Bayesian hybrid automata: Reconciling formal methods with metrology

Hybrid system dynamics arises when discrete actions meet continuous behaviour due to physical processes and continuous control. A natural domain of such systems are emerging smart technologies which add elements of intelligence, co-operation, and adaptivity to physical entities. Various flavours of hybrid automata have been suggested as a means to formally analyse dynamics of such systems. In this article, we present our current work on a revised formal model that is able to represent state tracking and estimation in hybrid systems and thereby enhancing precision of verification verdicts.

Model Predictive Control of Fixed Wing Aircraft Using a Disturbance Observer Approach

This paper develops a novel cascading Proportional-Integral-Derivative (PID) with Model Predictive Control (MPC) formulation for lateral control of a fixed wing aircraft in the presence of a constant load disturbance, with the consideration of actuator constraints. A Constrained Quadratic Programming (QP) problem is used to solve this MPC problem, via the Primal-Dual procedure. Furthermore, a disturbance observer is utilized to estimate this disturbance so that the setpoint calculation can be adjusted accordingly. Numerical simulations demonstrate steady-state tracking of the aircraft’s roll angle whilst rejecting this disturbance. In addition, heading (yaw) control is implemented via the outer PID loop, and perfect tracking is achieved for this as well. Throughout the entire simulation, the aircraft’s control inputs (aileron and rudder) do not violate their position and rate constraints, thus demonstrating the successful performance of the QP algorithm.