  We propose a unified framework to fast generate a safe optimal control action
for a new task from existing controllers on Multi-Agent Systems (MASs). The
control action composition is achieved by taking a weighted mixture of the
existing controllers according to the contribution of each component task.
Instead of sophisticatedly tuning the cost parameters and other
hyper-parameters for safe and reliable behavior in the optimal control
framework, the safety of each single task solution is guaranteed using the
control barrier functions (CBFs) for high-degree stochastic systems, which
constrains the system state within a known safe operation region where it
originates from. Linearity of CBF constraints in control enables the control
action composition. The discussed framework can immediately provide reliable
solutions to new tasks by taking a weighted mixture of solved component-task
actions and filtering on some CBF constraints, instead of performing an
extensive sampling to achieve a new controller. Our results are verified and
demonstrated on both a single UAV and two cooperative UAV teams in an
environment with obstacles.
