一个基于惩罚的分布式归零神经网络,用于在平等和不平等的约束下进行时间变化的优化,并将其应用于冗余机器人操纵器的合作控制
Liu He1, Hui Cheng1, Yunong Zhang2
1School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.
Frontiers in neurorobotics
|April 1, 2025
概括
本研究介绍了一种新的基于惩罚的归零神经网络 (PB-ZNN),用于解决在多代理系统 (MAS) 中改变目标和约束的分布式优化问题. 开发的分布式PB-ZNN算法确保了所有代理商的共识和可行性.
科学领域:
- 控制系统工程 控制系统工程
- 优化理论 优化理论
- 人工智能的人工智能
背景情况:
- 多代理系统 (MAS) 中的分布式优化问题通常涉及动态目标函数和约束.
- 现有的方法可能会在实时调整和分散的决策方面扎.
研究的目的:
- 开发一种新的方法来解决MAS中的分布式变时受约束优化 (DTVCO) 问题.
- 为了使代理人能够仅使用本地信息和邻居通信来计算最佳解决方案.
主要方法:
- 为连续时间DTVCO (CTDTVCO) 提出了一种基于惩罚的归零神经网络 (PB-ZNN).
- 整合了两个惩罚功能:一个用于代理人之间的共识,另一个用于约束满足.
- 使用欧勒公式开发了一个分布式PB-ZNN (DPB-ZNN) 算法,用于离散时间DTVCO (DTDTVCO).
主要成果:
- PB-ZNN模型以半集中的方式解决CTDTVCO,而DPB-ZNN以完全分布式的方式解决DTDTVCO.
- 对于PB-ZNN和DPB-ZNN的融合定理进行了展示和证明.
- 数字示例,包括冗余操纵器的合作控制,证明了算法的有效性和准确性.
结论:
- 拟议的PB-ZNN和DPB-ZNN算法有效地解决了分布式时间变化的受约束优化问题.
- DPB-ZNN算法为离散时间场景提供了一个完全分布式的解决方案.
- 这种方法通过模拟和实际应用 (如机器人操纵器控制) 来验证.
相关概念视频
01:07Time-Domain Interpretation of PD Control
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Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
Consider the example of control of motor torque. Initially, a positive...
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01:27Time and frequency -Domain Interpretation of PI Control
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Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
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01:22Controller Configurations
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Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
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01:24PI Controller: Design
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Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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01:26PD Controller: Design
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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
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01:21Linear Approximation in Time Domain
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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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