相关实验视频

Updated: Jan 12, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

11.1K

对于具有复杂不可测量的前提变量TS模糊系统的功能观察器设计

Wen-Bo Xie, Guan-Qun Chen, Wen-Jie Wu

    IEEE transactions on cybernetics
    |November 4, 2025
    PubMed
    概括

    本研究引入了一种用于设计在 Takagi-Sugeno (T-S) 模糊系统中具有不可测量的前提变量 (UPV) 的功能观察者控制器 (FOC) 的新方法. 该方法有效地估计和控制系统,尽管UPV中的非线性.

    更多相关视频

    Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods13:04

    Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

    Published on: September 19, 2012

    12.4K
    Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study20:24

    Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

    Published on: January 31, 2014

    17.1K

    相关概念视频

    Multi-input and Multi-variable systems01:22

    Multi-input and Multi-variable systems

    Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
    In the absence of...
    383
    Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

    Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

    Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
    In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
    277
    State Space Representation01:27

    State Space Representation

    The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
    Consider an RLC circuit, a...
    515
    Mechanistic Models: Overview of Compartment Models01:21

    Mechanistic Models: Overview of Compartment Models

    Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
    349
    Actor-Observer Effect01:23

    Actor-Observer Effect

    The actor-observer effect, a cognitive bias closely linked to the fundamental attribution error, refers to the tendency for individuals to attribute their behavior to external, situational factors while explaining others’ behavior in terms of internal, dispositional traits. This asymmetry in attribution significantly influences social perception and judgment.Cognitive Mechanisms Behind the EffectTwo primary psychological mechanisms contribute to the actor-observer effect: differences in...
    317
    Observational Studies01:11

    Observational Studies

    Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
    There are three types of observational studies – Prospective, retrospective, and cross-sectional.
    Prospective Study
    Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
    10.7K