File control/src/Controller/LinearSMCimproved.hpp#

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General interface to define an actuator.


typedef std::shared_ptr<boost::circular_buffer<SP::SiconosVector>> BufferOfVectors#
class LinearSMCimproved : public LinearSMC

Public Functions

LinearSMCimproved(SP::ControlSensor sensor)



sensor – the ControlSensor feeding the Actuator

LinearSMCimproved(SP::ControlSensor sensor, SP::SimpleMatrix B, SP::SimpleMatrix D = std::shared_ptr<SimpleMatrix>())

Constructor with all the data.

  • sensor – the ControlSensor feeding the Actuator

  • B – the B matrix in the FirstOrderLinearR

  • D – the D matrix in the FirstOrderLinearR

virtual ~LinearSMCimproved()


virtual void initialize(const NonSmoothDynamicalSystem &nsds, const Simulation &s)

Initialize Controller.

  • nsds – current nonsmooth dynamical system

  • s – current simulation setup

virtual void actuate()

Compute the new control law at each event Here we are using the following formula: TODO.

inline void setPerturbationPrediction(double ub = std::numeric_limits<double>::quiet_NaN())

Enable perturbation prediction.

inline const SiconosVector &up() const

Get the control input _up, acting against matched perturbations.


a reference to _up

void setPredictionOrder(unsigned int order)

Set the order of the prediction.

  • 0 -> the predicted value is the same as the one we measured

  • 1 -> \( \widetilde{Cp_{k+1}} = 2Cp_k - Cp_{k-1} \)

  • 2 -> \( \widetilde{Cp_{k+1}} = 3Cp_k - 3Cp_{k-1} + Cp_{k-2} \)


order – the order of the prediction

Protected Functions

void predictionPerturbation(const SiconosVector &xTk, SimpleMatrix &CBstar)#

Predict the effect of the perturnation during the next timestep.

  • xTk – available state at the current time instant

  • CBstar – matrix \( CB^{*} \)

Protected Attributes

bool _predictionPerturbation#

try to predict the perturbation

bool _inDisceteTimeSlidingPhase#

boolean to determine if we are in the discrete-time sliding phase

BufferOfVectors _measuredPert#

Vector to store previous values of the perturbation.

BufferOfVectors _predictedPert#

Vector of predicted values for the perturbation.

double _ubPerturbation#

Upper bound on the norm2 of the perturbation.

SP::SiconosVector _up#

Control input to counteract the effect of the perturbation.

Private Functions

inline LinearSMCimproved()#

default constructor