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Related Concept Videos

Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

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A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
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Two-Dimensional Force System: Problem Solving01:29

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Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
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One-Degree-of-Freedom System01:24

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
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When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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Method of Joints: Problem Solving II01:30

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Consider a truss structure with frictionless joints fixed to a wall and roller support. If a force of 150 N is applied to joint A, the forces in each member of the truss can be determined using the method of joints.
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Updated: Sep 23, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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Adaptive Dynamic Programming-Based Cooperative Motion/Force Control for Modular Reconfigurable Manipulators: A Joint

Bo Zhao, Yongwei Zhang, Derong Liu

    IEEE Transactions on Neural Networks and Learning Systems
    |May 11, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a cooperative motion/force control (CMFC) scheme using adaptive dynamic programming (ADP) for modular reconfigurable manipulators (MRMs). The approach enables cooperative task assignment for enhanced control performance and stability.

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    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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    Area of Science:

    • Robotics
    • Control Systems Engineering
    • Artificial Intelligence

    Background:

    • Modular reconfigurable manipulators (MRMs) present complex control challenges due to their interconnected joint modules.
    • Cooperative motion and force control (CMFC) is crucial for MRMs to perform intricate tasks effectively.
    • Existing control schemes often struggle with the dynamic interconnections and task distribution in MRMs.

    Purpose of the Study:

    • To develop a novel cooperative motion/force control (CMFC) scheme for modular reconfigurable manipulators (MRMs).
    • To implement an adaptive dynamic programming (ADP) approach for robust and stable control.
    • To address the challenges of joint task assignment and inter-module dynamics in MRMs.

    Main Methods:

    • A joint task assignment approach is used to decompose the MRM system dynamics.
    • A neural network (NN)-based robust decentralized observer is developed for module state estimation.
    • An improved local value function and a critic NN with nested learning structure are employed to solve the Hamilton-Jacobi-Bellman equation.
    • Force feedback compensation and Lyapunov stability analysis are utilized.

    Main Results:

    • The proposed CMFC scheme effectively assigns motion and force tasks cooperatively to each joint module.
    • The NN-based observer guarantees asymptotic stability of the observation error.
    • The closed-loop MRM system is proven to be uniformly ultimately bounded under the ADP-based CMFC scheme.
    • Simulations on a two-degree of freedom MRM system validate the control approach's effectiveness.

    Conclusions:

    • The developed ADP-based CMFC scheme provides a stable and effective control solution for MRMs.
    • The joint task assignment and decentralized observer approach successfully manage complex interconnections.
    • This research offers a promising direction for advanced control of modular robotic systems.