基于梯度的自适应PID-SMC控制,通过殖民地优化调整为自动水下车辆的自动水下车辆
Mohammed Yousri Silaa1, Oscar Barambones2, Aissa Bencherif1
1Telecommunications Signals and Systems Laboratory (TSS), Amar Telidji University of Laghouat, BP 37G, Laghouat 03000, Algeria.
基于PID的自适应式滑动模式控制器 (APID-SMC) 增强了自动水下车辆 (AUV) 的轨迹跟踪. 它使用殖民地优化 (ACO) 进行了优化,在具有挑战性的海洋环境中提供了卓越的准确性和稳定性.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 海洋工程 海洋工程
- 人工智能的人工智能
背景情况:
- 自主水下车辆 (AUV) 需要强大的控制来准确跟踪轨迹.
- 像滑动模式控制 (SMC) 和PID这样的传统控制器经常与外部干扰和不确定性作斗争.
- 提高AUV控制性能对于复杂的海上作战至关重要.
研究的目的:
- 为自动驾驶汽车提出和评估基于PID的自适应式滑动模式控制器 (APID-SMC).
- 使用殖民地优化 (ACO) 来优化APID-SMC,以改进轨迹跟踪.
- 证明控制器在应对外部干扰和不确定性时的强大稳定性.
主要方法:
- 开发一个APID-SMC,将SMC的稳定性与PID流控制相结合.
- 使用渐变下降算法 (GDA) 进行PID增益的在线调整.
- 通过ACO优化学习速度和滑动表面系数,以最大限度地减少轨迹跟踪错误.
主要成果:
- 与传统方法相比,APID-SMC显著降低了整数绝对误差 (IAE) 高达27.97%和整数时间绝对误差 (ITAE) 高达82.84%.
- 控制器表现出优异的瞬态性能和减少控制信号的声.
- 在模拟海洋环境中的极端噪音和不确定性下,经过证明的稳定性和有效性.
结论:
- 拟议的APID-SMC为AUV提供了一个高度有效和实用的控制解决方案.
- 基于ACO的优化提高了融合速度和性能的一致性.
- 在复杂的海洋环境中,APID-SMC提供了更好的轨迹跟踪精度和稳定性.
更多相关视频
06:45Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
08:35Interactive and Visualized Online Experimentation System for Engineering Education and Research
Published on: November 24, 2021
相关概念视频
PID Controller
PD Controller: Design
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
PI Controller: Design
Time-Domain Interpretation of PD Control
Consider the example of control of motor torque. Initially, a positive...
Root-Locus Method
This system can be represented by a block...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
