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2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)最新文献

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Event-Triggered Based Adaptive Dynamic Surface Control for a Class of Quadrotor UAVs* 一类四旋翼无人机基于事件触发的自适应动态表面控制*
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642199
Erzhen Shang, Yang Gao, Yang Li, Bo Yu, Jiasen Sun, Yilin Jia, Cheng Zhong, Guoqiang Zhu, Xiuyu Zhang
A hybrid adaptive control scheme for quadrotor control system based on event-triggered mechanism is proposed for the trajectory tracking control problem of quadrotor UAV. The high-gain state observer is constructed to estimate the unmeasurable states, then the adaptive radial basis function neural networks (RBFNNs) dynamic surface control strategy is designed to achieve precise tracking control. The event-triggered mechanism is introduced, which is effective reduces the update frequency of the system control signal. The simulation results show that the proposed control scheme can achieve more accurate tracking performance than the traditional backstepping sliding mode control (BSMC) scheme without sacrificing the tracking performance of the control system.
针对四旋翼无人机的轨迹跟踪控制问题,提出了一种基于事件触发机制的四旋翼控制系统混合自适应控制方案。构造高增益状态观测器估计不可测状态,设计自适应径向基函数神经网络(RBFNNs)动态面控制策略实现精确跟踪控制。引入事件触发机制,有效地降低了系统控制信号的更新频率。仿真结果表明,在不牺牲控制系统跟踪性能的前提下,所提出的控制方案比传统的反步滑模控制(BSMC)方案具有更精确的跟踪性能。
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引用次数: 0
On Pinning Synchronization of An Array of Linearly Coupled Dynamical Network 线性耦合动态网络阵列的钉住同步
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642181
Wudai Liao, Haoran Chen, Jinhuan Chen, Chaochuan Zhang, Xiufen Xin, Xiaobo Han
In this paper, we investigate the exponential synchronization problem for a class of linear coupled dynamic complex networks. In a complex network system, it is difficult to achieve synchronization only by the coupling of the network itself without the controller. Based on the linear feedback method, this paper proposes a strategy to achieve global exponential stability of the general complex dynamic network in the target state by means of pinning control. Some nodes of the complex network are controlled to achieve the same state of all nodes of the complex network. In addition, the conditions of global exponential synchronization of the complex network are given, and the strict proof is given by using Lyapunov stability theory. Numerical analysis and simulation results are presented to demonstrate effectiveness of the criterion.
研究了一类线性耦合动态复杂网络的指数同步问题。在复杂的网络系统中,仅靠网络本身的耦合而不加控制器是很难实现同步的。在线性反馈方法的基础上,提出了一种用钉住控制的方法实现一般复杂动态网络在目标状态下全局指数稳定的策略。对复杂网络中的部分节点进行控制,使其所有节点的状态保持一致。此外,给出了复杂网络全局指数同步的条件,并利用Lyapunov稳定性理论给出了严格的证明。数值分析和仿真结果验证了该准则的有效性。
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引用次数: 0
Optimal Control Problem for Linear System Based on Adaptive Dynamics Programming and Gradient Descent Method 基于自适应动态规划和梯度下降法的线性系统最优控制问题
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642163
Yanzhi Wu, Lu Liu
The optimal control problem is investigated for linear system with unknown dynamics in this paper. For linear system, adaptive dynamic programming (ADP) techniques and gradient descent method are combined to obtain an approximated optimal controller. We design ADP algorithms to calculate the system matrices of the linear system. Based on these calculated system matrices, a gradient descent algorithm is utilized to approximate the optimal feedback control gain. Finally, a numerical example is included for illustration.
研究了一类未知动态线性系统的最优控制问题。对于线性系统,将自适应动态规划(ADP)技术与梯度下降法相结合,得到近似最优控制器。我们设计了ADP算法来计算线性系统的系统矩阵。基于计算得到的系统矩阵,利用梯度下降算法逼近最优反馈控制增益。最后,给出了一个数值算例。
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引用次数: 0
Adaptive Discrete Time Dynamic Surface Control for Aircraft Flight Path Angle with Unknown Disturbances 未知干扰下飞机航迹角的自适应离散时间动态曲面控制
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642183
Huan He, Xiaodi Xu, Yilin Jia, Cheng Zhong, Guoqiang Zhu, Xiuyu Zhang
Aiming at the problem of tracking control system of the aircraft flight path angle, an adaptive discrete time dynamic surface control algorithm is proposed. Firstly, introducing the concept of discrete time system, the sampling signal form used is easy to suppress noise, and the impact of delay on the system is reduced through sampling. Afterwards, the dynamic surface control and the first-order digital low pass filter is introduced which making both controller and parameters easier and avoiding differential explosion in traditional backstepping method. Furthermorethe RBF Neural Network is introduced to approximate the unknown parameters and uncertain items in the system and the unknown interference part of the externa, which reduces the requirements on the system and structure. By using the Lyapunov function theory, it is proved that the closed-loop system is semi-globally ultimately uniformly bounded. Finally, simulation verification is performed and the results show that the proposed control algorithm can not only make the flight path angle track the reference trajectory, but also has a certain degree of robustness to unknown system parameters and unknown external interference.
针对飞机航迹角跟踪控制系统存在的问题,提出了一种自适应离散时间动态面控制算法。首先,引入离散时间系统的概念,采用易于抑制噪声的采样信号形式,通过采样降低了时延对系统的影响。然后,引入了动态曲面控制和一阶数字低通滤波器,使控制器和参数都变得简单,避免了传统反演方法的差分爆炸。引入RBF神经网络对系统中的未知参数和不确定项以及外部未知干扰部分进行逼近,降低了对系统和结构的要求。利用李雅普诺夫函数理论,证明了闭环系统是半全局最终一致有界的。最后进行了仿真验证,结果表明所提出的控制算法不仅能使航迹角跟踪参考轨迹,而且对未知系统参数和未知外部干扰具有一定的鲁棒性。
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引用次数: 0
Learning Representation with Q-irrelevance Abstraction for Reinforcement Learning 基于q -不相关抽象的强化学习表示
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642160
Shuai Hao, Luntong Li, Minsong Liu, Yuanheng Zhu, Dongbin Zhao
In order to improve the performance of deep reinforcement learning (DRL) algorithm in high-dimensional observation environments, we propose a new auxiliary task to learn representations to aggregate task-relevant information of observations. Inspired by Q-irrelevance abstraction, our auxiliary task trains a deep Q-network (DQN) to predict the true Q value distribution over all discrete actions. Then we use the output of DQN to train the encoder to discriminate states with different Q values. The encoder is used as the representation of proximal policy optimization (PPO). The resulting algorithm is called as Q-irrelevance Abstraction for Reinforcement Learning (QIARL). After training, the encoder can aggregate states with similar Q value distributions together for any policy and any action. Thus the encoder can encode the important information that is relevant to reinforcement learning task. We test QIARL in four Procgen environments compare with PPO, A2C and Rainbow. The experimental results show QIARL outperforms the other three algorithms.
为了提高深度强化学习(DRL)算法在高维观测环境中的性能,我们提出了一种新的辅助任务来学习表征,以聚合观测的任务相关信息。受Q不相关抽象的启发,我们的辅助任务训练一个深度Q网络(DQN)来预测所有离散动作的真实Q值分布。然后我们使用DQN的输出来训练编码器区分不同Q值的状态。编码器被用作近端策略优化(PPO)的表示。由此产生的算法被称为q -不相关抽象强化学习(QIARL)。经过训练后,编码器可以将具有相似Q值分布的状态聚合在一起,用于任何策略和任何动作。这样编码器就可以对与强化学习任务相关的重要信息进行编码。我们在四个Procgen环境中对QIARL进行了测试,并与PPO、A2C和Rainbow进行了比较。实验结果表明,QIARL算法优于其他三种算法。
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引用次数: 2
An Improved Multiple Sound Source Localization Method Using a Uniform Concentric Circular Microphone Array 一种改进的均匀同心圆形传声器阵列多声源定位方法
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642218
Yuting Zhang, Hongwei Zhang, Honghai Liu
Sound source localization finds its applications in various scenarios, such as video conferences, human-robot interaction, intelligent robotics, transportation, fault detection and medical treatment. To overcome the conflict of low frequency resolution issue for the microphone array with small aperture and spatial aliasing issue caused by the microphone array with large aperture, this paper adopts a uniform concentric circular array topology and proposes an improved method based on delay and sum beamforming algorithm to realize the multiple sound sources localization. Experimental results illustrate the effectiveness of the proposed algorithm.
声源定位应用于视频会议、人机交互、智能机器人、交通运输、故障检测、医疗等多种场景。为了克服小孔径传声器阵列低频分辨率问题与大孔径传声器阵列空间混叠问题的冲突,本文采用均匀同心圆形阵列拓扑,提出了一种基于延迟和和波束形成算法的改进方法,实现多声源定位。实验结果表明了该算法的有效性。
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引用次数: 0
Advanced Discrete Generalized-Neurodynamic Model Applied to Solve Discrete Time-Variant Augmented Sylvester Equation with Perturbation Suppression 应用先进的离散广义神经动力学模型求解具有扰动抑制的离散时变增广Sylvester方程
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642177
Yang Shi, Guoqian Liu, Jie Wang, Jiazheng Zhang, Jian Li, Dimitrios Gerontitis
In this paper, an advanced discrete generalized-neurodynamic (A-DGND) model is proposed to solve discrete time-variant augmented Sylvester equation (DTV-ASME) with perturbation suppression. Firstly, we present the discrete time-variant augmented Sylvester matrix equation that can be transformed into a simple matrix-vector problem. Secondly, in the continuous-time environment, for solving the continuous time-variant augmented Sylvester matrix equation (CTV-ASME), an advanced continuous generalized-neurodynamic (A-CGND) model is obtained. Then, based on the four-step discretization formula, an A-DGND model is proposed by discretizing the A-CGND model for solving DTV-ASME with perturbation suppression. Finally, according to the numerical experiment results, the effectiveness and robustness of A-DGND model for solving DTVASME are verified.
本文提出了一种先进的离散广义神经动力学(A-DGND)模型来求解具有扰动抑制的离散时变增广Sylvester方程(ddv - asme)。首先,我们提出了离散时变增广Sylvester矩阵方程,它可以转化为一个简单的矩阵-向量问题。其次,在连续时间环境下,针对连续时变增广Sylvester矩阵方程(CTV-ASME),得到了一种先进的连续广义神经动力学(A-CGND)模型。然后,在四步离散化公式的基础上,通过离散化A-CGND模型,提出了具有摄动抑制的ddv - asme的A-DGND模型。最后,根据数值实验结果,验证了A-DGND模型求解DTVASME的有效性和鲁棒性。
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引用次数: 0
Design and Implementation of Braking Control for Hybrid Electric Vehicles 混合动力汽车制动控制的设计与实现
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642191
Peng Mei, Shichun Yang, Bing-rui Xu, Kangkang Sun, Chao Zhang
Regenerative braking can effectively improve fuel consumption for hybrid electric vehicles, and it is a critical technology related to the multi-objective control situation, which is used to realize vehicle braking safety, the energy of braking recovery, and braking stability. Therefore, this paper put forward an adaptive fuzzy control (AFC) method for energy recovery in electric vehicles, mainly for a regenerative braking system. In particular, adaptive control is designed for estimating the road condition. The fuzzy logic control is proposed based on the braking strength of the vehicle, the battery state of charge, and vehicle speed. Combine the mentioned methods, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.
再生制动可以有效提高混合动力汽车的油耗,是一项涉及多目标控制情况的关键技术,用于实现车辆制动安全、制动能量回收和制动稳定性。因此,本文提出了一种用于电动汽车能量回收的自适应模糊控制(AFC)方法,主要针对再生制动系统。特别针对道路状况的估计设计了自适应控制。提出了基于车辆制动强度、电池充电状态和车速的模糊逻辑控制方法。结合上述方法,在Simulink环境下建立了电动汽车模型,验证了所提控制算法的适用性。
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引用次数: 0
Controller Design for Switched LPV Systems with Hidden semi-Markov Mode Switching 隐藏半马尔可夫模式切换切换LPV系统的控制器设计
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642209
Jianfeng Wang, Zhirun Chen, Yichong Sun, Zhan Li, Dacheng Pei, B. Cai
This paper is concerned with issue of stability analysis and control synthesis for a class of switched LPV systems with stochastic mode switching. The stochastic switching process is further regarded as hidden semi-Markov switching by using concepts of semi-Markov kernel and emission probability. With the construction of a novel Lyapunov function that depends on accessible-mode, parameter as well as elapsed time, the mean-square stability (MSS) criteria are developed for the closed-loop system with the usage of designed controller. Numerically testable stability criteria are established in sense of MSS by introducing the upper bound sojourn time and some mathematical techniques. The theoretical results are testified by a numerical example to demonstrate the effectiveness of the designed stabilizing controller.
研究了一类具有随机模态切换的开关LPV系统的稳定性分析与控制综合问题。利用半马尔可夫核和发射概率的概念,将随机切换过程进一步视为隐半马尔可夫切换。通过构造一个依赖于可达模式、参数和运行时间的新型李雅普诺夫函数,利用所设计的控制器建立了闭环系统的均方稳定性准则。通过引入上界逗留时间和一些数学技巧,建立了MSS意义下的数值可测试稳定性判据。通过数值算例验证了理论结果,验证了所设计的稳定控制器的有效性。
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引用次数: 1
Time-Variant and Time-Invariant Matrix Inequations of Zhang Equivalency Besides Matrix Equations 除矩阵方程外,张等价的时变和定常矩阵不等式
Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642205
Yunong Zhang, Jianzhen Xiao
Via the paper, the ZE (Zhang equivalency) concept is firstly revisited, and then, on the basis of ZE, equation-type ZE and inequation-type ZE are further showed and discussed. By utilizing ZND (i.e., Zhang neural dynamics) method, we present the general expressions of equation-type ZE, and apply them in seven types of time-variant matrix situations. Then, we further discuss the inequation-type ZE and present the order-l (i.e, 01), order-2 (i.e, 02), and order-3 (i.e, 03) general expressions of inequation-type ZE. By utilizing these expressions, we hence propose the 01, 02, and 03 expressions of inequation-type ZE in six types of matrix situations for handling corresponding time-variant matrix inequation problems.
本文首先对张等价(ZE)概念进行了重新审视,并在此基础上对方程型ZE和不等式型ZE进行了进一步的展示和讨论。利用ZND(即张神经动力学)方法,给出了方程型ZE的一般表达式,并将其应用于7类时变矩阵情况。然后,我们进一步讨论了不等式型ZE,并给出了不等式型ZE的阶1(即01)、阶2(即02)和阶3(即03)的一般表达式。利用这些表达式,我们提出了6类矩阵情况下不等式型ZE的01、02和03表达式,用于处理相应的时变矩阵不等式问题。
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引用次数: 1
期刊
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)
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