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设计、测试和实现控制系统
作为控制系统工程师,您可以在开发的所有阶段使用 matlab® 和 simulink®,包括被控对象建模、控制器设计、自动代码生成部署和系统验证。使用 matlab 和 simulink 控制系统产品,您可以:
使用基本模型、系统辨识或自动参数估计对线性和非线性被控对象动态特性进行建模。
配平、线性化和计算非线性 simulink 模型的频率响应。
使用根轨迹、波特图、lqr、lqg 和其他设计方法,基于被控对象模型设计控制器。
使用时域和频域中的超调、上升时间、相位裕度、增益裕度及其他性能和稳定性特性,以交互方式分析控制系统性能。
自动调节 pid、增益调度和任意 siso 和 mimo 控制系统。
设计和实现稳健的模型预测控制器或使用无模型控制方法,如模型引用自适应控制、极值搜索控制、强化学习和模糊逻辑。
将控制算法部署到嵌入式系统,用于实时控制、调节或参数估计。
设计和测试状态监控与预测性维护算法。
适用产品:控制系统
主题
被控对象建模、系统辨识和参数估计
- control system modeling with model objects (control system toolbox)
build models that represent your control system using model objects. - (system identification toolbox)
collect mimo data, estimate and compare models, and view corresponding model responses. - (system identification toolbox)
perform online parameter estimation for a time-varying arx model at the matlab command line. - inverted pendulum parameter estimation (simulink design optimization)
estimate multiple parameters of a model by iterated estimations.
配平、线性化和频率响应估计
- (simulink control design)
find steady-state operating points that meet specifications by trimming your simulink model using the steady state manager app. - linearize simulink model at model operating point (simulink control design)
linearize a model at its operating point consisting of initial state values and input signals. - (simulink control design)
identify a frequency-domain model for a high-frequency power electronics system using a prbs input signal in model linearizer.
控制设计和调节
- root locus design (control system toolbox)
design a compensator for an electrohydraulic servomechanism using root locus graphical tuning techniques. - design compensator using automated tuning methods (control system toolbox)
tune a compensator using automated tuning methods in control system designer. - tune control systems using systune (control system toolbox)
usesystune
to tune structured controllers for a simple application. - (simulink control design)
use pid tuner to identify a plant model and design a pid controller for a power electronics model that cannot be linearized. - tune gain-scheduled controller using closed-loop pid autotuner block (simulink control design)
use closed-loop pid autotuner block to tune gain-scheduled pid controller for a water-tank model in one simulation.
预测与稳健控制
- (model predictive control toolbox)
design and simulate a model predictive controller for a simulink model using mpc designer. - robust control of active suspension (robust control toolbox)
in this example, use h∞ synthesis to design a controller for a nominal plant model. then, use μ synthesis to design a robust controller that accounts for uncertainty in the model.
自适应与智能控制
- (simulink control design)
design an mrac controller that adapts disturbance model parameters to achieve performance matching an ideal reference model. - design and train agent using reinforcement learning designer (reinforcement learning toolbox)
design and train a dqn agent for a cart-pole system using the reinforcement learning designer app. - design controller for artificial pancreas using fuzzy logic (fuzzy logic toolbox)
design and tune a fis tree to control insulin infusion for type-1 diabetes.
可部署算法
- tune pi controllers using field oriented control autotuner block on real-time systems (motor control blockset)
compute the gain values of pi controllers within the speed and current controllers by using the field oriented control autotuner block. - simulation and code generation using simulink coder (model predictive control toolbox)
simulate your mpc controller in simulink and generate real-time code that uses either double-precision or single-precision signals. - (simulink design optimization)
monitor the condition of an electric vehicle battery in the field with a deployed version of parameter estimation using simulink compiler™.