Cascade explicit tube model predictive controller: application for a multi-robot system

关键词:  Explicit model predictive control (MPC) · Tube MPC · Cascade controller · Quadrotor · Multi-agent system · Distributed formation control

Key words:  Explicit model predictive control (MPC) · Tube MPC · Cascade controller · Quadrotor · Multi-agent system · Distributed formation control

摘要:

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.

Abstract:

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.