Disturbance Compensation
Estimate and compensate for disturbances and unknown dynamics for linear systems
Use estimation techniques that allow you to estimate the states and disturbances of a plant based on the its inputs and outputs.
Blocks
Active Disturbance Rejection Control | Design controller for plants with unknown dynamics and disturbances (Since R2022b) |
Extended State Observer | Estimate states and disturbances of a system (Since R2024a) |
Disturbance Compensator | Modify control actions to compensate for unknown dynamics and disturbances (Since R2024a) |
Ultra Local Model | Estimate nonlinear plant as single or double integrator systems with an affine term that captures unknown dynamics and disturbances (Since R2025a) |
Topics
Active Disturbance Rejection Control
- Active Disturbance Rejection Control
Design a disturbance rejection controller for plants with unknown dynamics and disturbances. - Design Active Disturbance Rejection Control for Water-Tank System
Design ADRC for a water-tank model and compare performance against a gain-scheduled PID controller. - Design ADRC for Multi-Input Multi-Output Plant
Design ADRC for a pilot-scale distillation column MIMO model and compare performance against a model predictive controller. (Since R2023b)
Disturbance Compensation
- 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. (Since R2024a) - 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. (Since R2024a) - Compensate for Disturbances in Spring-Mass-Damper System
Compensate for disturbances in a spring-mass-damper system using the Disturbance Compensator block. (Since R2024a)
Ultra-Local Model
- 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.
Code Generation
- 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. (Since R2024b)