扰动补偿
估计和补偿线性系统的扰动和未知动态特性
使用估计方法,基于被控对象的输入和输出来估计被控对象的状态和扰动。
模块
Active Disturbance Rejection Control | 为具有未知动态特性和扰动的被控对象设计控制器 (自 R2022b 起) |
Extended State Observer | Estimate states and disturbances of a system (自 R2024a 起) |
Disturbance Compensator | Modify control actions to compensate for unknown dynamics and disturbances (自 R2024a 起) |
Ultra Local Model | Estimate nonlinear plant as single or double integrator systems with an affine term that captures unknown dynamics and disturbances (自 R2025a 起) |
主题
自抗扰控制
- 自抗扰控制
为具有未知动态特性和扰动的被控对象设计抗扰控制器。 - 为水箱系统设计自抗扰控制
为水箱模型设计 ADRC,并与增益调度 PID 控制器比较性能。 - 为多输入多输出被控对象设计 ADRC
设计中试规模精馏塔 MIMO 模型的 ADRC,并与模型预测控制器比较性能。 (自 R2023b 起)
扰动补偿
- Control Design and Disturbance Compensation Using Extended State Observers
Estimate and compensate for disturbances and unknown dynamics in linear time-invariant or linear time-varying systems. (自 R2024a 起) - Apply Extended State Observer for Reference Tracking of DC Motor
Improve the disturbance rejection performance of a PID controller using the Extended State Observer block. (自 R2024a 起) - Compensate for Disturbances in Spring-Mass-Damper System
Compensate for disturbances in a spring-mass-damper system using the Disturbance Compensator block. (自 R2024a 起)
超局部模型
- Ultra-Local Model for Disturbance Estimation and Compensation
Estimate disturbances and unmodeled dynamics using ultra-local model. - Ultra-Local Model for System Identification and Output Prediction
Use the Ultra-Local Model block for system identification and output prediction. - Intelligent PID using Ultra Local Model for Ball on Beam Balance
Implement model-free intelligent PID control technique using ultra-local model.
代码生成
- Deploy Controller for SEPIC Converter for PIL Testing
Set up processor in the loop (PIL) testing and profiling of an active disturbance rejection controller for a SEPIC converter. (自 R2024b 起)