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Riccati iteration: existence, uniqueness, and global attraction of the positive definite fixed point (Prop. 4.4.1, parts 1–3)

Proved
BertsekasDP.riccati_psd_fixed_point_exists_unique_convergent

by jackjburleson · 1 vote · Sep 8, 2026 · Mathlib 0df444a (Lean v4.33.1)

control-theorylinear-quadratic-regulatormatrix-analysisriccati-equation

Let A∈Rn×nA \in \mathbb{R}^{n\times n}A∈Rn×n, B∈Rn×mB \in \mathbb{R}^{n\times m}B∈Rn×m, Q=C⊤C⪰0Q = C^{\top}C \succeq 0Q=C⊤C⪰0 with C∈Rq×nC \in \mathbb{R}^{q\times n}C∈Rq×n, and R≻0R \succ 0R≻0. Assume that (A,B)(A,B)(A,B) is controllable and (A,C)(A,C)(A,C) is observable in the sense of Definition 4.1.1 of Bertsekas, and let

F(P)=A⊤(P−PB(B⊤PB+R)−1B⊤P)A+QF(P) = A^{\top}\Bigl(P - PB\bigl(B^{\top}PB + R\bigr)^{-1}B^{\top}P\Bigr)A + QF(P)=A⊤(P−PB(B⊤PB+R)−1B⊤P)A+Q

be the discrete-time Riccati operator. Then there exists a positive definite matrix PPP such that:

  1. PPP solves the algebraic Riccati equation F(P)=PF(P) = PF(P)=P;
  2. PPP is the unique positive semidefinite fixed point: every P′⪰0P' \succeq 0P′⪰0 with F(P′)=P′F(P') = P'F(P′)=P′ equals PPP;
  3. the Riccati iteration converges from every positive semidefinite start: Fk(P0)→PF^{k}(P_0) \to PFk(P0​)→P as k→∞k \to \inftyk→∞ for every P0⪰0P_0 \succeq 0P0​⪰0.

Proof sketch (Bertsekas, Vol. I, \S4.4): FFF is order-preserving on the symmetric positive semidefinite cone; controllability gives a uniform upper bound Pˉ\bar PPˉ for the iterates Fk(0)F^k(0)Fk(0), which are nondecreasing since F(0)=Q⪰0F(0) = Q \succeq 0F(0)=Q⪰0, hence they converge to some P⪰0P \succeq 0P⪰0, and continuity of FFF gives F(P)=PF(P) = PF(P)=P. Observability shows P≻0P \succ 0P≻0 (an x≠0x \ne 0x=0 with x⊤Px=0x^{\top}Px = 0x⊤Px=0 forces CAjx=0CA^jx = 0CAjx=0 for all jjj, contradicting observability). Minimality of PPP among positive semidefinite fixed points follows from Fk(0)≤Fk(P′)=P′F^k(0) \le F^k(P') = P'Fk(0)≤Fk(P′)=P′, and the attraction property from comparing the iterates from P0P_0P0​ with those from 000 and from any fixed point.

Preamble
import Mathlib
import Definitions.Def_BertsekasRiccatiMap

open Matrix
Formal statement
namespace BertsekasDP

theorem riccati_psd_fixed_point_exists_unique_convergent {n m q : ℕ}
    (A : Matrix (Fin n) (Fin n) ℝ) (B : Matrix (Fin n) (Fin m) ℝ)
    (Q : Matrix (Fin n) (Fin n) ℝ) (R : Matrix (Fin m) (Fin m) ℝ)
    (C : Matrix (Fin q) (Fin n) ℝ)
    (hQ : Q = Cᵀ * C) (hQpsd : Q.PosSemidef) (hR : R.PosDef)
    (hctrb : BertsekasControllablePair A B)
    (hobs : BertsekasObservablePair A C) :
    ∃ P : Matrix (Fin n) (Fin n) ℝ, P.PosDef ∧
      BertsekasRiccatiMap A B Q R P = P ∧
      (∀ P' : Matrix (Fin n) (Fin n) ℝ, P'.PosSemidef →
        BertsekasRiccatiMap A B Q R P' = P' → P' = P) ∧
      (∀ P₀ : Matrix (Fin n) (Fin n) ℝ, P₀.PosSemidef →
        Filter.Tendsto (fun k => (BertsekasRiccatiMap A B Q R)^[k] P₀)
          Filter.atTop (nhds P)) := by sorry

end BertsekasDP
Source
D. P. Bertsekas, Dynamic Programming and Optimal Control, Vol. I, Athena Scientific, 3rd ed., 2005, Section 4.4, Proposition 4.4.1 (parts 1–3); cf. J. C. Willems, Least squares stationary optimal control and the algebraic Riccati equation, IEEE Trans. Automat. Control 16 (1971), no. 6, 621–634.

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