional variables in the form of Lagrange multipliers; proof of the existence of a saddle point of the Lagrange functional; the existence and construction of a solution to the Lagrange problem are solved together.

Aggressive Behavior in a Non-Antagonistic Positional Differential Game

This paper is a continuation of the research [3], in which a formalization of nonantagonistic positional differential two-player games (NPDGs) was offered for the case of different behavioral types of players (in short, the NPDGwBT) as follows. In addition to the usual (normal, nor) type of behavior oriented towards maximization of his/her own functional, each player can use other behavioral types described in [2, 7], namely, the altruistic (alt), aggressive (agg), and paradoxical (par) ones. By assumption, each player can switch from one behavioral type to another in the course of the game. Note that in [6, 7] such switching allowed to obtain new solutions in a repeated bimatrix 2 × 2 game. The formalization of players’ actions in the NPDGwBT presented in [3] relies on the formalization and results of the general theory of antagonistic positional differential games [4, 5]. By assumption, in the NPDGwBT each player chooses a closed-loop strategy simultaneously with his/her own indicator function that is defined on the whole game duration and takes values from the set {nor, alt, agg, par}. The indicator function shows the behavioral type dynamics of a given player. The strong and weak BT-solutions of the NPDGwBT were defined in [3]. Expectedly, in some cases the abnormal types of behavior (the ones differing from the normal type) may yield better outcomes for players in the NPDGwBT than in the NPDG. The main emphasis of the examples in [3] was stressed on the use of altruistic behavior by all players. This paper considers two examples of games with simple 2D motion dynamics and phase constraints in which each player can demonstrate altruism and also aggression towards a partner for certain time intervals, including the case of mutual aggression. In the first example, strong BT-solutions are constructed in which both players increase their payoffs in comparison with the game with the normal type of behavior. If the players are prohibited to choose the aggressive type of behavior, then the game has no BT-solutions. In the second example, strong BT-solutions are also constructed but, under the prohibition of aggression, they still exist and are induced by the altruistic type of behavior.

Fast Algorithms for Designing Complementary Sets of Sequences Under Multiple Constraints

Complementary sets of sequences (CSSs) are widely used in many applications, such as active sensing and wireless communication. The construction of CSS has attracted considerable attention over the past few decades. In this paper, efficient and comprehensive computational algorithms for CSS design are proposed. We seek to minimize complementary integral sidelobe level (CISL) under multiple constraints, including unimodular, peak-to-average power ratio, discrete phase, and spectrum compatible constraint. The task of CSS design can be formulated as solving a nonconvex constraint optimization problem. As this problem is difficult to tackle directly, we resort to the general majorization-minimization (MM) method. By utilizing the inherent algebraic structure of the objective function, we construct the majorizing function via two consecutive applications of the MM method and obtain a closed-form solution by a couple of FFT operations at each iteration. The relationship between MM-based algorithms and derivative-based algorithms is revealed. Our algorithms are more flexible and widely applicable, and the numerical experiment results demonstrate the effectiveness and superiority over the existing state-of-art algorithms.

Joint Antenna Selection and Analog Precoder Design With Low-Resolution Phase Shifters

Analog precoder was introduced recently to millimeter wave (mmWave) systems with large-scale antenna arrays as a promising hardware-efficient transceiver architecture. In practice, low-resolution phase shifters (PSs) are generally adopted to achieve low hardware cost and low power consumption, which, however, makes fine beam tuning challenging. Recent achievements in antenna selection technology motivate us to exploit the augmented antenna diversity of a large-scale antenna array to compensate the accuracy loss caused by this low-resolution PS implementation. In this correspondence, we consider a narrow-band multiple-input single-output downlink mmWave system. Our goal is to jointly select a set of transmit antennas and design the analog precoder with constant amplitude and discrete phase constraints to maximize the spectral efficiency. In particular, we propose a novel joint antenna selection and analog beamformer design algorithm, which can provide satisfactory performance with low complexity. Simulation results demonstrate the advances of the proposed algorithm compared with the low-resolution analog precoding schemes without antenna selection.

Complex ISNMF: A Phase-Aware Model for Monaural Audio Source Separation

This paper introduces a phase-aware probabilistic model for audio source separation. Classical source models in the short-time Fourier transform domain use circularly-symmetric Gaussian or Poisson random variables. This is equivalent to assuming that the phase of each source is uniformly distributed, which is not suitable for exploiting the underlying structure of the phase. Drawing on preliminary works, we introduce here a Bayesian anisotropic Gaussian source model in which the phase is no longer uniform. Such a model permits us to favor a phase value that originates from a signal model through a Markov chain prior structure. The variance of the latent variables are structured with nonnegative matrix factorization (NMF). The resulting model is called complex Itakura–Saito NMF (ISNMF) since it generalizes the ISNMF model to the case of nonisotropic variables. It combines the advantages of ISNMF, which uses a distortion measure adapted to audio and yields a set of estimates which preserve the overall energy of the mixture, and of complex NMF, which enables one to account for some phase constraints. We derive a generalized expectation-maximization algorithm to estimate the model parameters. Experiments conducted on a musical source separation task in a semiinformed setting show that the proposed approach outperforms state-of-the-art phase-aware separation techniques.

Linear phase sparse system identification in the presence of impulsive noise

ABSTRACTIn this paper, we incorporate an ℓp-norm sparsity constraint into linear phase constrained affine projection-sign algorithm (LPCAP-SA). The proposed algorithm combines the effect of linear phase constrained affine projection sign algorithm and ℓp-norm sparsity constraint .The proposed algorithm has better performance for linear phase sparse system identification in the presence of vigorous impulsive interference. The proposed ℓp-norm LPCAP-SA is based on the ℓ1-norm minimisation criterion on posterior error and ℓp-Norm on weight coefficients and a linear phase constraint. Simulations in Matlab software show that the proposed ℓp-norm LPCAP-SA has robustness against impulsive interferences and sparse environment for linear phase system.

A pedestrian dead reckoning system using a foot kinematic constraint and shoe modeling for various motions

In this paper, we propose a pedestrian dead reckoning (PDR) system that uses the velocity predicted by a foot kinematic constraint and ellipsoidal shoe modeling in the contact phase. Generally, a PDR system with foot-mounted inertial sensors often uses zero-velocity update (ZUPT) to reduce the influence of the bias and white noise in the gyroscope and accelerometer signals. However, when a pedestrian walks irregularly, ZUPT is unsuitable because the velocity is not small enough to assume that it is zero during the stance phase. Unlike a conventional PDR system that uses ZUPT in the stance phase when the shoe has completely stopped, the proposed PDR system uses the predicted velocity in the contact phase when the shoe touches the ground from the heel-strike to the toe-off states by employing the lever arm vector and the angular velocity to predict the nonzero velocity under the kinematic constraint. The lever arm vector is obtained by the attitude of the shoe according to ellipsoidal shoe modeling. The predicted velocity is used as a measure of the filter during the contact phase. The proposed PDR system can be utilized in various motions with nonzero velocity in the contact phase. The performance of the algorithm was verified by experimental results with various motions.

Wave‐LORAKS: Combining wave encoding with structured low‐rank matrix modeling for more highly accelerated 3D imaging

Wave-CAIPI is a novel acquisition approach that enables highly accelerated 3D imaging. This paper investigates the combination of Wave-CAIPI with LORAKS-based reconstruction (Wave-LORAKS) to enable even further acceleration. LORAKS is a constrained image reconstruction framework that can impose spatial support, smooth phase, sparsity, and/or parallel imaging constraints. LORAKS requires minimal prior information, and instead uses the low-rank subspace structure of the raw data to automatically learn which constraints to impose and how to impose them. Previous LORAKS implementations addressed 2D image reconstruction problems. In this work, several recent advances in structured low-rank matrix recovery were combined to enable large-scale 3D Wave-LORAKS reconstruction with improved quality and computational efficiency. Wave-LORAKS was investigated by retrospective subsampling of two fully sampled Wave-encoded 3D MPRAGE datasets, and comparisons were made against existing Wave reconstruction approaches. Results show that Wave-LORAKS can yield higher reconstruction quality with 16×-accelerated data than is obtained by traditional Wave-CAIPI with 9×-accerated data. There are strong synergies between Wave encoding and LORAKS, which enables Wave-LORAKS to achieve higher acceleration and more flexible sampling compared to Wave-CAIPI.

Periodic Regime of Motion of a Vibratory Robot under a Control Constraint

A class of motions of a vibratory robot consisting of a body with a pendulum inside it, on the angular acceleration of which a constraint is imposed, is considered. The limits of the angular acceleration correspond to the technical characteristics of the motor providing the pendulum rotation. Some phase constraints are imposed on the system and the control is proposed which satisfies them and provides periodic motions of the robot. The control during each period consists of seven intervals; choice of control at each of them is conditioned by velocity maximization. For considered control law numerical experiments are carried out and comparison with other controls is presented.

Study of the Practical Convergence of Evolutionary Algorithms for the Optimal Program Control of a Wheeled Robot

Evolutionary algorithms for solving the problem of the optimal program control are considered. The most popular evolutionary algorithms, the genetic algorithm (GA), the differential evolution (DE) algorithm, the particle swarm optimization (PSO), the bat-inspired algorithm (BIA), the bees algorithm (BA), and the grey wolf optimizer (GWO) algorithm are described. An experimental analysis of these algorithms and their comparison with gradient methods are given. An experiment was carried out to solve the problem of the optimal control of a mobile robot with phase constraints. Indicators of the best objective functional value, the average value for several startups, and the standard deviation were used to compare the algorithms.

Improving parallel imaging by jointly reconstructing multi-contrast data.

To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Admissible Controls in a Nonlinear Time-Optimal Problem with Phase Constraints

Abstract The paper is devoted to constructing admissible controls in a problem of optimal control by a nonlinear dynamic system under constraints on the current phase state. The dynamic system under consideration describes the controlled motion of a carrier rocket from the launching point to the time when the carrier rocket enters a given elliptic earth orbit. A problem consists in designing a program control for the carrier rocket that provides the maximal value of the payload mass led to the given orbit and the fulfillment of a number of additional restrictions on the current phase state of the dynamic system at the atmospheric part of the trajectory. The restrictions considered are due to the need to take into account the values of the dynamic velocity pressure, the attack angle and slip angle when the carrier moves in dense layers of the atmosphere. Such a problem is equivalent to a nonlinear time-optimal problem with phase constraints for carrier rockets of some classes. The algorithm for constructing admissible controls ensuring the fulfillment of additional phase constraints is suggested. The methodological basis of this algorithm is the application of some predictive control. This control is constructed in the problem without taking into account the constraints above. For a deterministic model of the atmosphere, such a predictive control is used to predict the values of a part of the phase state of the dynamic system at the next time. The prediction results are applied in the procedure of desired control construction. This procedure essentially takes into account specific features of the additional constraints. The results of numerical modeling are presented.

Phase-Constrained Parallel Magnetic Resonance Imaging Reconstruction Based on Low-Rank Matrix Completion

Low-rank matrix completion with phase constraints have been applied to the single-channel magnetic resonance imaging (MRI) reconstruction. In this paper, the reconstruction of sparse parallel imaging with smooth phase in each coil is formulated as the completion of a low-rank data matrix, which is modeled by the k-space neighborhoods and symmetric property of samples. The proposed algorithm is compared with a calibrationless parallel MRI reconstruction method based on both simulation data and real data. The experiment results show the proposed method has better performance in terms of MRI imaging enhancement, scanning time reduction, and denoising capability.

Multipoint Numerical Criterion for Manifolds to Guarantee Attractor Properties in the Problem of Synergetic Control Design

The paper presents the results of our research on the application of symbolic regression methods for the numerical solution of the problem of synthesis of synergetic control. Synergetic control is characterized by the presence of manifolds in the state space that must have the properties of an attractor, in particular terminal manifolds, as well as the existence of regions of state space through which system solutions do not pass, for example, phase constraints, that must have the properties of repellers. In the present paper we formulate a numerical criterion for ensuring the property of an attractor for a terminal manifold of arbitrary dimension, taking into account the dynamic behavior of the system in a neighborhood of a given manifold. The results of computational experiments on the effective application of the proposed criterion are presented. It is shown that the proposed approach makes it possible to automate the synthesis of synergistic control using the methods of symbolic regression.

Immersion principle for a variation calculus problem with boundary conditions

The is based on the investigation of the Fredholm integral equation of the first kind. For the Fredholm integral equation of the first kind, the existence theorem for the solution as well as the theorem on its general solution are proved. The basis of the proposed method for solving the variation problem is the principle. The essence of the is that the original variation problem with the boundary conditions with phase and integral constraints is replaced by equivalent optimal control problem with a free right end of the trajectory. This approach is made possible by finding the general solution of a class of Fredholm integral equations of the first order. In this work a method for solving the Lagrange problem with phase restrictions for processes described by ordinary differential equations without involvement of the Lagrange is supposed. Necessary and sufficient conditions for existence of a solution of the variation problem are obtained, feasible control is found and optimal solution is constructed by narrowing the field of feasible controls. In contrast to the well-known method for solving the problem of the variation calculus on the basis of the Lagrange principle, an entirely new approach an immersion principle is proposed. undefined undefined Звуковая функция ограничена 200 символами Настройки : История : Обратная связь : Donate Закрыть

Construction of terminal control for one nonlinear system

Abstract A mathematical model of motion of a nonlinear controlled system describing the dynamics of a four-screw helicopter with a rotary device for engines is considered. The equations of motion of the model in question differ from similar models in the order of the ones in the equations for the dynamics of a number of phase variables of the model. The problem of terminal control in the presence of phase constraints is considered. To solve it, the method of dynamic linearization of the location of the control function is applied. The values of the parameters are found under which the solution of the problem by this method does not contain singularities and satisfies the imposed condition of the problem with constraints on the phase variables. For parameters satisfying these conditions numerically Terminal controls and corresponding trajectories are constructed.