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Joint design of the discrete phase transmit sequence and receive filter in radar systems

IET RADAR SONAR AND NAVIGATION 2022年第2期16卷 315-326页

作者： Pishrow, Mohammad Mehdi Abouei, Jamshid Yazd Univ Dept Elect Engn POB 9195-741 Yazd Iran

In this study, the joint design of discrete phase transmit sequences and receive filters with the low peak sidelobe level and integrated sidelobe level in radar systems is considered. The problem is formulated as a minimisation of the peak (integrated) sidelobe level, forcing a unimodular discrete phase constraint at the design stage. To deal with the resulting non-convex and in general the NP-hard optimisation problem, an iterative method based on the alternate optimisation approach is proposed. Each iteration of the proposed method involves a non-convex min-max problem to be solved. In addition, a sequential rank-one constraint relaxation framework is proposed to initialise the procedure, each iteration of which requires the solution of a convex problem. Simulation results show that using the proposed framework for jointly finding transmit sequences and receive filters leads to a better peak sidelobe ratio and integrated sidelobe ratio for discrete phase sequences than the optimal mismatched filters design approach.

关键词： iteration methods radar systems matched filters integrated sidelobe ratio convex programming minimisation iterative methods resulting nonconvex low peak sidelobe level radar signal processing integrated sidelobe level optimal mismatched filters design approach NP-hard optimisation problem nonconvex min-max problem minimax techniques signal processing alternate optimisation approach discrete phase transmit sequence convex problem discrete phase sequences jointly finding transmit sequences design stage unimodular discrete phase constraint peak sidelobe ratio

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Improved exploitation of higher order smoothness in derivative-free optimization

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OPTIMIZATION LETTERS 2022年第7期16卷 2059-2071页

作者： Novitskii, Vasilii Gasnikov, Alexander Moscow Inst Phys & Technol Dolgoprudnyi Russia RAS Inst Informat Transmiss Problems Moscow Russia ISP RAS Res Ctr Trusted Artificial Intelligence Moscow Russia

We consider beta-smooth (satisfies the generalized Holder condition with parameter beta > 2) stochastic convex optimization problem with zero-order one-point oracle. The best known result was (Akhavan et al. in Exploiting higher order smoothness in derivative-free optimization and continuous bandits, 2020): E[f((x) over bar (N)) - f(x*)] = O(n(2)/gamma N beta-1/beta) in gamma-strongly convex case, where n is the dimension. In this paper we improve this bound: E[f((x) over bar (N)) - f(x*)] = O(n(2-1/beta)/gamma N beta-1/beta).

关键词： Zeroth-order optimization convex problem Stochastic optimization One-point oracle Smoothing kernel

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Robust fuzzy model predictive control for voltage regulation in islanded microgrids

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第5期16卷 1013-1029页

作者： Mottaghizadeh, Masood Aminifar, Farrokh Amraee, Turaj Sanaye-Pasand, Majid Univ Tehran Coll Engn Sch Elect & Comp Engn Tehran 113654563 Iran KN Toosi Univ Technol Fac Elect Engn Dept Elect Engn Tehran Iran

An effective robust fuzzy model predictive control (RFMPC) method for secondary voltage control in islanded microgrids (mu Gs) is presented here. In contrast to the existing techniques, which require a detailed model of mu G and an ideal communication network between mu G central controller and primary local controllers, RFMPC is synthesized for a non-linear model of the mu G with various time delays, uncertainties, and bounded disturbances. The famous Takagi-Sugeno fuzzy approach is adopted to approximate the inherently non-linear model of mu G by locally linear dynamics. The Lyapunov-Razumikhin functional method is exploited to deal with time delays. In this regard, sufficient conditions are provided in the form of linear matrix inequalities (LMIs). Then, a sequence of control laws corresponding to a set of terminal constraints is computed offline. Doing so, the online stage is reduced to solving a convex problem with LMI constraints considering the sequence of constraint sets obtained in the offline stage, thereby reducing the computational burden significantly. Robust positive invariance and input-to-state stability property concerning communication network deficiency are then speculated. The effectiveness of the proposed RFMPC is verified via a comprehensive suite of simulations in the MATLAB/SimPowerSystems environment.

关键词： μG central controller delays convex programming voltage control power system stability control laws effective robust fuzzy model predictive control method primary local controllers constraint set sequence input-to-state stability property fuzzy control predictive control linear matrix inequalities time delays islanded microgrids sufficient conditions Lyapunov methods Takagi-Sugeno fuzzy approach robust positive invariance centralised control robust control distributed power generation locally linear dynamics Lyapunov-Razumikhin functional method MATLAB-SimPowerSystems environment LMIs voltage regulation nonlinear model communication network efficiency control law sequences convex problem power generation control secondary voltage control RFMPC method

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Frank-Wolfe for Sign-Constrained Support Vector Machines

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2022年第10期E105D卷 1734-1742页

作者： Tajima, Kenya Henmi, Takahiko Kato, Tsuyoshi Gunma Univ Grad Sch Sci & Technol Kiryu 3768515 Japan

Domain knowledge is useful to improve the generalization performance of learning machines. Sign constraints are a handy represen-tation to combine domain knowledge with learning machine. In this paper, we consider constraining the signs of the weight coefficients in learning the linear support vector machine, and develop an optimization algorithm for minimizing the empirical risk under the sign constraints. The algorithm is based on the Frank-Wolfe method that also converges sublinearly and possesses a clear termination criterion. We show that each iteration of the Frank-Wolfe also requires O(nd+d2) computational cost. Furthermore, we derive the explicit expression for the minimal iteration number to ensure an c-accurate solution by analyzing the curvature of the objective function. Fi-nally, we empirically demonstrate that the sign constraints are a promising technique when similarities to the training examples compose the feature vector.

关键词： Frank-Wolfe algorithm support vector machine sign constraints convex problem and dual problem

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Rapid and safe wire tension distribution scheme for redundant cable-driven parallel manipulators

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ROBOTICA 2022年第7期40卷 2395-2408页

作者： Mousavi, Mohammad Reza Ghanbari, Masoud Moosavian, S. Ali A. Zarafshan, Payam KN Toosi Univ Technol Ctr Excellence Robot & Control Adv Robot & Automated Syst ARAS Lab Fac Mech Engn Tehran Iran Univ Tehran Dept Agrotechnol Coll Aburaihan Tehran Iran

A non-iterative analytical approach is investigated to plan the safe wire tension distribution along with the cables in the redundant cable-driven parallel robots. The proposed algorithm considers not only tracking the desired trajectory but also protecting the system against possible failures. This method is used to optimize the non-negative wire tensions through the cables which are constrained based on the workspace conditions. It also maintains both actuators' torque and cables' tensile strength boundary limits. The pseudo-inverse problem solution leads to an n-dimensional convex problem, which is related to the robot degrees of redundancy. In this paper, a comprehensive solution is presented for a 1-3 degree(s) of redundancy in wire-actuated robots. To evaluate the effectiveness of this method, it is verified through an experimental study on the RoboCab cable robot in the infinity trajectory tracking task. As a matter of comparison, some standard methods like Active-set and sequential quadratic programming are also presented and the average elapsed time for each method is compared to the proposed algorithm.

关键词： cable tension distribution redundant manipulators convex problem

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Anomaly Detection Method for Rocket Engines Based on convex Optimized Information Fusion

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SENSORS 2024年第2期24卷 415页

作者： Sun, Hao Cheng, Yuehua Jiang, Bin Lu, Feng Wang, Na Kim, Jongmyon Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing 210016 Peoples R China

The power system, as a core component of a launch vehicle, has a crucial impact on the reliability and safety of a rocket launch. Due to the limited measurement information inside the engine, it is often challenging to realize fast and accurate anomaly detection. For this reason, this paper introduces the rocket flight state data to expand the information source for anomaly detection. However, engine measurement and rocket flight state information have different data distribution characteristics. To find the optimal data fusion scheme for anomaly detection, a data set information fusion algorithm based on convex optimization is proposed, which solves the optimal fusion parameter using the convex quadratic programming problem and then adopts the adaptive CUSUM algorithm to realize the fast and accurate anomaly detection of engine faults. Numerical simulation tests show that the algorithm proposed in this paper has a higher detection accuracy and lower detection time than the traditional algorithm.

关键词： rocket engine data fusion convex problem fault diagnosis

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Beamspace-MIMO-NOMA Enhanced mm-Wave Wireless Communications: Performance Optimization 2

Beamspace-MIMO-NOMA Enhanced mm-Wave Wireless Communications...

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2nd International Conference on Computer Science and Software Engineering (CSASE)

作者： Majeed, Ammar A. Hburi, Ismail Univ Wasit Elect Engn Dept Wasit Iraq

ISBN: (纸本)9781665426329

In the literature, it is considered that the Multi-Input Multi-Output (MIMO) antennas are the most capable approach to meet all 5G requirements. One of the MIMO mm-wave drawbacks is the elevated power consumption due to Radio-Frequency-Chains (RF-Chains), which is efficiently solved using the beamspace-MIMO concept that reduces the total RF-chains number without significant performance loss. Another issue appeared with beamspace - MIMO, the limited number of users served on the exact time-frequency domain. To overcome these challenges, it has been proposed to use the Non-Orthogonal-Multiple-Access (NOMA) with beamspace to produce the new paradigm of beamspace-MIMO-NOMA. Hence, it can serve a group of users with correlated channels via the same beam using one RF-chain, which makes the users' number more than the RF-Chains number. This paper discusses the Spectral\Energy Efficiency (SETE) of the proposed scheme. Specifically, we propose and develop a low-complex iterative algorithm that reaches a near-perfect performance. The suggested approach, namely MSE-DPA, which stands for Mean-Square-Error Based Dynamic-Power-Allocation-Algorithm, is verified for the validity of this Figure-of-Merit. Simulation results show superior outcomes in terms of EE, which is about 85% greater than the traditional-MIMO systems.

关键词： MIMO-NOMA Millimeter-Wave Beamspace Beamspace-MIMO-NOMA RF-chains Power Allocation Beamforming Energy Efficiency Spectral Efficiency convex problem

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Stable Robust Fixed-Order Controller Design for Scalar and Multi-Output Systems 61

Stable Robust Fixed-Order Controller Design for Scalar and M...

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61st Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE)

作者： Mori, Shoma Nobuyama, Eitaku Kyushu Inst Technol Dept Syst Design & Informat Iizuka Japan Kyushu Inst Technol Dept Intelligent & Control Syst Iizuka Japan

ISBN: (数字)9784907764784

ISBN: (纸本)9784907764784

The objective of this paper is to propose new robust fixed-order controller design methods which guarantee the stability and the minimum-phase property of controllers. To this end, sufficient conditions for polynomials to be stable are given and using the sufficient conditions a robust fixed-order controller design method is proposed for a scaler system case. The design method reduces a robust fixed-order controller design problem which guarantees the stability of the obtained controller to a convex problem. Moreover, the proposed method is extended to a multi-output case and a numerical example of a 3-inertia system is presented to show the effectiveness of the proposed method.

关键词： Robust control Fixed-order controller Stable controller convex problem

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Near-optimal hybrid precoding for millimeter wave massive MIMO systems via cost-efficient Sub-connected structure

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IET COMMUNICATIONS 2020年第14期14卷 2340-2349页

作者： Huang, Yu Liu, Chen Song, Yunchao Yu, Xiaolei Nanjing Univ Posts & Telecommun Coll Elect & Opt Engn Nanjing Peoples R China Nanjing Univ Posts & Telecommun Coll Microelect Nanjing Peoples R China Nanjing Univ Posts & Telecommun Natl & Local Joint Engn Lab RF Integrat & Microas Nanjing Peoples R China Jiangsu Inst Qual & Standardizat Natl Qual Supervis & Testing Ctr RFID Prod Jiangs Nanjing Peoples R China

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) is a promising technology for next generation wireless communications. The utilisation of traditional full digital precoding techniques for mmWave massive MIMO systems is too costly. Fortunately, the hybrid (analogue/digital) precoding is a better choice. In this study, the authors investigate a near-optimal iterative approximation hybrid precoding algorithm via cost-efficient sub-connected structure for mmWave massive MIMO systems. Based on the minimum mean square error (MSE) criterion, the optimal design of the proposed hybrid precoders is non-convex. The original problem is reformulated as two optimisation sub-problems, where one of the sub-problems is convex and another is non-convex. First, the authors convert the non-convex sub-problem into a convex problem by relaxing the constant modulus constraint from beampattern with interference control method, and eliminating the block diagonal constraint from vector operation with the properties of Kronecker product. Then the two convex sub-problems are solved iteratively. The proposed algorithm can achieve a highly approximate optimal solution, which can be theoretically demonstrated to converge to a Karush-Kuhn-Tucker point of the original problem. Simulation results show that the proposed algorithm via both sub-connected and fully connected structure gets favourable performance in terms of MSE and achievable rate.

关键词： mean square error methods iterative methods MIMO communication precoding millimetre wave communication convex programming concave programming interference suppression approximation theory millimeter wave massive MIMO systems millimeter wave massive multiple-input multiple-output systems traditional full digital precoding techniques mmWave massive MIMO systems constant modulus block diagonal constraints nonconvex problem convex problem near-optimal hybrid precoding cost-efficient sub-connected structure next-generation wireless communications analogue-digital precoding gigabits per second transmitting data rate gigabits per second transmitting data rate near-optimal iterative approximation hybrid precoding algorithm minimum mean square error criterion optimisation sub-problems beampattern interference control method Kronecker product approximate optimal solution Karush-Kuhn-Tucker point achievable rate MSE

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Truss optimization applying finite element limit analysis including global and local stability

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2020年第1期62卷 41-54页

作者： Poulsen, Peter Noe Olesen, John Forbes Baandrup, Mads Tech Univ Denmark Dept Civil Engn Brovej B-118 DK-2800 Lyngby Denmark COWI AS Dept Major Bridges Int Parallelvej 2 DK-2800 Lyngby Denmark

For practical applications of optimized truss structures, it is essential to include global and local stability in order to obtain stable and realistic structures. The challenge of including both global and local stability has previously been approached in many ways. However, these proposals often lead to ill-conditioned optimization problems, with convergence issues due to the concavity of the problem. In this paper, a new method for handling both global and local stability in truss optimization is presented. The proposed method is based on the finite element limit analysis method. Initially, the global stability problem is solved by a convex semidefinite constraint, and subsequently, the concave local stability problem is included through an iterative process, where the local stability constraints are linearized and solved by a convex sub-problem. This step-wise approach diminishes convergence issues due to the concavity of the problem. The proposed method is demonstrated through three different applications showing significant effects of including global and local stability in the optimized designs, while at the same time demonstrating the validity and potential of the proposed method.

关键词： Truss topology optimization Global stability convex problem Limit analysis

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