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convex-optimization-based Constrained Control Strategy for 3-DOF Tandem Helicopter using Feedback Linearization

JOURNAL OF optimization THEORY AND APPLICATIONS 2021年第2-3期191卷 736-755页

作者： Vijayan, Nidya M. Johnson, Mija S. Jacob, Jeevamma Natl Inst Technol Calicut Dept Elect Engn Kozhikode Kerala India

This paper proposes a convex-optimization-based relatively optimal controller (ROC) for the attitude regulation of 3 degree of freedom (DOF) tandem helicopter utilizing feedback linearization (FBL). The constant velocity in the pseudo-active axis achieved by regulating two active axes results in the motion of the helicopter in a circular path at a specified altitude. The FBL helps in transforming the system model into two decoupled subsystems in Brunovsky's canonical form to reduce the computational complexities. Minimum control effort and constraint satisfaction are guaranteed by ROC while regulating the attitude of the 3-DOF tandem helicopter from a nominal initial condition. The Lyapunov stability theorem is employed for illustrating the stability of the closed-loop system. The robustness analysis gives a measure of perturbation that the designed controller can accommodate. Simulation results demonstrate the superiority over an FBL-based linear quadratic regulator controller. The efficacy of the proposed strategy is substantiated by experimental results.

关键词： convex-optimization 3-DOF tandem helicopter Feedback linearization Optimal control Lyapunov stability

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H2 model reduction for diffusively coupled second-order networks by convex-optimization

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AUTOMATICA 2022年 137卷 110118-110118页

作者： Yu, Lanlin Cheng, Xiaodong Scherpen, Jacquelien M. A. Xiong, Junlin Hefei Univ Technol Sch Elect Engn & Automation Hefei 230009 Peoples R China Westlake Univ Westlake Inst Adv Study Hangzhou 310024 Peoples R China Univ Cambridge Dept Engn Trumpington St Cambridge CB2 1PZ Cambs England Univ Groningen Engn & Technol Inst Groningen Fac Sci & Engn Jan C Willems Ctr Syst & Control Nijenborgh 4 NL-9747 AG Groningen Netherlands Univ Sci & Technol China Dept Automation Hefei 230026 Peoples R China

This paper provides an H-2 optimal scheme for reducing diffusively coupled second-order systems evolving over undirected networks. The aim is to find a reduced-order model that not only approximates the input-output mapping of the original system but also preserves crucial structures, such as the second-order form, asymptotically stability, and diffusive couplings. To this end, an H-2 optimal approach based on a convex relaxation is used to reduce the dimension, yielding a lower order asymptotically stable approximation of the original second-order network system. Then, a novel graph reconstruction approach is employed to convert the obtained model to a reduced system that is interpretable as an undirected diffusively coupled network. Finally, the effectiveness of the proposed method is illustrated via a large-scale networked mass-spring-damper system. (C) 2021 The Author(s). Published by Elsevier Ltd.

关键词： Second-order networks Diffusive coupling H-2 model reduction Linear matrix inequality convex-optimization

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A projection-based algorithm for model-order reduction with H₂ performance: A convex-optimization setting

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AUTOMATICA 2018年 93卷 510-519页

作者： Ibrir, Salim King Fahd Univ Petr & Minerals Elect Engn Dept KFUPM Box 5038 Dhahran Saudi Arabia

A suboptimal and a simple solution to the H-2-model-order-reduction problem is given. The proposed procedure is a combination of projection and H-2 Model-order Reduction (MOR) techniques. To show the efficacy of the proposed method, a set of comparisons with classical MOR methods is provided with numerical simulations. The numerical algorithm is subsequently employed in the design of reduced order nonlinear systems satisfying the Input-to-State Stability (ISS) with respect to their inputs. Reduced order models for nonlinear electrical circuits are successfully built to demonstrate the usefulness and the performance of the developed procedure. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Suboptimal H-2-model-order reduction Model-order reduction of nonlinear systems Electrical circuits convex-optimization Input-to-state-stable (ISS) systems

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convex - optimization for Reconstructing Compressed Signal using Orthogonal Matching Pursuit 3

Convex - Optimization for Reconstructing Compressed Signal u...

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3rd IEEE International Conference on Communication and Electronics Systems (ICCES)

作者： Anupama, H. Shanthala, S. Mahadevaswamy, H. R. Awasthi, Nitin Bangalore Inst Technol Bengaluru Karnataka India Bangalore Inst Technol Dept Telecommun Engn Bengaluru Karnataka India Jawaharlal Nehru Natl Coll Engn Shivamogga Karnataka India Apsis Solut Tech Bengaluru Karnataka India

ISBN: (纸本)9781538647653

Reconstruction of 2D signals is challenging as it involves a large number of samples. To reduce the redundant data, a sparse representation technique called Compressed Sensing (CS) is explored. In compressed sensing, sparse vector is compressed in size by using suitable sensing matrix. However reconstruction of original signal from compressed signal needs better understanding of sparseness of original signal and characteristics of sensing matrix. The reconstruction algorithm belongs to the category of convex optimization. This paper proposes an iterative greedy algorithm used in convex optimization technique for image reconstruction named Orthogonal Matching Pursuit (OMP). This work demonstrates how effectively we can use OMP to recover k-sparse signals in greedy fashion with lesser number of random linear measurements for a signal. The experimental results support the same.

关键词： Orthogonal Matching Pursuit Compressed sensing convex-optimization

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High Performance 3D CMP Design with Stacked Hybrid Memory Architecture in the Dark Silicon Era Using a convex optimization Model

High Performance 3D CMP Design with Stacked Hybrid Memory Ar...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Onsori, Salman Asad, Arghavan Raahemifar, Kaamran Fathy, Mahmood Bilkent Univ Dept Comp Engn Ankara Turkey Dept Comp Engn Ankara Iran Iran Univ Sci & Technol Tehran Iran Ryerson Univ Elect & Comp Engn Dept Toronto ON Canada

ISBN: (纸本)9781479953417

In this article, we present a convex optimization model to design a stacked hybrid memory system to improve performance and reduce energy consumption of the chipmultiprocessor (CMP). Our convex model optimizes numbers and placement of SRAM and STT-RAM memories on the memory layer, and efficiently maps applications/threads on cores in the core layer. Power consumption that is the main challenge in the dark silicon era is represented as a power constraint in this work and it is satisfied by the detailed optimization model in order to design a dark silicon aware 3D CMP. Experimental results show that the proposed architecture considerably improves the energydelay product (EDP) and performance of the 3D CMP compared to the Baseline memory design.

关键词： Dark silicon Non-Volatile Memory (NVM) Hybrid memory Architecture Embedded chip-multiprocessor (eCMP) convex-optimization power management

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High performance 3D CMP design with stacked hybrid memory architecture in the dark silicon era using a convex optimization model

High performance 3D CMP design with stacked hybrid memory ar...

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International Symposium on Circuits and Systems

作者： Salman Onsori Arghavan Asad Kaamran Raahemifar Mahmood Fathy Computer Engineering Department Bilkent University Ankara Turkey Computer Engineering Department Iran University of Science and Technology Tehran Iran Electrical and Computer Engineering Department Ryerson University Ontario Canada

ISBN: (纸本)9781479953424

In this article, we present a convex optimization model to design a stacked hybrid memory system to improve performance and reduce energy consumption of the chip-multiprocessor (CMP). Our convex model optimizes numbers and placement of SRAM and STT-RAM memories on the memory layer, and efficiently maps applications/threads on cores in the core layer. Power consumption that is the main challenge in the dark silicon era is represented as a power constraint in this work and it is satisfied by the detailed optimization model in order to design a dark silicon aware 3D CMP. Experimental results show that the proposed architecture considerably improves the energy-delay product (EDP) and performance of the 3D CMP compared to the Baseline memory design.

关键词： power management Dark silicon Non-Volatile Memory (NVM) Hybrid memory Architecture Embedded chip-multiprocessor (eCMP) convex-optimization

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A High-performance Hybrid Memory Architecture for Embedded CMPs Using A convex optimization model 12

A High-performance Hybrid Memory Architecture for Embedded C...

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International System-on-Chip (SoC) Design Conference

作者： Onsori, Salman Asad, Arghavan Raahemifar, Kaamran Fathy, Mahmood Bilkent Univ Dept Comp Engn Ankara Turkey Iran Univ Sci & Technol Dept Comp Engn Tehran Turkey Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)9781467393089

In this article, we present a convex optimization model to design a stacked hybrid memory system for 3D embedded chip-multiprocessors (eCMP). Our convex model optimizes numbers and placement of SRAM and STT-RAM memories on the memory layer, and maps applications/threads on cores in the core layer effectively. The detailed proposed model satisfies the power constraint which is the main challenge of dark-silicon era. Experimental results show that the proposed architecture considerably improves the energy-delay product (EDP) and performance of the 3D eCMP compared to the Baseline memory design.

关键词： Non-Volatile Memory (NVM) Hybrid memory Architecture Embedded Chip-multiprocessor (eCMP) convex-optimization

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Energy-Efficient Power-Controlled Resource Allocation for MIMO-Based Cognitive-Enabled B5G/6G Indoor-Flying Networks

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IEEE ACCESS 2022年 10卷 106828-106840页

作者： Salameh, Haythem Bany Al-Maaitah, Rakan Al-Obiedollah, Haitham Al-Ajlouni, Ahmad Al Ain Univ Dept Network & Commun Engn Al Ain U Arab Emirates Yarmouk Univ Dept Telecommun Engn Irbid 21136 Jordan Staffordshire Univ Sch Comp Stoke On Trent ST4 2DE Staffs England Hashemite Univ Fac Engn Dept Elect Engn Zarqa 13133 Jordan Al Balqa Appl Univ Fac Engn Al Salt 19117 Jordan

The proliferation of unmanned aerial vehicles (UAV), i.e., drones, in communication systems has recently attracted both industry and academia. This is mainly due to their flexible capabilities and features, which can support a wide range of communication applications. More specifically, drones can offer better coverage, better capacity, and a many-fold quality-of-service enhancement. Accordingly, recent communication technologies have been integrated with drones to support the unprecedented communication requirements of beyond fifth-generation (B5G) and 6G networks. Upon these bases, this paper sought to investigate the potential capabilities of multi-antenna drones in an uplink transmission cognitive radio (CR) indoor environment. With such an integrated system, a set of multiple-antenna drones communicates with a CR BS through the opportunistic utilization of the available channels without affecting the primary user's activities. In particular, this paper proposes an adaptive power channel assignment (APCA) protocol that aims to minimize the per-drone transmit power under a set of relevant CR-related and quality-of-service constraints. The constraints include the minimum rate requirements, the probability of success, per-antenna power, the minimum SNR, and relevant CR-related constraints. Furthermore, this paper attempts to mathematically prove that the formulated optimization problem is convex, thus, the optimal solution can be attained. Accordingly, the conventional convex algorithms are adopted to solve the problem and obtain the solution. The proposed APCA protocol is capable of selecting the channel that requires the minimum power. To investigate the performance of the proposed APCA protocol, we compare its performance against that of the conventional equal-power allocation. Simulation results reveal that the proposed APCA protocol significantly improves system performance in terms of the overall transmit power.

关键词： Drones Protocols Quality of service Uplink Resource management MIMO communication Indoor environment UAVs indoor propagation cognitive radio power-allocation channel assignment convex-optimization

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A NEW convex optimization-BASED TWO-PASS RATE CONTROL METHOD FOR OBJECT CODING IN AVS

A NEW CONVEX OPTIMIZATION-BASED TWO-PASS RATE CONTROL METHOD...

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IEEE Visual Communications and Image Processing Conference

作者： Yao, X. Z. Chan, S. C. Univ Hong Kong Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479961399

This paper proposed a new convex-optimization-based two-pass rate control method for object coding of China's audio video coding standard (AVS). The algorithm adopts a two-pass methodology to overcome the important interdependency problem between rate control and rate distortion optimization. An exponential model is used to describe the rate-distortion behavior of the codec so as to perform frame-level and object-level rate control under the two-pass framework. convex programming is utilized to solve for the resultant optimal bit allocation problem. Moreover, the region-of-interest (ROI) functionality is also realized at the object-level. The good performance and effectiveness of this method are illustrated using experimental results.

关键词： rate control AVS object-based coding rate-distortion optimization convex-optimization ROI

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LOW-RANKNESS OF COMPLEX-VALUED SPECTROGRAM AND ITS APPLICATION TO PHASE-AWARE AUDIO PROCESSING 44

LOW-RANKNESS OF COMPLEX-VALUED SPECTROGRAM AND ITS APPLICATI...

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Masuyama, Yoshiki Yatabe, Kohei Oikawa, Yasuhiro Waseda Univ Dept Intermedia Art & Sci Tokyo Japan

ISBN: (纸本)9781479981311

Low-rankness of amplitude spectrograms has been effectively utilized in audio signal processing methods including non-negative matrix factorization. However, such methods have a fundamental limitation owing to their amplitude-only treatment where the phase of the observed signal is utilized for resynthesizing the estimated signal. In order to address this limitation, we directly treat a complex-valued spectrogram and show a complex-valued spectrogram of a sum of sinusoids can be approximately low-rank by modifying its phase. For evaluating the applicability of the proposed low-rank representation, we further propose a convex prior emphasizing harmonic signals, and it is applied to audio denoising.

关键词： Instantaneous frequency phase derivative data-driven approach convex-optimization audio denoising

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