Adaptive Learning and Sampled-Control for Nonlinear Game Systems Using Dynamic Event-Triggering Strategy

2021 ◽  
pp. 1-14
Author(s):  
Chaoxu Mu ◽  
Ke Wang ◽  
Zhen Ni
Keyword(s):  
Adaptive Learning ◽  
Dynamic Event ◽  
Event Triggering ◽  
Nonlinear Game

scholarly journals Dynamic Event-Triggered Time-Varying Formation Control of Second-Order Dynamic Agents: Application to Multiple Quadcopters Systems

2020 ◽  
Vol 10 (8) ◽  
pp. 2814 ◽  
Author(s):  
Anh Tung Nguyen ◽  
Thanh Binh Nguyen ◽  
Sung Kyung Hong
Keyword(s):  
Formation Control ◽  
Second Order ◽  
Formation Flight ◽  
Time Varying ◽  
Triggering Mechanism ◽  
Agent Based ◽  
Dynamic Event ◽  
Event Triggering ◽  
Communication Ability ◽  
Event Triggered

This paper investigates the problem of the time-varying formation control of a second-order dynamic agent based on a distributed dynamic event-triggered algorithm. In this problem, each agent can exchange the information of its position and velocity with its neighbors via limited communication ability. Our approach provides a new dynamic event triggering mechanism to reduce the number of triggering times while maintaining satisfactory control performance. Further, a novel Lyapunov function is proposed to guarantee that the group of agents asymptotically tracks the desired time-varying formation trajectory. The practical applicability of the event triggering mechanism is also indicated by excluding the Zeno behavior in the proposed control algorithm. Finally, the validity and effectiveness of the proposed method are demonstrated via illustrative examples of the time-varying formation flight for six quadcopters.

scholarly journals Exponential Synchronization of Memristive Neural Networks with Discrete and Distributed Time-Varying Delays via Event-Triggered Control

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Biwen Li ◽  
Wenbo Zhou
Keyword(s):  
Neural Networks ◽  
Exponential Synchronization ◽  
Time Varying ◽  
Memristive Neural Networks ◽  
Dynamic Event ◽  
Synchronization Problem ◽  
Event Triggering ◽  
Triggering Conditions ◽  
Theoretical Results ◽  
Event Triggered

In this paper, we investigate the exponential synchronization problem of memristive neural networks (MNNs) with discrete and distributed time-varying delays under event-triggered control. An event-triggered controller with the static and dynamic event-triggering conditions is designed to improve the efficiency of resource utilization. By constructing a new Lyapunov function, some sufficient criteria are obtained to realize the exponential synchronization of considered drive-response MNNs under the designed event-triggered controller. In addition, the Zeno behavior will not occur by proving that the event-triggering interval has a positive lower bound under different event-triggering conditions. Finally, a numerical example is provided to prove the validity of our theoretical results.

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