In this paper, an interval estimation scheme is developed for delayed switched positive systems(DSPS) with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the de...
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In this paper, an interval estimation scheme is developed for delayed switched positive systems(DSPS) with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the delayed intersection zonotope with the positive generator matrix. First, considering the existence of asynchronism between the system mode and the correction matrix mode, the mismatched intersection zonotope is constructed for DSPS to verify the consistency between the system model and ***, by utilizing the introduced radius definitions, the ?∞performance is addressed to optimize the size of delayed intersection zonotopes. Subsequently, we present a joint-design approach of switching signals and the mode-dependent correction matrix by constructing positive generator matrix-based delayed radius functions. Furthermore, guaranteed nonnegative state bounds are derived for the considered DSPS based on the proposed lossless zonotopic estimation criteria. Finally, detailed simulations are conducted to validate the feasibility and superiority of the developed methods.
The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the syst...
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The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the systems,adaptive regulators are directly designed based on the event-triggered observations on the regulation *** adaptive regulators belong to the stochastic approximation algorithms and under moderate assumptions,the authors prove that the adaptive regulators are optimal for both the Hammerstein and Wiener systems in the sense that the squared regulation errors are asymptotically *** authors also testify the theoretical results through simulation studies.
The stability of complex systems is profoundly affected by underlying structures, which are often modeled as networks where nodes indicate system components and edges indicate pairwise interactions between nodes. Howe...
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The stability of complex systems is profoundly affected by underlying structures, which are often modeled as networks where nodes indicate system components and edges indicate pairwise interactions between nodes. However, such networks cannot encode the overall complexity of networked systems with higher-order interactions among more than two nodes. Set structures provide a natural description of pairwise and higher-order interactions where nodes are grouped into multiple sets based on their shared traits. Here we derive the stability criteria for networked systems with higher-order interactions by employing set structures. In particular, we provide a simple rule showing that the higher-order interactions play a double-sided role in community stability—networked systems with set structures are stabilized if the expected number of common sets for any two nodes is less than one. Moreover, although previous knowledge suggests that more interactions(i.e. complexity) destabilize networked systems, we report that,with higher-order interactions, networked systems can be stabilized by forming more local sets. Our findings are robust with respect to degree heterogeneous structures, diverse equilibrium states and interaction types.
The optimization of fuzzy grey cognitive map (FGCM) can enhance the decision quality of the system in managing uncertainties and incomplete information. Addressing this issue requires a method that effectively balance...
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Parkinson’s disease (PD) is a neurodegenerative disorder with slow progression whose symptoms can be identified at late stages. Early diagnosis and treatment of PD can help to relieve the symptoms and delay progressi...
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Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperati...
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Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperative decision-making,it is challenging for existing MARL algorithms to quickly converge to an optimal strategy for UCAV formation in BVR air combat where confrontation is complicated and reward is extremely sparse and *** to solve this problem,this paper proposes an Advantage Highlight Multi-Agent Proximal Policy Optimization(AHMAPPO)***,at every step,the AHMAPPO records the degree to which the best formation exceeds the average of formations in parallel environments and carries out additional advantage sampling according to ***,the sampling result is introduced into the updating process of the actor network to improve its optimization ***,the simulation results reveal that compared with some state-of-the-art MARL algorithms,the AHMAPPO can obtain a more excellent strategy utilizing fewer sample episodes in the UCAV formation BVR air combat simulation environment built in this paper,which can reflect the critical features of BVR air *** AHMAPPO can significantly increase the convergence efficiency of the strategy for UCAV formation in BVR air combat,with a maximum increase of 81.5%relative to other algorithms.
Breast cancer is among the major frequent types of cancer worldwide, causing a significant death rate every year. It is the second most prevalent malignancy in Egypt. With the increasing number of new cases, it is vit...
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The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the de...
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Pharmazeutische Anlagen für das Mahlen und die Pulver- bzw. Partikelaufbereitung benötigen eine individuell gestaltete Prozessgas- und Flüssigkeitsverteilung. Bürkert Fluid controlsystems bietet d...
Pharmazeutische Anlagen für das Mahlen und die Pulver- bzw. Partikelaufbereitung benötigen eine individuell gestaltete Prozessgas- und Flüssigkeitsverteilung. Bürkert Fluid controlsystems bietet dafür verschweißte Ventilplattformen, die die Medienführung wirtschaftlicher gestalten.
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