Estimation of input impulses by means of continuous finite memory observers. - Per Mattsson; Alexander Medvedev (ACC, 2012)

Analysis of a pulse-modulated model of endocrine regulation with time-delay. - Alexander N. Churilov; Alexander Medvedev; Per Mattsson (CDC, 2012)

Finite-dimensional reducibility of time-delay systems under pulse-modulated feedback. - Alexander N. Churilov; Alexander Medvedev; Per Mattsson (CDC, 2013)

State estimation in linear time-invariant systems with unknown impulsive inputs. - Per Mattsson; Alexander Medvedev (ECC, 2013)

Recursive identification of Hammerstein models. - Per Mattsson; Torbjörn Wigren (ACC, 2014)

Discrete-time modeling of a hereditary impulsive feedback system. - Alexander N. Churilov; Alexander Medvedev; Per Mattsson (CDC, 2014)

Periodical Solutions in a Pulse-Modulated Model of Endocrine Regulation With Time-Delay. - Alexander N. Churilov; Alexander Medvedev; Per Mattsson (IEEE Trans. Autom. Control., 2014)

Pulse-modulated model of testosterone regulation subject to exogenous signals. - Per Mattsson; Alexander Medvedev; Zhanybai T. Zhusubaliyev (CDC, 2016)

Convergence analysis for recursive Hammerstein identification. - Per Mattsson; Torbjörn Wigren (Autom., 2016)

Recursive Identification Method for Piecewise ARX Models: A Sparse Estimation Approach. - Per Mattsson; Dave Zachariah; Petre Stoica (IEEE Trans. Signal Process., 2016)

Recursive nonlinear-system identification using latent variables. - Per Mattsson; Dave Zachariah; Petre Stoica (Autom., 2018)

Flexible Models for Smart Maintenance. - Per Mattsson; Dave Zachariah; Niclas Björsell (ICIT, 2019)

Willems' fundamental lemma based on second-order moments. - Mina Ferizbegovic; Håkan Hjalmarsson; Per Mattsson; Thomas B. Schön (CDC, 2021)

Robust nonlinear set-point control with reinforcement learning. - Ruoqi Zhang; Per Mattsson; Torbjörn Wigren (ACC, 2023)

Observer-Feedback-Feedforward Controller Structures in Reinforcement Learning. - Ruoqi Zhang; Per Mattsson; Torbjörn Wigren (CoRR, 2023)

Aiding reinforcement learning for set point control. - Ruoqi Zhang; Per Mattsson; Torbjörn Wigren (CoRR, 2023)

Structured state-space models are deep Wiener models. - Fabio Bonassi; Carl R. Andersson; Per Mattsson; Thomas B. Schön (CoRR, 2023)

Regularized Linear Regression via Covariance Fitting. - Per Mattsson; Dave Zachariah; Petre Stoica (IEEE Trans. Signal Process., 2023)

Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior [Lecture Notes]. - Per Mattsson; Dave Zachariah; Petre Stoica (IEEE Signal Process. Mag., 2023)

Learning state observers for recurrent neural network models. - Fabio Bonassi; Carl R. Andersson; Per Mattsson; Thomas B. Schön (CDC, 2024)

Safe Output Feedback Improvement with Baselines. - Ruoqi Zhang; Per Mattsson; Dave Zachariah (CDC, 2024)

A Model Predictive Control Approach to Motion Planning in Dynamic Environments. - Bernhard Wullt; Per Mattsson; Thomas B. Schön; Mikael Norrlöf (ECC, 2024)

Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning. - Ruoqi Zhang; Ziwei Luo; Jens Sjölund; Thomas B. Schön; Per Mattsson (NeurIPS, 2024)

On the Equivalence of Direct and Indirect Data-Driven Predictive Control Approaches. - Per Mattsson; Fabio Bonassi; Valentina Breschi; Thomas B. Schön (IEEE Control. Syst. Lett., 2024)

Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles. - Ruoqi Zhang; Ziwei Luo; Jens Sjölund; Per Mattsson; Linus Gisslén; Alessandro Sestini (CoG, 2025)

Convergence in On-line Learning of Static and Dynamic Systems. - Torbjörn Wigren; Ruoqi Zhang; Per Mattsson (CoRR, 2025)

Probabilistic Bubble Roadmap. - Bernhard Wullt; Mikael Norrlöf; Per Mattsson; Thomas B. Schön (CoRR, 2025)