2018 Indian Control Conference (ICC)最新文献_第4页

CAN-based networked path-tracking control of a 4WS4WD electric vehicle: Maximum sampling period 基于can的4WS4WD电动汽车网络路径跟踪控制:最大采样周期

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8308006

A. Singh, R. Potluri

{"title":"CAN-based networked path-tracking control of a 4WS4WD electric vehicle: Maximum sampling period","authors":"A. Singh, R. Potluri","doi":"10.1109/INDIANCC.2018.8308006","DOIUrl":"https://doi.org/10.1109/INDIANCC.2018.8308006","url":null,"abstract":"An earlier work of the authors presented a multi-input multi-output (MIMO) path-tracking control system (PTCS) for an autonomous version of the four-wheel steering four-wheel drive (4WS4WD) electric vehicle. This PTCS has a supervisor module controlling eight motor control system modules. Since a serial communication link has several advantages over point-to-point wiring, the practical implementation planned by the authors of the PTCS has these nine modules forming feedback loops over a Controller Area Network (CAN) protocol-based serial link, thereby forming a networked control system (NCS). However, the MIMO nonlinear loops in the PTCS turn the selection of the minimum and maximum sampling periods TS min and TS max for a digital implementation, while factoring the time delays introduced by the communication, into a non-trivial task. There do not exist NCS methods to address the MIMO nonlinear loops. This paper determines Ts max by solving the difficulty of MIMO nonlinear loops by finding a SISO representation of the MIMO NCS using a procedure that is applicable to a class of MIMO NCS that evince a certain symmetry. It then validates the choice of Ts max through a hardware-in-the-loop simulation. The techniques shown are promising for applications involving coordination of multiple actuators and for CAN-based NCS.","PeriodicalId":338695,"journal":{"name":"2018 Indian Control Conference (ICC)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133570521","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: 2

Two stage proportional navigation guidance law for impact time control 冲击时间控制的两级比例导航制导律

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307997

Abdulrahman Saleem, Ashwini Ratnoo

引用次数: 3

Interpretation of complex reaction networks in Boolean network framework 布尔网络框架下复杂反应网络的解释

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307945

S. Sutavani, K. Sarda, A. Yerudkar, N. Singh

{"title":"Interpretation of complex reaction networks in Boolean network framework","authors":"S. Sutavani, K. Sarda, A. Yerudkar, N. Singh","doi":"10.1109/INDIANCC.2018.8307945","DOIUrl":"https://doi.org/10.1109/INDIANCC.2018.8307945","url":null,"abstract":"Real world chemical systems are modeled as Complex Reaction Networks (CRNs) in attempt to study their behavior in mathematical framework. Structures and reactive properties of small reactions can be computed efficiently and accurately using mass action kinetics. However, the CRNs with large number of nodes, requirements on amount and accuracy of data and computational complexity increases rapidly with number of nodes, rendering the conventional methods unfeasible when accuracy of data available and/or availability of computational power is not sufficient. The CRN dynamics are given by the deterministic differential equations which can demonstrate to different behaviors such as Oscillations, fixed points (unique or multiple, stable or unstable). This paper focuses on the results related to the fixed points, the attractor hypothesis. The paper proposes an approach to analyze the mass action kinetics of a CRN with the help of it's linear state-space formulation. The CRN is represented by a Boolean network. Formulating it's dynamics in the form of Boolean functions, the state transition matrix of the CRN is obtained using semi tensor product (STP) approach. This state transition matrix is analyzed for finding out possible equilibria and cycles of CRN. The method makes use of mass action dynamics without any quantitative knowledge of reaction rates to give qualitative behavior of system evolution.","PeriodicalId":338695,"journal":{"name":"2018 Indian Control Conference (ICC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134069851","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: 2

Autonomous maneuvering of a stratospheric airship 平流层飞艇的自主机动

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307998

D. Gobiha, N. K. Sinha

引用次数: 7

Frequency synchronisation of islanded microgrids using robust adaptation over Luré forms 基于鲁棒自适应的孤岛微电网频率同步

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307946

Navdeep M. Singh, P. Bajaria

引用次数: 0

Identification of approximate models for LTI multiscale systems LTI多尺度系统的近似模型辨识

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307956

V. S. Pinnamaraju, A. Tangirala

引用次数: 0

Observability-based secure state encryption design for cyberphysical systems 基于可观察性的网络物理系统安全状态加密设计

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307948

Yimeng Dong, N. Chopra

引用次数: 2

Pre-fuzzy-PID controller for effective control of electromagnetic levitation system 预模糊pid控制器对电磁悬浮系统进行有效控制

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307963

R. Gandhi, D. Adhyaru

引用次数: 9

Distributed optimization via primal-dual gradient dynamics with stochastic interactions 具有随机相互作用的原对偶梯度动力学分布优化

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307947

S. Pushpak, K. Ebrahimi, U. Vaidya

{"title":"Distributed optimization via primal-dual gradient dynamics with stochastic interactions","authors":"S. Pushpak, K. Ebrahimi, U. Vaidya","doi":"10.1109/INDIANCC.2018.8307947","DOIUrl":"https://doi.org/10.1109/INDIANCC.2018.8307947","url":null,"abstract":"In this paper, we analyze the performance of the primal-dual gradient dynamics algorithm in the presence of stochastic communication channel uncertainty. In contrast to the existing results on the analysis of discretized primal-dual gradient dynamics with communication channel uncertainty, the main contribution of this work is in analyzing the stochastic continuous-time primal-dual gradient dynamics. Primal-dual gradient dynamics for distributed optimization are naturally modeled as a continuous-time dynamical system and analysis of this dynamics help us understand fundamental limitations and trade-offs between the cost function, network topology, and channel uncertainty for distributed optimization. We analyze the mean square stochastic stability of primal-dual gradient dynamics with communication channel uncertainty. The network topology is said to be more robust for distributed optimization if it can tolerate maximum variance of communication uncertainty. One of the important results of this paper is to show the existence of an optimal number of neighbors individual agent should have for robust distributed optimization. The optimal number is a function of network topology and cost function. If the network has more or less number of neighbors than the optimal number, then the network performance degrades. Simulation results involving nearest network topology are presented to verify the main conclusion of this paper.","PeriodicalId":338695,"journal":{"name":"2018 Indian Control Conference (ICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130785671","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: 2

Time-frequency control of linear time-varying systems using forward Riccati differential equation 线性时变系统的正演Riccati微分方程时频控制

2018 Indian Control Conference (ICC) Pub Date : 1900-01-01 DOI: 10.1109/INDIANCC.2018.8307982

B. Basu, A. Staino

引用次数: 1