自适应控制设计
设计能够适应不断变化的过程信息的控制器
自 R2021a 起
自 R2021a 起
如果控制系统包含随时间变化的不确定性,如未建模的系统动态特性和扰动,则自适应控制器可以通过实时调整其参数来补偿变化的过程信息。通过执行此操作,此类控制器可以实现期望的参考跟踪,即使被控对象动态中存在不确定性也是如此。
Simulink® Control Design™ 软件为以下实时自适应控制方法提供几个 Simulink 模块。
极值搜索控制 - 无模型自适应,用于最大化从控制系统派生的目标函数
模型参考自适应控制 - 自适应,用于跟踪已知参考模型的输出
基于 ESO 的扰动补偿 - 无模型自适应,用于拒绝被控对象的内部和外部扰动
模块
Extremum Seeking Control | Compute controller parameters in real time by maximizing objective function |
Model Reference Adaptive Control | Compute control actions to make controlled system track reference model (自 R2021b 起) |
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) |
主题
极值搜索控制
- Extremum Seeking Control
Update controller parameters to maximize an objective function in the presence of unknown system dynamics. - Extremum Seeking Control for Reference Model Tracking of Uncertain Systems
Track a reference plant model by adapting feedforward and feedback gains for an uncertain dynamical system. - Anti-Lock Braking Using Extremum Seeking Control
Design an extremum seeking controller that maximizes the friction coefficient of an ABS system to achieve the shortest stopping distance.
模型参考自适应控制
- 模型参考自适应控制
计算控制动作,使不确定的受控系统能够跟踪给定参考被控对象模型的行为。 - Model Reference Adaptive Control of Satellite Spin
Design an MRAC controller that adapts plant uncertainty model parameters to achieve performance that matches an ideal reference model. - 一阶系统的间接模型参考自适应控制
设计一个间接 MRAC 控制器,用于估计未知一阶系统的属性。 - Indirect MRAC Control of Mass-Spring-Damper System
Design an indirect MRAC controller that estimates the parameters of an unknown MIMO system.
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。 - Design Active Disturbance Rejection Control for BLDC Speed Control Using PWM
Design ADRC for a brushless DC motor speed controller using pulse width modulation.
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)
滑动模式控制
- Sliding Mode Control Design for Mass-Spring-Damper System
A sliding mode controller defines a sliding surface that the system state converges to and remains on. (自 R2024a 起) - Sliding Mode Control Design for a Robotic Manipulator
Create a sliding mode controller for a robotic manipulator with two actuated joints. (自 R2024a 起)
迭代学习控制
- Model-Free Iterative Learning Control of SISO System
Implement an ILC controller to improve closed-loop trajectory tracking performance. (自 R2024a 起)