Consensus Control Strategy for the Treatment of Tumour with Neuroadaptive Cellular Immunotherapy

IF 15.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jiayue Sun;Dongni Li;Huaguang Zhang;Lu Liu;Wenyue Zhao
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引用次数: 0

Abstract

This paper presents a novel neuro-adaptive cellular immunotherapy control strategy that leverages the high efficiency and applicability of chimeric antigen receptor-engineered T (CAR-T) cells in treating cancer. The proposed real-time control strategy aims to maximize tumor regression while ensuring the safety of the treatment. A dynamic growth model of cancer cells under the influence of cellular immunotherapy is established for the first time, which aligns with clinical experimental results. Utilizing the backstepping method, a novel consensus reference model is designed to consider the characteristics of cancer cell changes during the treatment process and conform to clinical rules. The model is segmented and continuous, with cancer cells expected to decrease in a step-like manner. Furthermore, a prescribed performance mechanism is constructed to maintain the therapeutic effect of the proposed scheme while ensuring the transient performance of the system. Through the analysis of Lyapunov stability, all signals within the closed-loop system are proven to be semiglobally uniformly ultimately bounded (SGUUB). Simulation results demonstrate the effectiveness of the proposed control strategy, highlighting its potential for clinical application in cancer treatment.
神经适应性细胞免疫治疗肿瘤的共识控制策略
本文提出了一种新的神经适应性细胞免疫治疗控制策略,该策略利用嵌合抗原受体工程T细胞(CAR-T)治疗癌症的高效率和适用性。所提出的实时控制策略旨在最大限度地使肿瘤消退,同时保证治疗的安全性。首次建立了细胞免疫治疗作用下癌细胞的动态生长模型,与临床实验结果一致。利用回溯法,设计了一种新的共识参考模型,考虑了治疗过程中癌细胞变化的特点,符合临床规律。该模型是分段和连续的,癌细胞预计会以阶梯状的方式减少。此外,在保证系统暂态性能的同时,构建了一种规定的性能机制来维持所提出方案的治疗效果。通过对Lyapunov稳定性的分析,证明了闭环系统内的所有信号都是半全局一致最终有界的。仿真结果证明了所提出的控制策略的有效性,突出了其在癌症治疗中的临床应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ieee-Caa Journal of Automatica Sinica
Ieee-Caa Journal of Automatica Sinica Engineering-Control and Systems Engineering
CiteScore
23.50
自引率
11.00%
发文量
880
期刊介绍: The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control. Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.
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