Simulink에서의 제어 설계

시간 영역 요구 사항과 주파수 영역 요구 사항 지정, PID 이득과 같은 제어기 파라미터 조정

Simulink^® Design Optimization™은 설계 요구 사항을 지정하는 여러 가지 방법을 제공합니다. 검사 블록을 사용하여 기준 추종 및 신호 범위 충족과 같은 일반적인 제어 설계 요구 사항을 지정할 수 있습니다. 그런 다음 응답 최적화기 앱 또는 명령줄에서 이러한 설계 요구 사항을 충족하도록 모델의 제어기 파라미터를 최적화할 수 있습니다.

앱

응답 최적화기

설계 요구 사항을 충족하도록 모델 응답 최적화, 모델 강인성 테스트

블록

Check Against Reference	시뮬레이션하는 동안 모델 신호가 기준 신호를 추종하는지 검사
Check Custom Bounds	Check that model signal satisfies bounds during simulation
Check Step Response Characteristics	Check that model signal satisfies step response bounds during simulation

함수

모두 확장

비용 함수 구성하기

시뮬레이션 시나리오 생성하기

`sdo.SimulationTest`	Simulation scenario description
`setup`	Configure simulation scenario and model for optimization and evaluation (R2024a 이후)
`restore`	Restore simulation scenario and model to their previous state (R2024a 이후)

시간 영역 요구 사항 지정하기

`sdo.requirements.SignalBound`	Piecewise-linear amplitude bound
`sdo.requirements.SignalTracking`	Reference signal to track
`sdo.requirements.StepResponseEnvelope`	Step response bound on signal
`sdo.requirements.PhasePlaneEllipse`	Impose elliptic bound on phase plane trajectory of two signals
`sdo.requirements.PhasePlaneRegion`	Impose region bound on phase plane trajectory of two signals

변수 요구 사항 지정하기

`sdo.requirements.FunctionMatching`	Impose function matching constraint on variable
`sdo.requirements.MonotonicVariable`	Impose monotonic constraint on variable
`sdo.requirements.RelationalConstraint`	Impose relational constraint on pair of variables
`sdo.requirements.SmoothnessConstraint`	Impose bounds on gradient magnitude of variable

주파수 영역 요구 사항 지정하기

`sdo.requirements.BodeMagnitude`	Bode magnitude bound
`sdo.requirements.ClosedLoopPeakGain`	Closed loop peak gain bound
`sdo.requirements.GainPhaseMargin`	Gain and phase margin bounds
`sdo.requirements.OpenLoopGainPhase`	Nichols response bound
`sdo.requirements.PZDampingRatio`	Damping ratio bound
`sdo.requirements.PZNaturalFrequency`	Natural frequency bound
`sdo.requirements.PZSettlingTime`	Settling time bound
`sdo.requirements.SingularValue`	Singular value bound

비용 함수 최적화 구성하기

`sdo.optimize`	설계 최적화 문제 풀기
`sdo.OptimizeOptions`	Optimization option set for `sdo.optimize` function
`sdo.getParameterFromModel`	Get design variables for optimization
`sdo.setValueInModel`	Set design variable value in model
`sdo.getValueFromModel`	Get design variable value from model
`sdo.getModelDependencies`	List of model file and path dependencies
`evalRequirement`	Evaluate design requirement

검사 블록

`getbounds`	Get bounds specified in Check block
`sdo.setCheckBlockEnabled`	Enable or disable all check blocks in model

도움말 항목

최적화 기본 사항

How the Optimization Algorithm Formulates Minimization Problems
When you optimize parameters of a Simulink model to meet design requirements, Simulink Design Optimization software automatically converts the requirements into a constrained optimization problem and then solves the problem using optimization techniques.
계단 응답 요구 사항을 충족하기 위한 설계 최적화(GUI)
응답 최적화기를 사용하여 계단 응답 요구 사항을 충족하도록 제어기 파라미터를 최적화합니다.
Design Optimization to Track Reference Signal (GUI)
Optimize parameters without adding Signal Constraint blocks to the model.
Design Optimization to Meet Frequency-Domain Requirements (GUI)
This example shows how to tune model parameters to meet frequency-domain requirements using the Response Optimizer app.
Design Optimization to Meet Frequency-Domain Requirements (Code)
This example shows how to tune model parameters to meet frequency-domain requirements, using the sdo.optimize command.
Design Optimization Using Frequency-Domain Check Blocks (GUI)
Optimize model parameters to meet frequency-domain design requirements using the Response Optimizer.
Design Optimization to Meet Time-Domain and Frequency-Domain Requirements (GUI)
Interactively tune a controller to satisfy time-domain and frequency-domain design requirements using the Response Optimizer app.
계단 응답 요구 사항을 충족하기 위한 설계 최적화(코드)
명령줄에서 제어기 파라미터를 최적화합니다.
Write a Cost Function
Write a cost function for parameter estimation, response optimization, or sensitivity analysis. The cost function evaluates your design requirements using design variable values.

설계 요구 사항

Supported Design Requirements
Time-domain and frequency-domain requirements.
Specify Time-Domain Design Requirements in the App
Specify time-domain requirements such as lower and upper amplitude bounds, step response bounds, reference signals, elliptical bounds, and custom bounds.
Specify Variable Requirements in the App
Specify monotonic, smoothness, and relational constraints on variables in your model.
Specify Frequency-Domain Design Requirements in the App
Specify frequency-domain requirements, such as gain and phase margin bounds, closed-loop peak response bounds, step-response bounds, and custom bounds.

최적화 속도 개선하기

Skip Model Simulation Based on Parameter Constraint Violation (GUI)
This example shows how to optimize a design and specify parameter-only constraints that prevent the model from being evaluated in an invalid solution space.
Speed Up Response Optimization Using Parallel Computing
Scenarios when you can speed up optimization using parallel computing, and how the speedup happens.
Use Parallel Computing for Response Optimization
Use parallel computing for response optimization in the app, or at the command line.
Use Fast Restart Mode During Response Optimization
This topic shows how to speed up response optimization using Simulink fast restart.
시뮬레이션 중 액셀러레이터 모드 사용하기
Simulink Design Optimization은 Normal 시뮬레이션 모드와 Accelerator 시뮬레이션 모드를 지원합니다.

응답 최적화기 작업

Specify Design Variables for Optimization
Specify continuous and discrete variables to tune in the Response Optimizer app, including initial values and allowed ranges or values.
Specify Signals to Log
Specify signals to log in the Response Optimizer.
Create Linearization I/O Sets
Create linearization input/output sets in the Response Optimizer or Sensitivity Analyzer.
Compare Requirements and Design Variables Using Spider Plot
This example shows how to use a spider plot to compare requirement evaluations before and after optimizing the response.

코드 생성

Generate MATLAB Code for Design Optimization Problems (GUI)
This example shows how to automatically generate a MATLAB® function to solve a design optimization problem.

문제 해결

Optimization Does Not Make Progress

What to do if the optimization stalls or no changes are seen in parameters values.

Optimization Convergence

What to do if the optimization does not satisfy design requirements or takes a long time to converge near a solution, or if the system response becomes unstable.

Optimization Speed and Parallel Computing

What to do if no speedup is seen with parallel computing, if the results are different, or if the optimization stalls.

Undesirable Parameter Values

What to do if optimization gives undesirable parameter values or violates bounds on values.

Reverting to Initial Parameter Values

How to quit optimizing and revert to original values.