Chapter 6: Control Systems for Robotics
25 sections
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Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- Classical PID control can be extended through adaptation and gain tuning.
- Robust control ensures performance despite model uncertainty.
- Optimal controllers like LQR balance performance and effort.
- Nonlinear methods such as feedback linearization are essential for real-world dynamics.
- Force and impedance control are key in compliant interaction.
- Underactuated and nonholonomic robots require specialized, often nonlinear control strategies.
Key Concepts
- -- PID Control
- A control methodology integrating Proportional, Integral, and Derivative components to minimize error in a system.
- -- Adaptive Control
- A control strategy that adjusts parameters in real-time to accommodate varying dynamics of the system.
- -- Robust Control
- A method that guarantees system performance under uncertainty and disturbances.
- -- Optimal Control
- A control approach that seeks to minimize a specific cost function while satisfying system constraints.
- -- Feedback Linearization
- A technique that transforms nonlinear dynamics into linear dynamics through coordinate transformation.
- -- Impedance Control
- Control that manages the interaction forces between a robot and its environment by modeling the robot as a mass-spring-damper.
- -- Underactuated Systems
- Systems with fewer actuation inputs than degrees of freedom, requiring control strategies that exploit their natural dynamics.
- -- Nonholonomic Systems
- Systems constrained by non-integrable velocity states, often requiring unique planning and control strategies.
Additional Learning Materials
Supplementary resources to enhance your learning experience.