Observer Design & Implementation in Python | Motor Control Example Explained скачать в хорошем качестве

Observer Design & Implementation in Python | Motor Control Example Explained

Link to Python Code: https://github.com/MCIMP-book/mcimp/b... Want to estimate hidden states of a system when not everything is measurable? That’s exactly what an observer is for. In this video, we walk through the core concepts of observer design and show you how to implement one in Python—with a hands-on example using a DC motor model. From observability to Luenberger observer design, you’ll get both the theoretical overview and practical code you can adapt to your own projects. 🔧 What’s Inside: • What is an observer, and why do we need one? • Luenberger observer: design and intuition • Implementing observers in Python with numpy, scipy, and control libraries • Realistic motor control example: estimate speed from voltage input and noisy output • Visualizing estimation error and observer performance 🐍 Tools Used: • Python • NumPy & SciPy • python-control library • Matplotlib for visualization 📘 Perfect for: • Students learning control systems or working on senior design • Engineers prototyping model-based estimation • Anyone transitioning from theory to Python-based implementation Link to slides: https://faculty.washington.edu/chx/te... Tags: Observer Design, Python Control, State Estimation, Motor Control, Luenberger Observer, DC Motor Model, State Space, Observability, Control Systems, Engineering Education, System Dynamics, Modern Control, MATLAB to Python, Feedback Control, Robotics, Electrical Engineering, Python-control, SciPy, NumPy