In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),...In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.展开更多
文摘In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.
