On the robustness of the integrable trajectories of the control systems with limited control resources

IF 1.2 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS Archives of Control Sciences Pub Date : 2023-09-13 DOI:10.24425/acs.2023.146958
Nesir Huseyin, Anar Huseyin, Khalik G. Guseinov
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引用次数: 0

Abstract

The control system described by Urysohn type integral equation is considered where the system is nonlinear with respect to the phase vector and is affine with respect to the control vector. The control functions are chosen from the closed ball of the space $L_q\left(\Omega;\mathbb{R}^m\right),$ $q>1,$ with radius $r$ and centered at the origin. The trajectory of the system is defined as $p$-integrable multivariable function from the space $L_p\left(\Omega;\mathbb{R}^n\right),$ $\frac{1}{q}+\frac{1}{p}=1,$ satisfying the system's equation almost everywhere. It is shown that the system's trajectories are robust with respect to the remaining control resource. Applying this result it is proved that every trajectory can be approximated by the trajectory obtained by full consumption of the total control resource.
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有限控制资源下控制系统可积轨迹的鲁棒性
考虑由Urysohn型积分方程描述的控制系统,其中系统对相位矢量是非线性的,对控制矢量是仿射的。控制函数从空间$L_q\left(\Omega;\mathbb{R}^m\right),$$q>1,$的封闭球中选择,半径为$r$,以原点为中心。系统的轨迹定义为$L_p\left(\Omega;\mathbb{R}^n\right),$$\frac{1}{q}+\frac{1}{p}=1,$空间中几乎处处满足系统方程的$p$ -可积多变量函数。结果表明,系统轨迹相对于剩余控制资源具有鲁棒性。应用这一结果,证明了每条轨迹都可以用控制资源全部消耗时得到的轨迹来逼近。
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来源期刊
Archives of Control Sciences
Archives of Control Sciences Mathematics-Modeling and Simulation
CiteScore
2.40
自引率
33.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.
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