A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently-developed computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with spherical and rotating earth, hard constraints for desired terminal conditions and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack and bounds on the bank angle. In addition, the terminal constraints are the threedimensional position and velocity vector components at the end of the reentry. Where as the angle of attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

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A dynamic inversion-based three-dimensional nonlinear aiming point guidance law is presented in this paper for reactive collision avoidance of unmanned aerial vehicles. When an obstacle is detected in the close vicinity and collision is predicted, an artificial safety sphere is put around the center of the obstacle. Next, the velocity vector of the vehicle is realigned towards an 'aiming point' on the surface of the sphere in such a way that passing through it can guarantee safe avoidance of the obstacle. The guidance command generation is based on angular correction between the actual and the desired direction of the velocity vector. Note that the velocity vector gets aligned along the selected aiming point quickly (i.e., within a fraction of the available time-to-go), which makes it possible to avoid pop-up obstacles. The guidance algorithm has been verified with simulations carried out both for single obstacles as well as for multiple obstacles on the path and also with different safety sphere sizes around the obstacles. The proposed algorithm has been validated using both kinematic as well as point mass model of a prototype unmanned aerial vehicle. For better confidence, results have also been validated by incorporating a first-order autopilot models for the velocity vector magnitude and directions.

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