An LMI-based design framework for multirate steady-state Kalman filters using cyclic reformulation. Addresses the semidefinite measurement noise covariance in systems with sensors at different sampling rates (e.g., GPS at 1 Hz + wheel spee…

Guide to all articles: Control engineering, Control theory, Research, MATLAB code, and Video lectures. 制御工学ブログの全記事ガイドです：制御工学の記事へのリンク，論文執筆・プレゼン記事もあります。

A tutorial on kernel-based regularized system identification. Explains stable spline, tuned-correlated, and diagonal-correlated kernels, hyperparameter tuning via empirical Bayes, and MATLAB implementation with impulseest.

Compare IMC, Smith Predictor, Disturbance Observer, 2-DOF control, and Model Error Compensator (MEC). Structural comparison, selection guidelines, and connections to robust control engineering.

A comprehensive tutorial on state feedback control and state-space design for control systems. Covers pole placement, LQR optimal regulators, integral-type servo systems, LMI-based design, observer-based feedback with the separation princi…

The 2-DOF conditional feedback structure is the structural origin of MEC. Setting T = P_M yields MEC, which is equivalent to 2-DOF control for linear systems with feedforward input. MEC extends further to non-minimum-phase and nonlinear sy…

Structural comparison of Internal Model Control (IMC) and Model Error Compensator (MEC). Both use the plant-model output difference, but IMC designs the controller while MEC adds robustness to existing systems.

A survey of Model Error Compensator (MEC) research by independent groups worldwide. Covers applications to quadcopters, teleoperation, underwater robots, power electronics, data-driven tuning with FRIT and Smart MBD, and theoretical analys…

Apply the Model Error Compensator (MEC) to nonlinear systems for robust feedback linearization. Unlike standard feedback linearization, MEC does not require exact model knowledge or full state measurement. The output-feedback structure ach…

How to apply the Model Error Compensator (MEC) to non-minimum phase systems using a parallel feedforward compensator. Non-minimum phase plants have unstable zeros that prevent standard high-gain compensation. The PFC approach resolves this…

Learn how to add robustness to existing PID control systems using the Model Error Compensator (MEC). MEC is a simple add-on compensator that suppresses the effect of model uncertainty and parameter variations without modifying the PID cont…

A tutorial on classical parametric system identification. Explains ARX, ARMAX, Output-Error, and Box-Jenkins model structures, the prediction error method (PEM) for parameter estimation, model order selection, and MATLAB implementation. In…

A tutorial on subspace identification methods for control systems. Explains N4SID, MOESP, and CVA algorithms, model order selection via SVD, and MATLAB implementation. Includes connections to multirate and LPTV system identification resear…

A comprehensive guide to system identification in control engineering. Covers parametric methods, subspace identification (N4SID), kernel-based estimation, multirate systems, and data-driven control. With MATLAB code and links to research …

A detailed comparison between Model Error Compensator (MEC) and Disturbance Observer (DOB) for robust control. Covers structural differences, inverse model requirements, applicability to non-minimum phase and nonlinear systems, and practic…

A comprehensive guide to the H-infinity filter for robust state estimation. Covers the worst-case optimization formulation, LMI-based design with Bounded Real Lemma, comparison with Kalman filter, pole placement constraints, and extensions…

A comprehensive guide to the Kalman filter for state estimation. Covers the prediction-update algorithm, steady-state Kalman filter, Kalman-Bucy filter, tuning of Q and R, Extended and Unscented Kalman filters, and multi-rate Kalman filter…

A comprehensive guide to state observers and state estimation in control systems. Covers Luenberger observers, Kalman filters, H-infinity filters with LMI design, multi-rate state estimation, and outlier-robust MCV observers. Includes link…

Estimation of robust invariant set for discrete-time switched linear systems with peak-bounded disturbances. A novel method combining recursive state updating and robust invariant ellipsoid achieves less conservative estimation.

Observer-based feedback controller design for multi-rate systems where sensors and actuators operate at different sampling rates. Using cyclic reformulation and LMI optimization of the l2-induced norm, both observer gains and feedback gain…

System identification algorithm for multirate sensing environments using cyclic reformulation and subspace identification. Proposes a method to identify plant models from input-output data when sensors have different sampling rates, withou…

This article explains cyclic reformulation-based system identification for LPTV systems. A subspace identification method with state coordinate transformation recovers periodic time-varying parameters without requiring periodic inputs. Bas…

This article explains the tracking performance limitation for 1-DOF control systems with unstable plants, extending the achievable-output-set approach from 2-DOF systems. The closed-form result separates the contributions of unstable zeros…

MSCS 2026 で富山に来ています。今年度３回目です。 MSCS 2026 新幹線ができて以降、鉄道に乗ったのははじめてです。 小中の同級生8名で飲みました。 pic.twitter.com/tLZPTWHuJj — Hiroshi Okajima (@control_eng_ch) 2026年3月2日 ワークショップ前に、富…

This article explains the MEC design with parallel feedforward compensator for MIMO non-minimum phase systems with polytopic uncertainties, based on SICE JCMSI 2022. LMI-based H-infinity analysis for both continuous- and discrete-time syst…

This article explains a design method for the Model Error Compensator (MEC) for systems with polytopic-type uncertainty and disturbances, based on SICE JCMSI 2021. LMI-based H-infinity analysis combined with particle swarm optimization ena…

This article explains the Model Error Compensator (MEC) with a parallel feed-forward filter (PFF) for non-minimum-phase plants with unstable zeros and time delays, based on SICE JCMSI 2017. Design methods for PFF and compensator using PSO …

This article explains a compensator design method that minimizes the modeling gap between a nominal model and the actual plant, proposed in SICE JCMSI 2013. The compensator includes the nominal model internally and feeds back the output di…

This article explains the dynamic quantizer design method for networked control systems under communication rate constraints, published in IEEE Transactions on Automatic Control (2016). The method combines invariant set analysis and partic…

This article explains a design method for delta-sigma data conversion systems with a pre-filter that separately handles quantization noise and signal distortion. The pre-filter and post-filter are designed using particle swarm optimization…