proximal-riccati.hpp

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#pragma once
 
#include "riccati-base.hpp"
#include "riccati-kernel.hpp"
 
namespace aligator {
namespace gar {

template <typename _Scalar>
class ProximalRiccatiSolver : public RiccatiSolverBase<_Scalar> {
public:
  using Scalar = _Scalar;
  ALIGATOR_DYNAMIC_TYPEDEFS_WITH_ROW_TYPES(Scalar);
  using Base = RiccatiSolverBase<Scalar>;
  using StageFactorVec = std::vector<StageFactor<Scalar>>;
  StageFactorVec datas;
 
  using Kernel = ProximalRiccatiKernel<Scalar>;
  using StageFactorType = typename Kernel::StageFactorType;
  using value_t = typename StageFactorType::value_t;
  using kkt0_t = typename Kernel::kkt0_t;
  using KnotType = LqrKnotTpl<Scalar>;
 
  explicit ProximalRiccatiSolver(const LqrProblemTpl<Scalar> &problem);

  bool backward(const Scalar mudyn, const Scalar mueq);
 
  bool forward(std::vector<VectorXs> &xs, std::vector<VectorXs> &us,
               std::vector<VectorXs> &vs, std::vector<VectorXs> &lbdas,
               const std::optional<ConstVectorRef> &theta = std::nullopt) const;
 
  void cycleAppend(const KnotType &knot);
  VectorRef getFeedforward(size_t i) { return datas[i].ff.matrix(); }
  RowMatrixRef getFeedback(size_t i) { return datas[i].fb.matrix(); }
 
  kkt0_t kkt0;     //< initial stage KKT system
  VectorXs thGrad; //< optimal value gradient wrt parameter
  MatrixXs thHess; //< optimal value Hessian wrt parameter
 
protected:
  const LqrProblemTpl<Scalar> *problem_;
};
 
#ifdef ALIGATOR_ENABLE_TEMPLATE_INSTANTIATION
extern template class ProximalRiccatiSolver<context::Scalar>;
#endif
 
} // namespace gar
} // namespace aligator