Tuning machine parameters of particle accelerators is a repetitive and time-consuming task that challenging to automate. While many off-the-shelf optimization algorithms are available, in practice their use limited because most methods do not account for safety-critical constraints each iteration, such as loss signals or step-size limitations. One notable exception safe Bayesian optimization, w...