Robust optimal motion planning approach to cooperative grasping and transporting using multiple UAVs based on SDRE

In this paper, we consider the problem of controlling a team of Quadrotors that cooperatively grasp and transport a common payload in three dimensions in the presence of external disturbances and parametric uncertainties such as wind field effects. The main contribution of this work is to propose a cooperative control algorithm based on a decentralized strategy. This algorithm consists of two main parts: first calculating the control vectors for each Quadrotor using Moore–Penrose theory and second combining these control vectors with individual control vectors, which are obtained from a closed-loop non-linear robust optimal controller. In this regard, a robust optimal sliding mode controller (ROSMC), which incorporates the state-dependent Riccati equation (SDRE) method with sliding mode control (SMC) technique, is designed. It also has the capability of maximum dynamic load carrying capacity (DLCC) to increase the carrying capacity and the efficiency of the group of Quadrotors. The proposed method inherits the advantages of both approaches including robustness against model uncertainties and high flexibility in designing the control parameters to provide an optimal solution for the non-linear dynamic of the system. The control algorithm is based on the Lyapunov technique, which is able to provide the stability of the end-effecter during tracking of the desired trajectory with acceptable precision. Finally, the simulation results demonstrate the effectiveness of the control strategy for the cooperative Quadrotors to grasp and transport a common payload in various manoeuvres.