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IEEE Conference on Decision and control

作者： Mark Jeeninga Juan E. Machado Michele Cucuzzella Giacomo Como Jacquelien Scherpen Department of Automatic Control Lund University Lund Sweden Chair of Control Systems and Network Control Technology Faculty 3 Mechanical Engineering Electrical and Energy Systems Brandenburg University of Technology Cottbus - Senftenberg Cottbus Germany Department of Electrical Computer Science and Biomedical Engineering Univeristy of Pavia Pavia Italy Department of Mathematical Science “G.L. Lagrange” Politecnico di Torino Torino Italy Department of Automatic Control Lund University Faculty of Science and Engineering Jan C. Willems Center for Systems and Control ENTEG University of Groningen Groningen the Netherlands

In this paper, using tools from graph theory we provide verifiable necessary and sufficient conditions for the existence of a unique hydraulic equilibrium in district heating systems of meshed topology and containing multiple heat sources. Even though numerous publications have addressed the design of efficient algorithms for numerically finding hydraulic equilibria in the general context of water distribution networks, this is not the case for the analysis of existence and uniqueness. Moreover, most of the existing work dealing with these aspects exploit the equivalence between the nonlinear algebraic equations describing the hydraulic equilibria and the KKT conditions of a suitably defined nonlinear convex optimization problem. Differently, this paper proposes necessary and sufficient graph-theoretic conditions on the actuator placement for the existence and uniqueness of a hydraulic equilibrium, independent of the actuators' control objective. An example based on a representative district heating network is considered to illustrate the key aspects of our contribution, and an explicit formulation of the steady state solution is given for the case in which pressure drops through pipes are linear with respect to the flow rate.

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Experimental Comparison of H-Infinity Synthesis and Feedback Linearization on a MIMO Gimbal Example

Experimental Comparison of H-Infinity Synthesis and Feedback...

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control Technology and Applications (CCTA),

作者： Mert Özçelik Burak Kürkçü Zeki Yağız Bayraktaroğlu Control Systems Design Department Aselsan Inc. Ankara Turkey Department of Mechanical Engineering University of California Berkeley CA USA Department of Computer Engineering Hacettepe University Ankara Turkey Department of Mechanical Engineering Istanbul Technical University Istanbul Turkey

This study investigates the controller types and effects of the design techniques on gimbal stabilization. Since implementing the controllers and determining the system’s robustness is straightforward, the frequency domain design approaches are widely used with linear controllers in electro-optical inertial stabilized systems. Besides, the required system models can be obtained from experimental data easily. Nevertheless, the system model could change in the operational conditions. Therefore, nonlinear controllers are needed in this situation. In this investigation, we obtained a proper system model using system identification methods to design a mixed-sensitivity H ∞ controller. Then, we proposed an input-output feedback linearization controller with a linear quadratic regulator (LQR) based state feedback controller design to stabilize the 2 degrees of freedom (DOF) gimbal. Finally, we compared these two controllers regarding reference tracking, sensitivity function, and disturbance rejection performances on the experimental setup under 6 DOF disturbance profiles.

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Optimal solving of a scheduling problem using quantum annealing metaheuristics on the D-Wave quantum solver

TechRxiv

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TechRxiv 2023年

作者： Bożejko, Wojciech Klempous, Ryszard Pempera, Jaroslaw Rozenblit, Jerzy Smutnicki, Czeslaw Uchroński, Mariusz Wodecki, Mieczyslaw The Department of Control Systems and Mechatronics Wroclaw University of Science and Technology Poland University of Arizona United States Department of Computer Engineering Wroclaw University of Science and Technology Poland Department of Control Systems and Mechatronics Wroclaw University of Science and Technology Poland Department of Telecommunications and Teleinformatics Wroclaw University of Science and Technology Poland

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. The main disadvantage of calculations on quantum computers is their non-determinism. For optimization problems, of course, it is possible to get surprisingly good results but without a guarantee of the actual optimality of the result, i.e., an assurance that there exists no better solution which could potentially be found by the quantum machine. In this paper, we propose a novel approach that provides such a guarantee of optimality. We generate a solution that is optimal in the strict mathematical sense, without probabilistic considerations. To accomplish this, we use the D-Wave quantum machine working as a sampler implementing quantum annealing – an approach considered a hardware metaheuristic – to obtain upper and lower bounds on the value of the objective function of the problem under consideration. Then, we use the Branch and Bound scheme controlled by quantum annealing. This allows us to obtain very quickly – in constant time – the boundaries of the considered subproblems. Our approach is a combination of calculations realized on a quantum machine controlled by procedures implemented on a classical computer, allowing us to generate optimal solutions to the NP-hard problems of task scheduling on a single machine with a total weighted tardiness criterion. The proposed quantum algorithm shows a significant advantage over the classical CPU approach both in terms of calculation time and the number of generated solution tree nodes. © 2023, CC BY.

关键词： Quantum computers

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Deeploy: Enabling Energy-Efficient Deployment of Small Language Models On Heterogeneous Microcontrollers

arXiv

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arXiv 2024年

作者： Scherer, Moritz Macan, Luka Jung, Victor J.B. Wiese, Philip Bompani, Luca Burrello, Alessio Conti, Francesco Benini, Luca The Integrated Systems Laboratory ETH Zürich Zürich8092 Switzerland University of Bologna Bologna40126 Italy The Department of Control and Computer Engineering Politecnico di Torino Turin10129 Italy

With the rise of Embodied Foundation Models (EFMs), most notably Small Language Models (SLMs), adapting Transformers for edge applications has become a very active field of research. However, achieving end-to-end deployment of SLMs on microcontroller (MCU)-class chips without high-bandwidth off-chip main memory access is still an open challenge. In this paper, we demonstrate high-efficiency end-to-end SLM deployment on a multicore RISC-V (RV32) MCU augmented with ML instruction extensions and a hardware neural processing unit (NPU). To automate the exploration of the constrained, multi-dimensional memory vs. computation tradeoffs involved in aggressive SLM deployment on heterogeneous (multicore+NPU) resources, we introduce Deeploy, a novel Deep Neural Network (DNN) compiler, which generates highly-optimized C code requiring minimal runtime support. We demonstrate that Deeploy generates end-to-end code for executing SLMs, fully exploiting the RV32 cores' instruction extensions and the NPU: We achieve leading-edge energy and throughput of 490 µJ/Token, at 340 Token/s for an SLM trained on the TinyStories dataset, running for the first time on an MCU-class device without external memory. © 2024, CC BY-SA.

关键词： Microcontrollers

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement

arXiv

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arXiv 2024年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node’s local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3-bits). Our proposed algorithm respects the network’s bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm’s operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm’s unique characteristics. © 2024, CC BY.

关键词： Optimization algorithms

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear systems

arXiv

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arXiv 2023年

作者： Koelewijn, Patrick J.W. Singh, Rajiv Seiler, Peter Tóth, Roland Sioux Technologies B.V. Eindhoven Netherlands Control Systems Group Eindhoven University of Technology Eindhoven Netherlands The MathWorks Inc. Natick United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples. Copyright © 2023, The Authors. All rights reserved.

关键词： Nonlinear dynamical systems

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Resource-Efficient and Self-Adaptive Quantum Search in a Quantum-Classical Hybrid System

arXiv

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arXiv 2024年

作者： Jiang, Zihao Du, Zefan Ruan, Shaolun Chen, Juntao Wang, Yong Cheng, Long Buyya, Rajkumar Mao, Ying The Department of Computer and Information Science Fordham University New York City United States The School of Computing and Information Systems Singapore Management University Singapore The School of Control and Computer Engineering North China Electric Power University Beijing China The School of Computing and Information Systems The University of Melbourne Australia

Over the past decade, the rapid advancement of deep learning and big data applications has been driven by vast datasets and high-performance computing systems. However, as we approach the physical limits of semiconductor fabrication in the post-Moore's Law era, questions arise about the future of these applications. In parallel, quantum computing has made significant progress with the potential to break limits. Major companies like IBM, Google, and Microsoft provide access to noisy intermediate-scale quantum (NISQ) computers. Despite the theoretical promise of Shor's and Grover's algorithms, practical implementation on current quantum devices faces challenges, such as demanding additional resources and a high number of controlled operations. To tackle these challenges and optimize the utilization of limited onboard qubits, we introduce ReSaQuS, a resource-efficient index-value searching system within a quantum-classical hybrid framework. Building on Grover's algorithm, ReSaQuS employs an automatically managed iterative search approach. This method analyzes problem size, filters less probable data points, and progressively reduces the dataset with decreasing qubit requirements. Implemented using Qiskit and evaluated through extensive experiments, ReSaQuS has demonstrated a substantial reduction, up to 86.36% in cumulative qubit consumption and 72.72% in active periods, reinforcing its potential in optimizing quantum computing application deployment. © 2024, CC BY.

关键词： Hybrid systems

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Trust Establishment for the Role-Based Collaborative Multi-Robot systems

Trust Establishment for the Role-Based Collaborative Multi-R...

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IEEE International Conference on systems, Man and Cybernetics

作者： Behzad Akbari Haibin Zhu Ya-Jun Pan Department of Mechanical Engineering Advanced Control and Mechatronics Laboratory Dalhousie University Halifax NS Canada Department of Computer Science and Mathematics Collaborative Systems Laboratory Nipissing University NorthBay ON Canada

Trust evaluation and trust establishment play crucial roles in the management of trust within a multi-agent system. When it comes to collaboration systems, trust becomes directly linked to the specific roles performed by agents. The Role-Based Collaboration (RBC) methodology serves as a framework for assigning roles that facilitate agent collaboration. Within this context, the behavior of an agent with respect to a role is referred to as a process role. This research paper introduces a role engine that incorporates a trust establishment algorithm aimed at identifying optimal and reliable process roles. In our study, we define trust as a continuous value ranging from 0 to 1. To optimize trustworthy process roles, we have developed a consensus-based Gaussian Process Factor Graph (GPFG) tool. Our simulations and experiments validate the feasibility and efficiency of our proposed approach with autonomous robots in unsignalized intersections and narrow hallways.

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Research on Selective Harmonic Elimination Pulse Width Modulation of Three-Level NPC Inverter Based on Adaptive Restart Genetic Algorithm

Research on Selective Harmonic Elimination Pulse Width Modul...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Tao Jing Yuehua Liang A. S. Maklakov A. A. Nikolaev School of Computer and Information Engineering Henan University Kaifeng Henan China Zhejiang Entive Smart Kitchen Appliance Co. Ltd. Shengzhou Zhejiang China Department of Automation and Control Moscow Polytechnic University Moscow Russia Department of Automated Electric Drive and Mechatronics Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The harmonic elimination task of three-level neutral point clamped (3L-NPC) inverters is related to a complicated engineering optimization problem, which mainly involves constrained nonlinear transcendental equations with multiple solutions. In order to solve the problems of difficult initial value determination, slow convergence rates and susceptibility to local optima trapping in the process of using traditional numerical algorithms, This paper introduces a novel selective harmonic elimination pulse width modulation (SHEPWM) framework, enhanced by an adaptive restart genetic algorithm, to address the limitations of conventional optimization methods. By introducing the adaptive restart mechanism, the performance and robustness of the solution algorithm can be improved, so as to circumvent entrapment in local optima and secure the global optimum across the entire solution space. The simulation results show that there are divergent trends in the switching angles and the total harmonic distortion (THD) values of the output voltage obtained by the proposed method, but all of them can effectively eliminate the specified low-order harmonics. These findings verifies the practical applicability and solution diversity of the proposed method, as well as provides new ideas and methods for solving optimization problems in other engineering fields.

关键词： Total harmonic distortion Voltage Switches Pulse width modulation Harmonic analysis Inverters Robustness systems simulation Genetic algorithms Convergence

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Tight Collision Probability for UAV Motion Planning in Uncertain Environment

arXiv

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arXiv 2023年

作者： Liu, Tianyu Zhang, Fu Gao, Fei Pan, Jia Department of Mechanical Engineering The University of Hong Kong Hong Kong Institute of Cyber-Systems and Control Zhejiang University China Department of Computer Science The University of Hong Kong Hong Kong

Operating unmanned aerial vehicles (UAVs) in complex environments that feature dynamic obstacles and external disturbances poses significant challenges, primarily due to the inherent uncertainty in such scenarios. Additionally, inaccurate robot localization and modeling errors further exacerbate these challenges. Recent research on UAV motion planning in static environments has been unable to cope with the rapidly changing surroundings, resulting in trajectories that may not be feasible. Moreover, previous approaches that have addressed dynamic obstacles or external disturbances in isolation are insufficient to handle the complexities of such environments. This paper proposes a reliable motion planning framework for UAVs, integrating various uncertainties into a chance constraint that characterizes the uncertainty in a probabilistic manner. The chance constraint provides a probabilistic safety certificate by calculating the collision probability between the robot's Gaussian-distributed forward reachable set and states of obstacles. To reduce the conservatism of the planned trajectory, we propose a tight upper bound of the collision probability and evaluate it both exactly and approximately. The approximated solution is used to generate motion primitives as a reference trajectory, while the exact solution is leveraged to iteratively optimize the trajectory for better results. Our method is thoroughly tested in simulation and real-world experiments, verifying its reliability and effectiveness in uncertain environments. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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