Single-Input Single-Output Nonlinear Robotic Dynamic Systems

To address the requirements of input-output nonlinear robotic dynamic systems, we developed a novel control approach that enables precise trajectory tracking while ensuring all signals remain within acceptable bounds. This methodology not only resolves trajectory tracking deficiencies but also guarantees system stability and reliability through Lyapunov-based stability analysis implemented in the control algorithm. The robustness against uncertainties and disturbances is achieved by incorporating adaptive control techniques and disturbance observers in the code architecture. Through system modeling and optimization of control algorithms featuring real-time parameter adaptation loops, we achieve efficient control of nonlinear robotic dynamics. The core implementation includes trajectory error minimization functions using gradient descent optimization and signal bounding checks through conditional saturation blocks. This approach, while demonstrated for robotic systems, can be extended to other control applications through modular code design, providing an effective solution framework for practical implementations.