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Yuhe Xia1,Xianfu Zhang1,Shengxiang Xia2,Mingyue Wu1,Yiyu Feng1.[en_title][J].Control Theory and Technology,2024,22(4):568~580.[Copy]
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YuheXia1,XianfuZhang1,ShengxiangXia2,MingyueWu1,YiyuFeng1
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(1 School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China;2 School of Science, Shandong Jianzhu University, Jinan 250101, Shandong, China)
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DOI:https://doi.org/10.1007/s11768-024-00227-5
基金项目:This work was supported by the Major Fundamental Research Program of the Natural Science Foundation of Shandong Province, China (No. ZR2020ZD25), the Autonomous Innovation Team Foundation for “20 Items of the New University” of Jinan City (No. 202228087).
Pathological basal ganglia oscillations with time delays: a memoryless feedback control strategy
Yuhe Xia1,Xianfu Zhang1,Shengxiang Xia2,Mingyue Wu1,Yiyu Feng1
(1 School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China;2 School of Science, Shandong Jianzhu University, Jinan 250101, Shandong, China)
Abstract:
Pathological basal ganglia oscillations are associated with the hypokinetic motor symptoms of Parkinson’s disease. In this paper, a memoryless feedback control strategy is proposed to suppress pathological oscillations in the basal ganglia. In the most of closed-loop control strategies, the excitatory subthalamic nucleus populations are both monitored and stimulated targets, neglecting the important contribution of the external globus pallidus populations in suppressing pathological oscillations. To this end, we transform the original model into a time-delay system with a lower-triangular structure, and construct a memoryless state feedback controller utilizing the gain scaling method. It is proved by the Lyapunov–Krasovskii functional method that all the signals of the resulting closed-loop system are bounded, and the system states converge to an adjustable region of the origin. In addition, the input delay in stimulating the target is considered and a corresponding controller is designed to achieve convergence of the states in the resulting closed-loop system with both state delays and input delay. Moreover, simulation tests are conducted to explore the performance of the control strategy. This paper further explores the intrinsic dynamics in the neural system, and provides an effective strategy for closed-loop deep brain stimulation control.
Key words:  Parkinson’s disease · Pathological oscillations · Memoryless feedback · Lower-triangular structure · Time delays