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IEEE Conference on Decision and control

作者： Leilei Cui Bo Pang Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA

Risk sensitivity is a fundamental aspect of biological motor control that accounts for both the expectation and variability of movement cost in the face of uncertainty. However, most computational models of biological motor control rely on model-based risk-sensitive optimal control, which requires an accurate internal representation in the central neural system to predict the outcomes of motor commands. In reality, the dynamics of human-environment interaction is too complex to be accurately modeled, and noise further complicates system identification. To address this issue, this paper proposes a novel risk-sensitive computational mechanism for biological motor control based on reinforcement learning (RL) and adaptive dynamic programming (ADP). The proposed ADP-based mechanism suggests that humans can directly learn an approximation of the risk-sensitive optimal feedback controller from noisy sensory data without the need for system identification. Numerical validation of the proposed mechanism is conducted on the arm-reaching task under divergent force field. The preliminary computational results align with the experimental observations from the past literature of computational neuroscience.

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Follow me droney! Will UWB technology do it right? 12

Follow me droney! Will UWB technology do it right?

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12th Asia Conference on Mechanical and Aerospace engineering, ACMAE 2021

作者： Hanzel, Krzysztof Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

Object tracking for consumer drones is currently a rapidly developing technology. Its implementation is currently carried out with the use of object-in-image detection, which often limits the latest possibilities of this technology. The disadvantage of such a solution is also the increase in energy demand and the need to provide additional computing power, or delays resulting from the transfer of this operation to the control device. The proposed solution to this problem in this article is the use of UWB (Ultra-wideband) technology, which is increasingly appearing in consumer devices. The possible yield related to the accuracy of determining the position of the object as well as the experimentally determined frequency of receiving information about the position was presented. Additional advantages, such as resistance to NLOS (non-line of sight) conditions, were also presented. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Embedded Multi-Port Converters for Synthesis and Enhancement of Hybrid-Clamped Multilevel Converters

Embedded Multi-Port Converters for Synthesis and Enhancement...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Yuzhuo Li Pasan Gunawardena Hao Tian Yunwei Li Department of Electrical and Computer Engineering University of Alberta Edmonton Canada School of Control Science and Engineering Shandong University Jinan China

Leveraging a number of inner capacitors/inductors, hybrid-clamped multilevel converters (MLCs) normally face great challenges among good performance (proper charge/discharge of these devices), high efficiency (maintaining low losses) and high power density (compact profile). On the other hand, these multiple-device energy-processing requirements have been addressed well in some promising multi-port converters (MPCs), and, therefore, inspire us to implement well-developed compact MPCs to facilitate the voltage/current level generation process in hybrid-clamped MLCs. Though recently, some researchers started to integrate active cells into hybrid-clamped MLCs and improve capacitor voltage control and generate extra output levels, the systematic synthesis method is still unclear and rarely discussed in the literature. To address this gap, we propose a systematic synthesis method for those hybrid clamped MLCs that can benefit from embedding well-developed MPCs. The approach can be applied for both voltage-source and current-source hybrid-clamped MLCs, covering emerging MLCs. In particular, we also derived and verified a new mixed hybrid MLC family through an emerging current-fed dual-input isolated multi-port converter. This topology features both current-source and voltage-source benefits and is ideal for future renewable generation integration.

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Neural Network Based Active Fault-tolerant control of Spacecraft via Prescribed Performance

Neural Network Based Active Fault-tolerant Control of Spacec...

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Asian control Conference

作者： Ze Yang Baoqing Yang Ruihang Ji Jie Ma Control and Simulation Center Harbin Institute of Technology Harbin China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This paper mainly studies the fault diagnosis and fault tolerance control of spacecraft attitude control system (ACS). Firstly, a novel model-free fault diagnosis network (FDN) is constructed based on Bi-LSTM neural networks. It uses only historical data to approximate the ACS mechanism, generate residuals, and combine adaptive thresholds to detect actuator and sensor faults. Secondly, to solve the problem of missing angular rate measurement caused by sensor faults, a fault-tolerant controller based on adaptive tracking differentiator (ATD) to generate virtual angular rate and have prescribed performance is designed to improve the robustness to faults and avoid performance degradation. Finally, simulation results are given to evaluate the effectiveness of the proposed scheme.

关键词： Fault diagnosis Space vehicles Fault tolerance Analytical models Actuators Attitude control Simulation

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Collaborative Satisfaction of Long-Term Spatial Constraints in Multi-Agent Systems: A Distributed Optimization Approach (extended version)

arXiv

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arXiv 2025年

作者： Mehdifar, Farhad Dhullipalla, Mani H. Bechlioulis, Charalampos P. Dimarogonas, Dimos V. The Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden The Division of Systems and Control The Department of Electrical and Computer Engineering University of Patras Patra Greece

This paper addresses the problem of collaboratively satisfying long-term spatial constraints in multi-agent systems. Each agent is subject to spatial constraints, expressed as inequalities, which may depend on the positions of other agents with whom they may or may not have direct communication. These constraints need to be satisfied asymptotically or after an unknown finite time. The agents’ objective is to collectively achieve a formation that fulfills all constraints. The problem is initially framed as a centralized unconstrained optimization, where the solution yields the optimal configuration by maximizing an objective function that reflects the degree of constraint satisfaction. This function encourages collaboration, ensuring agents help each other meet their constraints while fulfilling their own. When the constraints are infeasible, agents converge to a least-violating solution. A distributed consensus-based optimization scheme is then introduced, which approximates the centralized solution, leading to the development of distributed controllers for single-integrator agents. Finally, simulations validate the effectiveness of the proposed approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Multi agent systems

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Distributed Optimization via Gradient Descent with Event-Triggered Zooming Over Quantized Communication

Distributed Optimization via Gradient Descent with Event-Tri...

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IEEE Conference on Decision and control

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA US Department of Electrical and Computer Engineering School of Engineering University of Cyprus Aalto University Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technologyy Stockholm Sweden

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples.

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Investigation of Mode Transformation in Motor control System of Unmanned Aerial Vehicle Exposed to Intentional Electromagnetic Interference

Investigation of Mode Transformation in Motor Control System...

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Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Fei Fan Changdong Wang Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9784885523472

ISBN: (纸本)9798350349498

Susceptibility acts as a critical metric for assessing an electrical apparatus’s performance and reliability amidst the external electromagnetic environment, especially the intentional electromagnetic interference (IEMI). Given that the IEMI often invades electrical systems in common-mode (CM) and converts to the differential-mode (DM) signal to disrupt the normal operation of devices, investigating the mode transformation in the system under attack is pivotal for its susceptibility analysis. This paper first investigates the CM to DM conversion in the motor control system of the unmanned aerial vehicle (UAV) illuminated by an external IEMI. Experimental studies explore the influence of the distance between UAV and copper ground on mode conversion, revealing that adjusting the UAV’s landing gear height have the potential to enhance its susceptibility.

关键词： Performance evaluation Motor drives Electric potential Gears Electromagnetic interference RF signals Immunity testing

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Data-Efficient control Barrier Function Refinement

Data-Efficient Control Barrier Function Refinement

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American control Conference (ACC)

作者： Bolun Dai Heming Huang Prashanth Krishnamurthy Farshad Khorrami Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY

control barrier functions (CBFs) have been widely used for synthesizing controllers in safety-critical applications. When used as a safety filter, a CBF provides a simple and computationally efficient way to obtain safe controls from a possibly unsafe performance controller. Despite its conceptual simplicity, constructing a valid CBF is well known to be challenging, especially for high-relative degree systems under nonconvex constraints. Recently, work has been done to learn a valid CBF from data based on a handcrafted CBF (HCBF). Even though the HCBF gives a good initialization point, it still requires a large amount of data to train the CBF network. In this work, we propose a new method to learn more efficiently from the collected data through a novel prioritized data sampling strategy. A priority score is computed from the loss value of each data point. Then, a probability distribution based on the priority score of the data points is used to sample data and update the learned CBF. Using our proposed approach, we can learn a valid CBF that recovers a larger portion of the true safe set using a smaller amount of data. The effectiveness of our method is demonstrated in simulation on a two-link arm.

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Optimization of Cube Storage Warehouse Scheduling Using Genetic Algorithms

Optimization of Cube Storage Warehouse Scheduling Using Gene...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Won Yong Ha Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA

In this paper, a new scheduling model is presented to speed up the logistics processing in an automatic cube storage warehouse. Automated guided vehicles (AGV) are used to move all items in the warehouse according to the computer's instructions. The tasks to be performed by the AGV are optimally distributed using Genetic Algorithms (GA). The goal of our research is to optimize order scheduling in automatic warehouses to reduce human resources and lower the cost of logistics. The proposed GA's fitness function reflects removing the stacked bin, a cube storage warehouse characteristic, and getting the designated bin. Through extensive computer simulations, it is shown that the higher the generation of the GA we design, the lower the logistics processing time. As compared with other meta-heuristic optimization algorithms, our proposed GA algorithm demonstrates a maximum of 21% reduction in delivery time.

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Worst-Scenario Prediction for Field-to-Cable Coupling Under Continuous Intentional Electromagnetic Interference Attack

Worst-Scenario Prediction for Field-to-Cable Coupling Under ...

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Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Huamin Jie Eng Kee Chua Zhenyu Zhao Yongqi Chang Changdong Wang Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9784885523472

ISBN: (纸本)9798350349498

Studying intentional electromagnetic interference (IEMI) is crucial for safeguarding hardware safety, as it helps to address the deliberate disruption of electronic devices. The field-to-cable coupling serves as a prevalent attack mechanism of IEMI, precipitating unexpected failures of the device under test. Many efforts focus on the analysis of field-to-cable coupling under high-power electromagnetic pulse, but less target on the phenomenon illuminated with continuous waves. This paper proposes a novel method to predict the worst-case for field-tocable coupling under continuous IEMI attack. By employing the transmission line theory to characterize the cables and obtaining the impedance information of the devices at both ends of the cable, an analytical model is built for determining the terminal voltage frequency responses induced by IEMI. Subsequently, the sensitive frequency region of this cable-connected electrical system can be determined, facilitating purposive immunity improvements. Using an unmanned aerial vehicle (UAV) as an example, the analytical calculations are compared with the radiated susceptibility test. The results exhibit a good agreement with experiments and validate the effectiveness of the proposed method.

关键词： Couplings Analytical models Systematics Electromagnetic interference Voltage Immunity testing autonomous aerial vehicles

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