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283 lines
7.3 KiB
283 lines
7.3 KiB
/*
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* This file is part of ACADO Toolkit.
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*
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* ACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.
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* Copyright (C) 2008-2014 by Boris Houska, Hans Joachim Ferreau,
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* Milan Vukov, Rien Quirynen, KU Leuven.
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* Developed within the Optimization in Engineering Center (OPTEC)
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* under supervision of Moritz Diehl. All rights reserved.
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*
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* ACADO Toolkit is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 3 of the License, or (at your option) any later version.
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*
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* ACADO Toolkit is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with ACADO Toolkit; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*
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*/
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/**
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* \file include/acado/noise/gaussian_noise.hpp
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* \author Hans Joachim Ferreau, Boris Houska
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*/
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#ifndef ACADO_TOOLKIT_GAUSSIAN_NOISE_HPP
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#define ACADO_TOOLKIT_GAUSSIAN_NOISE_HPP
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#include <acado/noise/noise.hpp>
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BEGIN_NAMESPACE_ACADO
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/**
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* \brief Generates pseudo-random Gaussian noise for simulating the Process.
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*
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* \ingroup BasicDataStructures
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*
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* The class GaussiaNoise generates pseudo-random Gaussian noise
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* for simulating the Process within the SimulationEnvironment.
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*
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* \author Hans Joachim Ferreau, Boris Houska
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*/
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class GaussianNoise : public Noise
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{
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//
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// PUBLIC MEMBER FUNCTIONS:
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//
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public:
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/** Default constructor.
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*/
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GaussianNoise( );
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/** Constructor which takes mean value and variance of the random variable.
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* The dimension of these limit vector determine the dimension of the
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* random variable.
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*
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* @param[in] _mean Mean value for each component.
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* @param[in] _variance Variance for each component.
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*/
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GaussianNoise( const DVector& _mean,
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const DVector& _variance
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);
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/** Constructor which takes the dimension of the random variable as well as
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* as common values for the mean value and variance of the random variable.
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*
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* @param[in] _dim Dimension of random variable.
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* @param[in] _mean Mean value for each component.
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* @param[in] _variance Variance for each component.
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*/
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GaussianNoise( uint _dim,
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double _mean,
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double _variance
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);
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/** Copy constructor (deep copy).
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*
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* @param[in] rhs Right-hand side object.
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*/
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GaussianNoise( const GaussianNoise& rhs
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);
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/** Destructor.
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*/
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virtual ~GaussianNoise( );
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/** Assignment Operator (deep copy)
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*
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* @param[in] rhs Right-hand side object.
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*/
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GaussianNoise& operator=( const GaussianNoise& rhs
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);
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/** Clone constructor (deep copy).
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*
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* \return Pointer to deep copy of base class type
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*/
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virtual GaussianNoise* clone( ) const;
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/** Clone constructor for a given noise component (deep copy).
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*
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* @param[in] idx Right-hand side object.
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*
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* \return Pointer to deep copy of base class type
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*/
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virtual GaussianNoise* clone( uint idx
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) const;
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/** Assigns new mean values to the random variable.
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*
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* @param[in] _mean New mean value for each component.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_VECTOR_DIMENSION_MISMATCH
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*/
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inline returnValue setMeans( const DVector& _mean
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);
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/** Assigns new mean values to the random variable.
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*
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* @param[in] _mean New common mean value for all components.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_INVALID_ARGUMENTS
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*/
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inline returnValue setMeans( double _mean
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);
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/** Assigns new mean value on the component of the random variable
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* with given index.
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*
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* @param[in] idx Index of component.
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* @param[in] _mean New mean value.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_INDEX_OUT_OF_BOUNDS
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*/
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inline returnValue setMean( uint idx,
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double _mean
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);
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/** Assigns new variances to the random variable.
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*
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* @param[in] _variance New variances for each component.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_VECTOR_DIMENSION_MISMATCH
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*/
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inline returnValue setVariances( const DVector& _variance
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);
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/** Assigns new variances to the random variable.
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*
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* @param[in] _variance New common variance for all components.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_INVALID_ARGUMENTS
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*/
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inline returnValue setVariances( double _variance
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);
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/** Assigns new variance on the component of the random variable
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* with given index.
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*
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* @param[in] idx Index of component.
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* @param[in] _variance New variance.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_INDEX_OUT_OF_BOUNDS
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*/
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inline returnValue setVariance( uint idx,
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double _variance
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);
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/** Initializes noise generation and performs a couple of consistency checks.
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* Initialization of the pseudo-random number generator can be based on
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* a seed in order to allow exact reproduction of generated noise. If seed
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* is not specified (i.e. 0), a seed is obtain from the system clock.
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*
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* @param[in] seed Seed for pseudo-random number generator.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_INVALID_NOISE_SETTINGS, \n
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* RET_NO_NOISE_SETTINGS
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*/
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virtual returnValue init( uint seed = 0
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);
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/** Generates a single noise vector based on current internal settings.
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*
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* @param[out] _w Generated noise vector.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_BLOCK_NOT_READY, \n
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* RET_VECTOR_DIMENSION_MISMATCH
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*/
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virtual returnValue step( DVector& _w
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);
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/** Generates a noise vector sequence based on current internal settings.
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* Noise is generated for each grid point of the VariablesGrid passed.
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*
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* @param[in,out] _w Generated noise vector sequence.
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*
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* \return SUCCESSFUL_RETURN, \n
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* RET_BLOCK_NOT_READY, \n
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* RET_VECTOR_DIMENSION_MISMATCH
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*/
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virtual returnValue step( VariablesGrid& _w
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);
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/** Returns mean values of the random variable.
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*
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* \return Mean values of the random variable
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*/
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inline const DVector& getMean( ) const;
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/** Returns variances of the random variable.
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*
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* \return Variances of the random variable
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*/
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inline const DVector& getVariance( ) const;
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//
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// PROTECTED MEMBER FUNCTIONS:
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//
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protected:
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/** Returns a pseudo-random number based on a Gaussian distribution with
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* given mean and variance.
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*
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* @param[in] _mean Mean value of Gaussian distribution.
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* @param[in] _variance Variance of Gaussian distribution.
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*
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* \return Gaussian distributed pseudo-random number
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*/
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double getGaussianRandomNumber( double _mean,
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double _variance
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) const;
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//
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// PROTECTED MEMBERS:
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//
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protected:
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DVector mean; /**< Mean value for each component. */
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DVector variance; /**< Variance for each component. */
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};
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CLOSE_NAMESPACE_ACADO
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#include <acado/noise/gaussian_noise.ipp>
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#endif // ACADO_TOOLKIT_GAUSSIAN_NOISE_HPP
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/*
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* end of file
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*/
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