  We consider robust control synthesis for linear systems with complex
specifications that are affected by uncertain disturbances. This work is
motivated by autonomous systems interacting with partially known, time-varying
environments. Given a specification in bounded linear temporal logic, we
propose a method to synthesize control policies that fulfill the specification
for all considered disturbances, where the disturbances affect the atomic
propositions of the specification. Our approach relies on introducing affine
disturbance feedback policies and casting the problem as a bilinear
optimization problem. We introduce an inner approximation of the constraint set
leading to a mixed-integer quadratic program that can be solved using
general-purpose solvers. The framework is demonstrated on a numerical case
study with applications to autonomous driving.
