Tuning and validation of complex control systems

In recent years, we have been developing specialised simulation- and optimisation-based analysis tools for tuning and validation of complex control systems. It is well known that the vast majority of the budget for any prototype design is spent in this activity. We are particularly interested in assessing the robust performance of complex realistic, industrial-standard controllers for different prototypes, mainly in the area of aerospace applications, with large numbers of uncertainties, either epistemic or aleoteric, associated with the representative model. It is imperative for the clearance of a design, to have certain identified variables - normally the control signals and variables associated with system safety in the presence of hundreds of uncertain parameters - respect certain a-priori defined limits all the time to ensure the satisfactory safe operation and thus success of the mission. 

At Exeter, we develop analysis tools (Worst Case Analysis Tools: WCAT - II) to address this crucial problem, which relies on a suite of single- and multi-objective optimisation algorithms and polynomial chaos surrogate modelling. The applications/missions that we have been investigating include flight control, attitude control of satellites (for Earth observation), control laws for the European reusable launch vehicle (RLV), integrated guidance, navigation and control (GNC) of autonomous rendezvous in Mars Sample Return (MSR), and GNC of Entry, Descent and Landing Systems (EAGLE). To respect and protect the legacy controllers and models from industry, the proposed tools treat them as 'black-box' with access limited to certain input and output variables.

We are also interested in tuning the legacy controllers of a mission efficiently to suit a related but different mission, such that multiple desired objects are robustly met, and the solution is obtained in a cost-effective manner.

Worst Case Analysis Tools (WCAT)

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