Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388179
Yuxin Wei, Guoping Liu
This paper investigates the problem of consensus tracking for discrete-time networked multi-agent systems (N-MASs), where information is exchanged through a network with a constant communication delay. Based on output feedback, observer and the networked predictive control scheme, a novel consensus protocol is proposed to compensate for the communication delay actively and follow the track of the external reference. For NMASs with a directed topology and a constant delay, a necessary and sufficient condition for the consensus is given. An numerical simulation is given to validate the theoretical results.
{"title":"Consensus tracking control of leader-follower multi-agent systems based on the networked predictive control scheme","authors":"Yuxin Wei, Guoping Liu","doi":"10.1109/ICICIP.2015.7388179","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388179","url":null,"abstract":"This paper investigates the problem of consensus tracking for discrete-time networked multi-agent systems (N-MASs), where information is exchanged through a network with a constant communication delay. Based on output feedback, observer and the networked predictive control scheme, a novel consensus protocol is proposed to compensate for the communication delay actively and follow the track of the external reference. For NMASs with a directed topology and a constant delay, a necessary and sufficient condition for the consensus is given. An numerical simulation is given to validate the theoretical results.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126755378","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388161
Lingfeng Xu, Chuandong Li, Ling Chen
Since its discovery, memristor has been well studied by researchers from all around the world, and its application in recognition proves to be very promising. In this paper, we modify a memristor crossbar circuit from an existing work to recognize 8 × 8 pixel binary images. We use analog memristors instead of binary memristors to complete the circuit. The simulated recognition rate is 82.5% in average, and we step further by carrying out a Monte Carlo simulation to analyze the performances of the circuit under different memristance variations and statistical distributions. We find that as the memristance variation rises up, the recognition rate under Gaussian distribution drops quickly, while the performance under uniform distribution is relatively stable. In the final part, we provide some outlooks and remarks on the possible improvements of the circuit.
{"title":"Analog memristor based neuromorphic crossbar circuit for image recognition","authors":"Lingfeng Xu, Chuandong Li, Ling Chen","doi":"10.1109/ICICIP.2015.7388161","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388161","url":null,"abstract":"Since its discovery, memristor has been well studied by researchers from all around the world, and its application in recognition proves to be very promising. In this paper, we modify a memristor crossbar circuit from an existing work to recognize 8 × 8 pixel binary images. We use analog memristors instead of binary memristors to complete the circuit. The simulated recognition rate is 82.5% in average, and we step further by carrying out a Monte Carlo simulation to analyze the performances of the circuit under different memristance variations and statistical distributions. We find that as the memristance variation rises up, the recognition rate under Gaussian distribution drops quickly, while the performance under uniform distribution is relatively stable. In the final part, we provide some outlooks and remarks on the possible improvements of the circuit.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130323845","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388204
H. Lin, Qinglai Wei, Derong Liu
In this paper, a novel critic-identifier-actor optimal control scheme is designed for discrete-time affine nonlinear systems with uncertainties. A neural identifier is established to learn the unknown control coefficient matrix for affine nonlinear system working together with an actor-critic-based scheme to solve the optimal control in online and forward-in-time manner without value or policy iterations. A critic network learns approximate value function at each step. Another actor network attempts to improve the current policy based on the approximate value function. The weights of all neural networks (NNs) are updated at each sampling instant. Lyapunov theory is utilized to prove the stability of the closed-loop system. A simulation example is provided to illustrate the effectiveness of the developed method.
{"title":"Online critic-identifier-actor algorithm for optimal control of nonlinear systems","authors":"H. Lin, Qinglai Wei, Derong Liu","doi":"10.1109/ICICIP.2015.7388204","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388204","url":null,"abstract":"In this paper, a novel critic-identifier-actor optimal control scheme is designed for discrete-time affine nonlinear systems with uncertainties. A neural identifier is established to learn the unknown control coefficient matrix for affine nonlinear system working together with an actor-critic-based scheme to solve the optimal control in online and forward-in-time manner without value or policy iterations. A critic network learns approximate value function at each step. Another actor network attempts to improve the current policy based on the approximate value function. The weights of all neural networks (NNs) are updated at each sampling instant. Lyapunov theory is utilized to prove the stability of the closed-loop system. A simulation example is provided to illustrate the effectiveness of the developed method.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114630043","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388230
Zhuoran Chen, X. Liao
In this letter, a recurrent kernel online learning algorithm with a processed feedback is proposed. The delayed output is processed by a well designed nonlinear piecewise function, which strengthens or weakens the feedback in response to different situation. Furthermore, the algorithm includes a data-dependent adaptive learning rate which evolves from kernel incremental meta-learning algorithm. Experimental results show that the novel algorithm outperforms both the kernel adaptive filter with multiple feedback and the kernel algorithm with single feedback in terms of convergence speed and estimation accuracy.
{"title":"Kernel incremental meta-learning with processed feedback","authors":"Zhuoran Chen, X. Liao","doi":"10.1109/ICICIP.2015.7388230","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388230","url":null,"abstract":"In this letter, a recurrent kernel online learning algorithm with a processed feedback is proposed. The delayed output is processed by a well designed nonlinear piecewise function, which strengthens or weakens the feedback in response to different situation. Furthermore, the algorithm includes a data-dependent adaptive learning rate which evolves from kernel incremental meta-learning algorithm. Experimental results show that the novel algorithm outperforms both the kernel adaptive filter with multiple feedback and the kernel algorithm with single feedback in terms of convergence speed and estimation accuracy.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132104119","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388182
Zepeng Ning, Lixian Zhang, Jitai Liang, J. de Jesús Rubio
This paper is concerned with the problem of state estimation for a class of discrete-time Takagi-Sugeno fuzzy affine systems against measurement quantization. The quantization density can be manually adjusted to satisfy different performance requirements at different time instants, which can reduce the amount of transmitted information when the performance requirement for the fuzzy filtering error system is not critical. With the aid of a fuzzy-basis-dependent Lyapunov function and the S-procedure approach, sufficient conditions on the existence of the desired H∞ filters are established to ensure that the fuzzy filtering error system is asymptotically stable with a prescribed H∞ performance index. Finally, a practical example of single-link robot arm is provided to illustrate the effectiveness as well as the smaller transmitted information burden of the proposed state estimation strategy.
{"title":"State estimation for T-S fuzzy affine systems with variable quantization density","authors":"Zepeng Ning, Lixian Zhang, Jitai Liang, J. de Jesús Rubio","doi":"10.1109/ICICIP.2015.7388182","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388182","url":null,"abstract":"This paper is concerned with the problem of state estimation for a class of discrete-time Takagi-Sugeno fuzzy affine systems against measurement quantization. The quantization density can be manually adjusted to satisfy different performance requirements at different time instants, which can reduce the amount of transmitted information when the performance requirement for the fuzzy filtering error system is not critical. With the aid of a fuzzy-basis-dependent Lyapunov function and the S-procedure approach, sufficient conditions on the existence of the desired H∞ filters are established to ensure that the fuzzy filtering error system is asymptotically stable with a prescribed H∞ performance index. Finally, a practical example of single-link robot arm is provided to illustrate the effectiveness as well as the smaller transmitted information burden of the proposed state estimation strategy.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132216993","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388220
Pengyuan Guo, Zhongshan Jiang, Sai Wang
Aiming at the variable-speed constant-frequency and constant-voltage control strategy of Brushless Doubly-Fed Generator (BDFG) independent operation, stator double synchronous speed mathematical model was established through coordinate transformation of the mechanical rotor speed d-q coordinate model. Besides to improve the robustness and achieve online PID parameters adjustment when the generator state changed, the expert PID regulator was introduced. Finally the direct voltage control strategy based on the flux oriented control theory and expert PID regulator was deduced. It can be seen that the system can control the output power according to the load, and realize the variable-speed constant-frequency and constant-voltage electricity generation. The effectiveness of the proposed control strategy is verified by simulation.
{"title":"Study on the direct voltage control strategy of Brushless Doubly-Fed independent power generation system","authors":"Pengyuan Guo, Zhongshan Jiang, Sai Wang","doi":"10.1109/ICICIP.2015.7388220","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388220","url":null,"abstract":"Aiming at the variable-speed constant-frequency and constant-voltage control strategy of Brushless Doubly-Fed Generator (BDFG) independent operation, stator double synchronous speed mathematical model was established through coordinate transformation of the mechanical rotor speed d-q coordinate model. Besides to improve the robustness and achieve online PID parameters adjustment when the generator state changed, the expert PID regulator was introduced. Finally the direct voltage control strategy based on the flux oriented control theory and expert PID regulator was deduced. It can be seen that the system can control the output power according to the load, and realize the variable-speed constant-frequency and constant-voltage electricity generation. The effectiveness of the proposed control strategy is verified by simulation.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132242795","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}
In this paper, we analyze the effects of frequency offset to Weighted fractional Fourier transform (WFRFT) system under the time frequency fading channel. The expression of signal-to-interference ratio (SIR) due to ICI and ISI is derived for the first time. The bit error rate (BER) performance of BPSK modulation scheme of single-carrier (SC), OFDM and WFRFT-OFDM systems are simulated respectively. Simulation results show that when carrier offset exists, WFRFT system has superiority over both SC and OFDM systems by choosing an optimal fractional order.
{"title":"Performance analysis for WFRFT-OFDM systems to carrier frequency offset in doubly selective fading channels","authors":"Shuang Yu, Hao Dai, Keqi Wu, Guoxiang Zhou, Xiaoxia Cheng, Chaoyong Xu","doi":"10.1109/ICICIP.2015.7388135","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388135","url":null,"abstract":"In this paper, we analyze the effects of frequency offset to Weighted fractional Fourier transform (WFRFT) system under the time frequency fading channel. The expression of signal-to-interference ratio (SIR) due to ICI and ISI is derived for the first time. The bit error rate (BER) performance of BPSK modulation scheme of single-carrier (SC), OFDM and WFRFT-OFDM systems are simulated respectively. Simulation results show that when carrier offset exists, WFRFT system has superiority over both SC and OFDM systems by choosing an optimal fractional order.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892789","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388134
Yuming Feng, Chuandong Li, Tingwen Huang
In this letter, we combine the continuous systems with the impulsive control systems. Thus we propose a new mathematic model, namely sandwich control system. The system is a cyclic control system and there is no "rest time" for the inputs. The first and last parts of the system's inputs are continuous and other's is impulsive for a period of the system. We study the stability of it by constructing a Lyapunov function and using some mathematical techniques we get an exponential stability criteria in terms of a set of linear matrix inequalities. By the use of the results in this paper, the Chua's oscillor is controlled.
{"title":"Sandwich control systems","authors":"Yuming Feng, Chuandong Li, Tingwen Huang","doi":"10.1109/ICICIP.2015.7388134","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388134","url":null,"abstract":"In this letter, we combine the continuous systems with the impulsive control systems. Thus we propose a new mathematic model, namely sandwich control system. The system is a cyclic control system and there is no \"rest time\" for the inputs. The first and last parts of the system's inputs are continuous and other's is impulsive for a period of the system. We study the stability of it by constructing a Lyapunov function and using some mathematical techniques we get an exponential stability criteria in terms of a set of linear matrix inequalities. By the use of the results in this paper, the Chua's oscillor is controlled.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133263695","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388149
Bakhtawar Seerat, Usman Qamar
Due to availability of large amount of data with the emergence of computers and internet, data mining is getting popular in every field of life like business, health, disasters etc for predictive analysis. As more and more data becomes available, it becomes difficult to get useful information from that. In that case, that tremendous data is quite useless. For that purpose data mining comes as a savior and helps us to extract useful information out of the data. This information can be used further for decision making. This paper presents a model that helps in diagnosis of diseases by analyzing the patients' data. The patients' attributes are analyzed and association rules are extracted from these attributes. Association rule based Classification is used for disease diagnosis and thus helpful in clinical decision making. A patient is classified as healthy or sick based on his attributes using classification. Disease Mining Model is proposed (DMM) based on association rules mining (ARM). This model is globally optimized by using Weighted Association Rules Mining (WARM) as Optimized Disease Mining Model (ODMM) which provides improved accuracy of disease prediction for every disease dataset. Both DMM and ODMM are tested on nine datasets of different diseases. Results of disease diagnosis are verified against real diagnosis. WARM improves the accuracy of diagnosis and thus outperforms ARM. Thus in this work, Classification using Ripper algorithm is much improved using weight optimization.
{"title":"Rule induction using enhanced RIPPER algorithm for clinical decision support system","authors":"Bakhtawar Seerat, Usman Qamar","doi":"10.1109/ICICIP.2015.7388149","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388149","url":null,"abstract":"Due to availability of large amount of data with the emergence of computers and internet, data mining is getting popular in every field of life like business, health, disasters etc for predictive analysis. As more and more data becomes available, it becomes difficult to get useful information from that. In that case, that tremendous data is quite useless. For that purpose data mining comes as a savior and helps us to extract useful information out of the data. This information can be used further for decision making. This paper presents a model that helps in diagnosis of diseases by analyzing the patients' data. The patients' attributes are analyzed and association rules are extracted from these attributes. Association rule based Classification is used for disease diagnosis and thus helpful in clinical decision making. A patient is classified as healthy or sick based on his attributes using classification. Disease Mining Model is proposed (DMM) based on association rules mining (ARM). This model is globally optimized by using Weighted Association Rules Mining (WARM) as Optimized Disease Mining Model (ODMM) which provides improved accuracy of disease prediction for every disease dataset. Both DMM and ODMM are tested on nine datasets of different diseases. Results of disease diagnosis are verified against real diagnosis. WARM improves the accuracy of diagnosis and thus outperforms ARM. Thus in this work, Classification using Ripper algorithm is much improved using weight optimization.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121700100","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}
Pub Date : 2015-11-01DOI: 10.1109/ICICIP.2015.7388226
Bin Cao, Ziqian Wang, Haibo Shi, Yixin Yin
This paper presents a six-layer Aluminum Industry 4.0 architecture for the aluminum production and full lifecycle supply chain management. It integrates a series of innovative technologies, including the IoT sensing physical system, industrial cloud platform for data management, model-driven and big data driven analysis & decision making, standardization & securitization intelligent control and management, as well as visual monitoring and backtracking process etc. The main relevant control models are studied. The applications of real-time accurate perception & intelligent decision technology in the aluminum electrolytic industry are introduced.
{"title":"Research and practice on Aluminum Industry 4.0","authors":"Bin Cao, Ziqian Wang, Haibo Shi, Yixin Yin","doi":"10.1109/ICICIP.2015.7388226","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388226","url":null,"abstract":"This paper presents a six-layer Aluminum Industry 4.0 architecture for the aluminum production and full lifecycle supply chain management. It integrates a series of innovative technologies, including the IoT sensing physical system, industrial cloud platform for data management, model-driven and big data driven analysis & decision making, standardization & securitization intelligent control and management, as well as visual monitoring and backtracking process etc. The main relevant control models are studied. The applications of real-time accurate perception & intelligent decision technology in the aluminum electrolytic industry are introduced.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121795689","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}
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