Browsing by Author "Cheng, Teng-Hu"

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A Switched Systems Approach to Image-Based Localization of Targets That Temporarily Leave the Camera Field of View
(2018-11-01)
Parikh, Anup
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Cheng, Teng-Hu
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Licitra, Ryan
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Dixon, Warren E.
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機械工程學系
Image sensors have widespread use in many robotics applications and, in particular, in target tracking. While existing methods assume continuous image feedback, the novelty of this brief stems from the development of dwell time conditions to guarantee convergence of state estimates to an ultimate bound for a class of image-based observers in the presence of intermittent measurements. A Lyapunov analysis for the switched system is performed to develop convergence conditions based on the minimum amount of time the object must be visible and on the maximum amount of time the object may remain outside the camera view. Experimental results are included to verify the theoretical results and elucidate real-world performance.
Communications and Networking Technologies for Intelligent Drone Cruisers
(2019-01-01)
Wang, Li-Chun
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Lai, Chuan-Chi
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Shuai, Hong-Han
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Lin, Hsin-Piao
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Li, Chi-Yu
Future mobile communication networks require an Aerial Base Station (ABS) with fast mobility and long-term hovering capabilities. At present, unmanned aerial vehicles (UAV) or drones do not have long flight times and are mainly used for monitoring, surveillance, and image post-processing. On the other hand, the traditional airship is too large and not easy to take off and land. Therefore, we propose to develop an "Artificial Intelligence (AI) Drone-Cruiser" base station that can help 5G mobile communication systems and beyond quickly recover the network after a disaster and handle the instant communications by the flash crowd. The drone-cruiser base station can overcome the communications problem for three types of flash crowds, such as in stadiums, parades, and large plaza so that an appropriate number of aerial base stations can be accurately deployed to meet large and dynamic traffic demands. Artificial intelligence can solve these problems by analyzing the collected data, and then adjust the system parameters in the framework of Self-Organizing Network (SON) to achieve the goals of self-configuration, self-optimization, and self-healing. With the help of AI technologies, 5G networks can become more intelligent. This paper aims to provide a new type of service, On-Demand Aerial Base Station as a Service. This work needs to overcome the following live technical challenges: innovative design of drone-cruisers for the long-time hovering, crowd estimation and prediction, rapid 3D wireless channel learning and modeling, 3D placement of aerial base stations and the integration of WiFi front-haul and millimeter wave/WiGig back-haul networks.
Decentralized Synchronization of Uncertain Nonlinear Systems With a Reputation Algorithm
(2018-03-01)
Klotz, Justin R.
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Parikh, Anup
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Cheng, Teng-Hu
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Dixon, Warren E.
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機械工程學系
Decentralized synchronization approaches generally assume that communication of state information between neigh-boring agents is completely accurate. However, just one agent's communication of inaccurate information to neighbors can significantly degrade the performance of the entire network. To help abate this problem, we present a decentralized controller for a leader-follower framework which uses local information to vet neighbors and change consensus weights accordingly. Because updates of the consensus weights produce a switched system, switching control theory techniques are used to develop a dwell-time that must elapse between agents' successive weight updates. A Lyapunov-based stability analysis is presented which develops sufficient conditions for approximate convergence of follower agents' states to a leader agent's time-varying state. Simulation results are provided to demonstrate the performance of the developed techniques.
Distributed Coverage Control with Dependent Density Functions
(2018-01-01)
Wu, Pin-Xian
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Li, Jun-Ming
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Cheng, Teng-Hu
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機械工程學系
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Department of Mechanical Engineering
A distributed coverage control strategy is developed for a group of heterogeneous robots in this work. Most existing coverage controllers assume the relation between the underlying density function and the locations of the robots is independent. To relax the condition for more potential applications, a new coverage control strategy that accounts for the dependence between the underlying density function and the locations of the robots is developed, and moreover, it can be extended to the conventional coverage controller by selecting specific system parameters. In addition, the heterogeneity among the robots can also cause various levels of reduction to the underlying density function, and hence, an Enhanced Multiplicatively Weighted Voronoi (EMWV) partition along with the controller is developed, so that optimal coverage can be obtained despite the heterogeneity between the robots. Stability analysis is proven to ensure system convergence, and simulations are conducted to verify the efficacy of the developed controllers.
Event-Triggered Control of Multiagent Systems for Fixed and Time-Varying Network Topologies
(2017-10-01)
Cheng, Teng-Hu
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Kan, Zhen
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Klotz, Justin R.
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Shea, John M.
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Dixon, Warren E.
A decentralized controller that uses event-triggered communication scheduling is developed for the leader-follower consensus problem under fixed and switching communication topologies. To eliminate continuous interagent communication, state estimates of neighboring agents are designed for control feedback and are updated via communication to reset growing estimate errors. The communication times are based on an event-triggered approach and are adapted based on the trade-off between the control system performance and the desire to minimize the amount of communication. An important aspect of the developed event trigger strategy is that communication is not required to determine when a state update is needed. Since the control strategy produces switched dynamics, analysis is provided to show that Zeno behavior is avoided by developing a positive constant lower bound on the minimum inter-event interval. A Lyapunov-based convergence analysis is also provided to indicate bounded convergence of the developed control methodology.
Output-Feedback-Based Event-Triggered Control of Multi-Agent Systems Without Continuous Inter-Agent Communication
(2018-01-01)
Shih, Chung-Shan
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Cheng, Teng-Hu
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機械工程學系
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Department of Mechanical Engineering
An output-feedback-based decentralized controller that uses event-triggered communication is developed for the leader-follower consensus problem. An observer is designed to estimate the state of each agent, and the estimated state is communicated to its neighboring agents for interaction. To eliminate continuous inter-agent communication, another estimators that estimate the states of neighboring agents are designed for control feedback and are updated via intermittent communication to reset increasing estimate errors. The communication times are based on an event-triggered strategy and are adapted based on the interplay between the control performance and the amount of reduced communication. The main contribution of the developed triggering approach is that inter-agent communication is not required to determine when a state update is needed. Since the developed control scheme introduces switched dynamics, analysis is conducted to indicate that Zeno behavior does not exist. A convergence analysis is also conducted to show bounded convergence of the developed control methodology.