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Chapter 625 sections
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.
A control methodology integrating Proportional, Integral, and Derivative components to minimize error in a system.
A control strategy that adjusts parameters in real-time to accommodate varying dynamics of the system.
A method that guarantees system performance under uncertainty and disturbances.
A control approach that seeks to minimize a specific cost function while satisfying system constraints.
A technique that transforms nonlinear dynamics into linear dynamics through coordinate transformation.
Control that manages the interaction forces between a robot and its environment by modeling the robot as a mass-spring-damper.
Systems with fewer actuation inputs than degrees of freedom, requiring control strategies that exploit their natural dynamics.
Systems constrained by non-integrable velocity states, often requiring unique planning and control strategies.