Input Mapping-Based Model Predictive Control with Event-Triggered Adaptive Strategy for Rigid-Soft Hybrid Manipulator

Key Points

• Improved control occurs through a novel event-triggered adaptive strategy, enhancing system responsiveness and precision.
• The model predictive control framework utilizes input mapping to optimize movement in hybrid manipulator systems, showing significant improvements in dynamic tasks.
• Analysis relies on the implementation of adaptive strategies to manage and respond to system changes and uncertainties effectively.
• This method may enable more efficient control in robotics applications, addressing challenges with actuator dynamics and flexibility.