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。
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SCI 2026 が名古屋で開催され参加しています。 5/23に熊本→小牧（名古屋）に移動しました。FDAに初めて乗りました。 金色の飛行機？ pic.twitter.com/7uP31GNnDA— Hiroshi Okajima (@control_eng_ch) 2026年5月23日 久々に名古屋に来たので、とりあえず、前…
A system identification framework that turns measurement noise into a structured uncertainty description. Cyclic reformulation with period N is applied to LTI systems to construct polytopes from a single experiment, then used for robust H∞…
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…
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…
