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Zhuang G, Wang X, Xia J, Wang Y. Observer-based asynchronous feedback H∞ control for delayed fuzzy implicit jump systems under HMM and event-trigger mechanisms. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.02.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
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Jia C, Hu J, Yi X, Liu H, Huang J, Cao Z. Recursive state estimation for a class of quantized coupled complex networks subject to missing measurements and amplify-and-forward relay. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
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Wang J, Zhuang G, Xia J, Chen G. Memory characteristics-based generalized fuzzy dissipative robust control for multiple delayed uncertain jump systems. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.08.107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Liu R, Liu M, Ye D, Yu Y. Event-triggered Adaptive Fixed-time Fuzzy Control for Uncertain Nonlinear Systems with Unknown Actuator Faults. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.08.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Karimoddini A, Hailemichael A, Jamshidi M. FLC-ROS: A generic and configurable ROS package for developing fuzzy logic controllers1. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022. [DOI: 10.3233/jifs-210341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Fuzzy logic controllers can handle complex systems by incorporating expert’s knowledge in the absence of formal mathematical models. Further, fuzzy logic controllers can effectively capture and accommodate uncertainties that are inherent in real-world controlled systems. On the other hand, Robot Operating System (ROS) has been widely used for many robotic applications due to its modular structure and efficient message-passing mechanisms for the integration of system’s components. For this reason, Robot Operating System is an ideal tool for developing software stacks for robotic applications. This paper develops a generic and configurable Robot Operating System package for the implementation of fuzzy logic controllers, particularly type-1 and interval type-2, which are based on either Mamdani or Takagi-Sugeno-Kang fuzzy inference mechanisms. This is achieved by employing a systematic object-oriented approach using the Unified Model Language (UML) to implement the fuzzy inference system as a single class that is composed of fuzzifier, inference, and defuzzifier classes. The deployment of the developed Robot Operating System package is demonstrated by implementing an interval type-2 fuzzy logic control of an Unmanned Aerial Vehicle (UAV).
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Affiliation(s)
- Ali Karimoddini
- Department of Electrical and Computer Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA
| | - Abel Hailemichael
- Department of Electrical and Computer Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA
| | - Mo Jamshidi
- Department of Electrical and Computer Engineering, The University of Texas, San Antonio, TX, USA
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Output-feedback distributed consensus for nonlinear multi-agent systems with quantization. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.11.022] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Event-triggered optimal control for discrete-time multi-player non-zero-sum games using parallel control. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.10.073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Jia X, Xu S, Shi X, Du B, Zhang Z. Adaptive output feedback tracking for time-delay nonlinear systems with unknown control coefficient and application to chemical reactors. Inf Sci (N Y) 2021. [DOI: 10.1016/j.ins.2021.10.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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