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20th IEEE International Conference on Mechatronics and automation, ICMA 2023

作者： Zheng, Xiao-Yi Yan, Hong-Sen Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China

ISBN: (纸本)9798350320831

For stochastic nonlinear systems with input saturation, few of the existing control methods use a suitable auxiliary system to solve input saturation problem, and most of them are for deterministic systems. In this study, according to the backstepping approach and the Lyapunov stability theorem, utilizing multi-dimensional Taylor network (MTN), an adaptive controller is presented to secure that all closed-loop signals keep bounded in probability, in which MTN is implemented to approach the uncertain function during the controller design. Moreover, the impact raised by input saturation is mitigated by designing an appropriate auxiliary system, in which the order of the auxiliary system is the same as that of the controlled system. Furthermore, unlike the majority of prior findings, the final output signal could be constrained in a mean quartic sense by an explicit expression of the input saturation error (the difference between the control signal and the saturation input) and the parameters used for design. Finally, the efficiency of the suggested control methodology is confirmed by providing an example. © 2023 IEEE.

关键词： Stochastic systems

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LSTM-TD3-based control for delayed drone combat strategies 19th

LSTM-TD3-based control for delayed drone combat strategies

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19th Chinese Intelligent systems Conference, CISC 2023

作者： Ji, Bingyu Wang, Jun Zhang, Hailin Zhang, Ya School of Automation Southeast University Nanjing210096 China Key Laboratory Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789819968817

Reinforcement learning has made great achievements in the field of game confrontation, and military rendition intelligence is also imminent. In this paper, we propose a game confrontation game model based on LSTM and deep reinforcement learning for the red and blue sides of the drones in the delayed *** action buffer pair is added to the original battlefield environment to create a large latency environment, a TD3 algorithm is designed to join LSTM to predict the state trend, and a historical data pool is built using PER. The training results in the simulation platform show that the model has a significant improvement in effectiveness in the large latency environment, with a 0.22 improvement in battle damage ratio and a 34.76% improvement in win rate over the original model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Reinforcement learning

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Efficient temporal alignment network for smoke detection

Efficient temporal alignment network for smoke detection

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2023 Jiangsu Annual Conference on automation, JACA 2023

作者： Li, Weitai Lu, Xiaobo Cao, Yichao School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781839539848

Smoke is a distinctive feature of pre-fire combustion and it is critical to prevent fires by detecting smoke. Previous work has demonstrated that deep learning methods have a wide range of applications in the field of smoke detection. However, existing methods still have some problems, i.e., it is difficult to balance the relationship between accuracy and speed. In order to solve the existing problems, we proposed Efficient Temporal Alignment Network (ETAN) for Video Smoke Detection. Feature Aggregation Module (FAM) was designed to extract the dynamic features between frames, and we proposed Recursive Memory Feature Update (RMFU) module to maintain the features of past frames and fuse the current features to boost detection performance. Finally, experiments demonstrated that the proposed method improved about 3.8 mAP compared with base detector with little increase in the number of parameters, and outperformed all the single-frame detection methods with the same amount of parameters. Compared with video smoke detection methods, the detection achieved close to the same accuracy while 6.1 times faster than multi-frame methods. © The Institution of engineering & Technology 2023.

关键词： Smoke

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Non-Smooth Speed control of Switched Reluctance Motor Based on Generalized Proportional Integral Observer 42

Non-Smooth Speed Control of Switched Reluctance Motor Based ...

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42nd Chinese control Conference, CCC 2023

作者： Yin, Qingzhao Tian, Zheng Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789887581543

This paper investigates the speed regulation control of switched reluctance motor (SRM) systems. To improve the antidisturbance performance of SRM, a composite non-smooth control strategy is proposed. First, the structure of SRM is analyzed, and a simplified nonlinear model is obtained based on a segmented representation of the varying phase inductance. A virtual control function is introduced to represent the nonlinear part of the torque equation, whose inverse function is cascaded to linearized the nonlinear model. Second, a generalized proportional integral observer (GPIO) is constructed to estimate the lumped disturbance of the system, which is used for feedforward compensation design. Finally, a composite speed controller is designed based on a combination of finite time proportional feedback and feed-forward compensation based on GPIO (FTP+GPIO). The speed error closed-loop system can be regarded as a first-order finite time control system with bounded disturbances. Strict analysis shows that the proposed scheme can improve the anti-disturbance performance of the closed-loop system. The effectiveness of the proposed method is verified by simulation results. Moreover, it is compared with proportional feedback combining feed-forward compensation (P+GPIO) method and proportional integral (PI) control method. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Closed loop systems

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Anti-disturbance Low Speed Regulation control of PMSMs Using Modified Extended State Observer Based on Rotor Position

Anti-disturbance Low Speed Regulation Control of PMSMs Using...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. However, the position signal of encoder with quantization errors results in crawling and shaking at low speeds. Considering quantization error as a type of noise limited their own accuracy, the environmental influences like mechanical vibration and electromagnetic interference also lead to noise in rotor position. The modified ESO method incorporated a Kalman filter (KF) is proposed to reduce the negative impact of noise. Due to differential amplification noise, the position signal is used instead of traditional speed signal for observers design because of its undesirable characteristics at low speed. The modified ESO based on rotor position is used to estimate both speed signal and disturbances to enhance the low speed performance in the presence of disturabances and measurement noise. The friction model is embedded for above integrated structure due to its nonliearity at low speeds. Considering the negative effects of measurement noise and disturbance at low speeds, it has verified that the proposed algorithm has better dynamic and steady-state performance and anti-disturbance ability through simulation. © The Institution of engineering & Technology 2024.

关键词： State estimation

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Self-supervised Depth Completion with Adaptive Online Adaptation 23

Self-supervised Depth Completion with Adaptive Online Adapta...

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7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023

作者： Chen, Yang Tan, Yang Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450398633

Although depth completion has achieved remarkable performance relying on deep learning in recent years, these models tend to suffer a performance degradation when exposed to new environments. Online adaptation, where the model is trained in a self-supervised manner during testing, seems a promising technique to alleviate the drop. However, continuous online adaptation may cause the model to over-adapt and miss the optimal parameters, resulting in oscillation or even degradation of the model performance, in addition to wasting computational resources. Therefore, this paper proposes an adaptive online adaptation framework to make model adaptively trigger online adaptation when encountering novel environments and stop adaptation when model has adapted to the current environment. In detail, we design a trigger to detect the familiarity of model to the current scenario based on image similarity and then launch online adaptation when the scenario is novel. Besides, we elaborate a stopper to monitor the error between prediction and depth input and convert online adaptation to inference when online adaptation does not bring improvement for model. Experimental results demonstrate that our method improves the accuracy of model prediction and increases average running speed of the model on each frame in online adaptation. © 2023 ACM.

关键词： Deep learning

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An optimal trajectory planning algorithm for T-shaped acceleration curve with non-zero acceleration at the beginning and end

An optimal trajectory planning algorithm for T-shaped accele...

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2022 Chinese automation Congress, CAC 2022

作者： Luo, Yongxu Yahui, Gan Xianzhong, Dai SE University Key Laboratorty of Measurement and Control of Complex Systems of Engineering Ministry School of Automation NanJing China

ISBN: (纸本)9781665465335

In order to solve the problem that T-type trajectory planning curve can not completely replace polynomial trajectory planning,this paper proposes an S-type programming algorithm based on the optimization algorithm with T-type acceleration. The algorithm solves the complex and cumbersome problem of time planning of T-shaped acceleration and deceleration curve with non-zero acceleration and velocity at the beginning and end. Taking into account the characteristics of fast acceleration of trajectory planning curve, it can not only solve the case where the initial and end velocities are not zero, but also solve the case where the initial and end accelerations are not zero. The algorithm is based on the analysis of the characteristics of acceleration stage, constant speed stage and deceleration stage. When the highest speed of the curve is determined, the time of all speed segments is also determined. The concept of maximum reachable speed of trajectory is proposed. The complex multivariate nonlinear programming is transformed into a single convex function. The algorithm is simplified by using the symmetry of the variation forms in acceleration stage and deceleration stage. The maximum achievable velocity is solved by dichotomy, Newton iterative method and gradient descent method. The experiment shows that the solving efficiency of Newton iterative method is 40% higher than that of dichotomy method. Compared with the quintic polynomial programming algorithm, the overall planning time is reduced by 9.6% and the tracking error is reduced by 15.9%. © 2022 IEEE.

关键词： Acceleration

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Distributed Asymptotic Consensus in Directed Networks of Nonaffine systems With Nonvanishing Disturbance

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1133-1140页

作者： Qingling Wang Changyin Sun School of Automation Southeast UniversityNanjing 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096China

In this paper the distributed asymptotic consensus problem is addressed for a group of high-order nonaffine agents with uncertain dynamics,nonvanishing disturbances and unknown control directions under directed networks.A class of auxiliary variables are first introduced which forms second-order filters and induces all measurable signals of agents’*** view of this property,a distributed robust integral of the sign of the error(DRISE)design combined with the Nussbaum-type function is presented that guarantees not only the desired asymptotic consensus,but also the uniform boundedness of all closed-loop *** with the traditional sliding mode control(SMC)technique,the main feature of our approach is that the integral operation in the proposed control algorithm is designed to be adopted in a continuous manner and ensures less chattering *** results for a group of Duffing-Holmes chaotic systems are employed to verify our theoretical analysis.

关键词： Asymptotic consensus nonaffine systems nonvanishing disturbance Nussbaum-type functions unknown control directions

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Adaptive Augmented Kalman Filter-Based control for Electronic Throttle systems with Disturbances and Noises 42

Adaptive Augmented Kalman Filter-Based Control for Electroni...

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42nd Chinese control Conference, CCC 2023

作者： Li, Wen Su, Jinya Li, Shihua School of Automation Southeast University Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

In this study, we investigate the control problem of electronic throttle systems in the presence of practical challenges such as disturbances and measurement noises. To address these challenges, we propose an adaptive augmented Kalman filter (AAKF) based control approach that combines the strengths of extended state observer in disturbance estimation and adaptive Kalman fil-ter in adaptive noise filtering. The outputs of AAKF are integrated into the Backstepping control design, resulting in a composite control that concurrently achieves fast disturbance rejection and noise suppression. We conduct a comparative simulation study against conventional methods without adaptive filtering to validate the effectiveness of the proposed AAKF-based control strat-egy, which exhibits superior position control accuracy and disturbance attenuation performance. We envision that our proposed control strategy will contribute to improving vehicle power, fuel economy, and emission performance. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Adaptive filtering

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Fixed-Time Adaptive Tracking Event-Based control for Uncertain Stochastic Nonlinear systems With Output Constraints

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International Journal of Robust and Nonlinear control 2025年第0期

作者： Wang, Kun Xie, Liping Yuan, Yixuan Zhang, Kanjian Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

This paper focuses on an adaptive fixed-time tracking control problem for nonstrict-feedback stochastic nonlinear systems with unknown control coefficients and output constraints. To overcome this problem, this article introduces a unified system transformation function to facilitate the transition of the system from constrained to unconstrained states. Subsequently, a fuzzy approximation principle is utilized for handling unknown terms in the transformed system, while Nussbaum functions are employed to manage unknown control directions. Then, combined with the backstepping technique, an adaptive fixed-time tracking controller is designed with an event-triggered mechanism, which not only achieves the convergence of tracking errors within a limited time independent of initial states, but also conserves resources. Under the proposed tracking controller, practical fixed-time stability can be ensured for the closed-loop system. Finally, two simulation examples demonstrate the efficacy of the proposed scheme. © 2025 John Wiley & Sons Ltd.

关键词： Stochastic systems

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