Chunyu Yang
23 Papers
Chunyu Yang is an academic researcher. The author has contributed to research in topics: Computer science & Control theory (sociology). The author has co-authored 9 publications.
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Papers
Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua’s circuit
TL;DR: In this paper , an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack.
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Robust Kalman Filter for Systems with Colored Heavy-tailed Process and Measurement Noises
TL;DR: In this paper , the robust state estimation for a linear system with colored heavy-tailed process and measurement noises is considered, where state augmentation and measurement differencing methods are employed to whiten the colored noise and use the Student's t distribution to model the heavytailed property, which makes a new state space model with the augmented state vector.
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ADP-Based Optimal Control of Linear Singularly Perturbed Systems with Uncertain Dynamics: A Two-Stage Value Iteration Method
TL;DR: In this paper , the problem of adaptive dynamic programming (ADP) based on optimal control of linear singularly perturbed systems (SPSs) subject to completely unknown dynamics is studied.
Optimal Dynamic Controller Design for Linear Quadratic Tracking Problems
Jianguo Zhao,Chunyu Yang,Weinan Gao,Ju H. Park +3 more
TL;DR: This paper introduces a novel performance index for infinite-horizon linear quadratic tracking problems, reformulating the problem using the minimal polynomial of the exosystem, and providing a solution that achieves closed-loop stability and asymptotic tracking without stability constraints on the exosystem.
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Obstacle Avoidance for Trackless Rubber-Tired Vehicle Based on Risk-Grid Particle Swarm Optimization in Confined Space of Deep Well
TL;DR: In this article , a novel environment model is constructed with a basic grid map and a risk one, and an improved obstacle avoidance planning algorithm is proposed by designing a risk grid particle swarm optimization (RGPSO) algorithm.
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