深度强化学习增强了注塑成型机中的液压伺服系统的PID控制
Xiaoxi Hao1, Zengmiao Xin2, Weizhuo Huang1
1School of Mechanical and Automation Engineering, Wuyi University, Jiangmen, 529020, Guangdong, China.
Scientific reports
|July 2, 2025
概括
本研究介绍了用于注塑机的使用深度决定性政策梯度 (DDPG) 的自适应PID控制策略. 该方法提高了位置控制的准确性和系统对干扰的稳定性.
科学领域:
- * 控制系统工程 * 控制系统工程
- * 液压系统 * 液压系统
- * 机器学习应用程序
背景情况:
- *注塑成型机中的伺服液压系统面临着由于非线性和外部干扰而导致位置控制精度的挑战.
- *传统的控制方法很难适应这些系统固有的动态变化和不确定性.
研究的目的:
- * 开发一种新的自适应比例整合导数 (PID) 控制策略,以提高伺服液压系统的位置控制精度.
- * 为了在不同的条件下提高注射成型机控制系统的动态响应和稳定性.
主要方法:
- * 实施辅助伺服,以增加流量容量并改善系统动态响应.
- *利用深度决定性政策梯度 (DDPG) 算法,根据系统反实时调整PID参数.
- * 集成基于DDPG的自适应PID控制与辅助伺服结构.
主要成果:
- * 拟议的自适应PID控制策略与传统方法相比,显示出更高的跟踪精度.
- * 该系统呈现出更快的收率和更强的抗外部干扰和系统非线性性的强度.
- *通过DDPG实时优化PID参数,提高了适应时间变化的操作条件的适应性.
结论:
- *新的自适应PID控制策略有效地解决了伺服液压系统中传统方法的局限性.
- * DDPG和辅助伺服的集成为复杂的液压系统的自适应控制提供了一个有前途的方法.
- * 这项研究为提高注塑机的性能和可靠性提供了新的技术途径.
相关概念视频
PID Controller
242
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
242
PD Controller: Design
358
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,...
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
358
PI Controller: Design
508
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...
508
Time-Domain Interpretation of PD Control
183
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...
183
Time and frequency -Domain Interpretation of PI Control
208
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...
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
208
Second Order systems I
240
A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
By reinterpreting the system, one can derive the closed-loop transfer function, which...
240


