2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)最新文献_第2页

Event-triggered Control for Zero-sum Games Based on Critic-identifier Architecture with Particle Swarm Optimization 基于临界标识体系和粒子群优化的零和博弈事件触发控制

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642185

Weichen Luo, Mingming Liang, Derong Liu, Bo Zhao

引用次数: 0

UAV-Aided Secure Communication With Deployment Optimization and Cooperative Jamming 基于部署优化和协同干扰的无人机辅助安全通信

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642178

Hongbing Li, Juan Wu, L. Luo, Jiang Xiong

{"title":"UAV-Aided Secure Communication With Deployment Optimization and Cooperative Jamming","authors":"Hongbing Li, Juan Wu, L. Luo, Jiang Xiong","doi":"10.1109/ICICIP53388.2021.9642178","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642178","url":null,"abstract":"This paper investigates the jointly transmit power and unmanned aerial vehicle (UAV)/jammer deployment optimization problem for UAV enabled jammer-assisted secure communication systems, where a jammer is exploited to assist transmitting data from a source node to a legitimate destination node in the presence of multiple eavesdroppers. To increase the secrecy energy efficiency, which is defined as the achievable secrecy rate per energy consumption unit, we formulate a secrecy energy efficiency maximization problem by jointly optimizing the transmit power and UAV/jammer deployment. The resulting optimization problem is shown to be a non-convex and fractional optimization problem, which is challenging to solve. As such, we decompose the original problem into two sub-problems, and then, an efficient iterative algorithm is proposed by leveraging the extensive search method and Dinkelbach method in combination with successive convex approximation (SCA) techniques. Numerical simulation results show that the proposed scheme significantly improves the secrecy energy efficiency of the system.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125824120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering 基于动态时间翘曲和约束k-介质聚类的索引跟踪

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642192

Ran Zhang, Hongzong Li, Jun Wang

引用次数: 0

Pre-Optimization of High Dimensional Extreme Learning Machine with Cooperative Coevolution 基于协同进化的高维极限学习机预优化

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642187

J. Li, Chen Peng, Yuyan Wang, Yumin Yin, Bolin Liao

{"title":"Pre-Optimization of High Dimensional Extreme Learning Machine with Cooperative Coevolution","authors":"J. Li, Chen Peng, Yuyan Wang, Yumin Yin, Bolin Liao","doi":"10.1109/ICICIP53388.2021.9642187","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642187","url":null,"abstract":"Extreme Learning Machine (ELM) is a special type of single hidden layer feedforward neural network, which uses pseudo-inverse to compute weights of the output layer, and is often faster than the gradient-based methods. However, due to the random initialization of input weights and biases, the performance of this algorithm is not always stable, and is less effective in large-scale applications. Therefore, in this paper, based on an effective large-scale optimization algorithm, i.e., cooperative coevolutionary particle swarm optimization (CCPSO), an improved hybrid ELM learning algorithm, named CCPSO-ELM, is proposed, where the input weights and the hidden layer biases are optimized using CCPSO. Compared with the traditional ELM algorithm, as well as ELM optimized by traditional PSO, the CCPSO-ELM is more likely to avoid local optima, has smaller optimization errors, and is more robust against noises. The results are verified by experiments on two different types of problems, i.e., large-scale multivariate function approximation and pattern classification.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130475420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Positioning Control of Piezoelectric Stick-slip Actuators Based on Single Neuron Adaptive PID Algorithm 基于单神经元自适应PID算法的压电粘滑作动器定位控制

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642174

Yan Li, Yi Dong, Piao Fan

{"title":"Positioning Control of Piezoelectric Stick-slip Actuators Based on Single Neuron Adaptive PID Algorithm","authors":"Yan Li, Yi Dong, Piao Fan","doi":"10.1109/ICICIP53388.2021.9642174","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642174","url":null,"abstract":"Aiming at the problem of large positioning control error caused by the change of starting and ending position of piezoelectric stick-slip actuators, an adaptive PID full closed loop control method based on single neuron is proposed in this paper. Firstly, the dynamic model of the spring damping system is adopted, and the LuGre friction model is introduced to represent the stick-slip relationship between the drive block and the friction rod. Then, the adaptive PID full closed-loop control scheme based on single neuron and the principles of traditional PID algorithm and variable speed integral PID control algorithm are analyzed. The proposed control method is simulated and compared with the other two methods by MATLAB software. Finally, the effectiveness of the proposed method is verified by an experimental platform. The experimental results show that the maximum positioning errors of the proposed control method and the other two methods are 180 nm, 270 nm and 280 nm, respectively, when the desired position is 1 mm in low-frequency motion. Under the same experimental conditions, the proposed control scheme shows high control accuracy when the starting and ending position changes.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129297870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time-Varying Polar Decomposition by Continuous-Time Model and Discrete-Time Algorithm of Zeroing Neural Network Using Zhang Time Discretization (ZTD) 连续时间模型时变极分解和张时间离散化(ZTD)归零神经网络的离散时间算法

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642222

Zanyu Tang, Liangjie Ming, Yunong Zhang, Runhao Shi

引用次数: 0

Model Predictive Direct Power Control for PWM Rectifiers Based on Online Parameter Identification 基于在线参数辨识的PWM整流器模型预测直接功率控制

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642203

Yongzhi Wang, Dan Wang, Zhouhua Peng

引用次数: 2

Dual Noise-Suppressed ZNN with Predefined-Time Convergence and its Application in Matrix Inversion 具有预定义时间收敛的对偶噪声抑制ZNN及其在矩阵反演中的应用

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642164

Luyang Han, Bolin Liao, Yongjun He, Xiao Xiao

{"title":"Dual Noise-Suppressed ZNN with Predefined-Time Convergence and its Application in Matrix Inversion","authors":"Luyang Han, Bolin Liao, Yongjun He, Xiao Xiao","doi":"10.1109/ICICIP53388.2021.9642164","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642164","url":null,"abstract":"Original zeroing neural network (OZNN) can effectively solve the problem of matrix inversion. Generally, the problem of matrix inversion is solved in the noiseless environment. However, noises are common, OZNN can not solve the problem with harmonic noise interference. Therefore, the integrated enhanced zeroing neural network (IEZNN) is proposed to overcome this difficulty. IEZNN can deal with the harmonic noise interference problem when the time change slightly. But in the case of large amplitude or frequency, IEZNN has not strong ability to tolerate the noise and the convergence speed is relatively slow. Therefore, by adding a novel nonlinear activation for IEZNN, which also has the ability to suppress noise, a dual noise-suppressed ZNN (DNSZNN) is proposed to solve this problem. DNSZNN not only has good noise suppression characteristics, but also can converge in the predefined time. Finally, the experimental results demonstrate that the DNSZNN has the best robustness and convergence performance under the same external harmonic noise interference compared with the OZNN and the IEZNN.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122864073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Robot Manipulator Control via Solving Four-Layered Time-Variant Equations Including Linear, Nonlinear Equalities and Inequalities 求解包含线性、非线性等式和不等式的四层时变方程的机器人操纵器控制

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642176

Xinhui Zhu, Li Zhang, Yang Shi, Jing Wang, Jian Li

{"title":"Robot Manipulator Control via Solving Four-Layered Time-Variant Equations Including Linear, Nonlinear Equalities and Inequalities","authors":"Xinhui Zhu, Li Zhang, Yang Shi, Jing Wang, Jian Li","doi":"10.1109/ICICIP53388.2021.9642176","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642176","url":null,"abstract":"Robot manipulator control is a complicated multi-tasking problem in reality. It includes not only basic tracking task, but also additional tasks, such as conquering joint angle limits, posture control. However, most existing works only consider the goal of tracking and formulate it as single-layered time-variant problems, which leads to impracticality. In this work, robot manipulator control problem is formulated as four-layered time-variant equations including linear, nonlinear equalities and inequalities. Each layer formulates one subtask: The first layer of nonlinear equality describes basic tracking task based on forward kinematics; The second layer and third layer are inequalities, which describe joint angle upper and lower limits; The last layer is a linear equality with respect to joint angle velocity, which could be designed by user to describe other task, such as posture control. To solve this complicated four-layered time-variant problem, it is converted as single-layered equation based on the zeroing neural dynamics method. Then, continuous-time solution is proposed. Furthermore, discrete-time algorithm is proposed based on a third-order time-discretization formula and continuous-time solution. Numerical experiments illustrate the effectiveness and superiority compared to existing work.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129548755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Stabilization of Discrete-Time Hidden Semi-Markov Jump Systems with Time-varying Emission Probability 具有时变发射概率的离散隐半马尔可夫跳变系统的镇定

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642210

Shiyuan Fang, Hanzhi Li, Dacheng Pei, Meixi Wu, Yichong Sun, B. Cai

引用次数: 1