Approximation of the minimal robustly positively invariant set for discrete-time LTI systems with persistent state disturbances

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Invariant approximations of the minimal robust. positively invariant set

Published versio

The impact of the input parameterisation on the feasibility of MPC and its parametric solution

Feasibility is an important issue in predictive control, but the influence of many important parameters such as the desired steady-state, or target, the current value of the input are rarely discussed in the literature. This paper makes two contributions. First it gives visibility to the issue that including core parameters such as the target and the current input vastly increases the dimension of the parametric space, with possible consequences on the complexity of any parametric solutions. Secondly, it is shown that a simple re-parameterisation of the d.o.f. to take advantage of reference governor concepts can lead to large increases in feasible volumes, with no increases in the dimension of the required optimisation variables

Prioritised objectives for model predictive control of building heating systems

Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have been widely reported. A key requirement for successful realisation of such approaches is that strategies are formulated in such a way as to be easily adapted to fit a wide range of buildings with little commissioning effort. This paper introduces an MPC-based building heating strategy, whereby the (typically competing) objectives of energy and thermal comfort are optimised in a prioritised manner. The need for balancing weights in an objective function is eliminated, simplifying the design of the strategy. The problem is further divided into supply and demand problems, separating a high order linear optimisation from a low order nonlinear optimisation. The performance of the formulation is demonstrated in a simulation platform, which is trained to replicate the thermal dynamics of a real building using data taken from the building

ENIGMA-A centralised supervisory controller for enhanced onboard electrical energy management with model in the loop demonstration

A centralised smart supervisor (CSS) controller with enhanced electrical energy management (E2-EM) capability has been developed for an Iron Bird Electrical Power Generation and Distribution System (EPGDS) within the Clean Sky 2 ENhanced electrical energy MAnagement (ENIGMA) project. The E2-EM strategy considers the potential for eliminating the 5 min overload capability of the generators to achieve a substantial reduction in the mass of the EPGDS. It ensures optimal power and energy sharing within the EPGDS by interfacing the CSS with the smart grid network (SGN), the energy storage and regeneration system (ESRS), and the programmable load bank 1 secondary distribution board (PLB1 SDU) during power overloads and failure conditions. The CSS has been developed by formalizing E2-EM logic as an algorithm operating in real time and by following safety and reliability rules. The CSS undergoes initial verification using model-in-the-loop (MIL) testing. This paper describes the EPGDS simulated for the MIL testing and details the E2-EM strategy, the algorithms, and logic developed for the ENIGMA CSS design. The CSS was subjected to two test cases using MIL demonstration, and based on the test results, the performance of the ENIGMA CSS is verified and validated

ENIGMA—A Centralised Supervisory Controller for Enhanced Onboard Electrical Energy Management with Model in the Loop Demonstration

A centralised smart supervisor (CSS) controller with enhanced electrical energy management (E2-EM) capability has been developed for an Iron Bird Electrical Power Generation and Distribution System (EPGDS) within the Clean Sky 2 ENhanced electrical energy MAnagement (ENIGMA) project. The E2-EM strategy considers the potential for eliminating the 5 min overload capability of the generators to achieve a substantial reduction in the mass of the EPGDS. It ensures optimal power and energy sharing within the EPGDS by interfacing the CSS with the smart grid network (SGN), the energy storage and regeneration system (ESRS), and the programmable load bank 1 secondary distribution board (PLB1 SDU) during power overloads and failure conditions. The CSS has been developed by formalizing E2-EM logic as an algorithm operating in real time and by following safety and reliability rules. The CSS undergoes initial verification using model-in-the-loop (MIL) testing. This paper describes the EPGDS simulated for the MIL testing and details the E2-EM strategy, the algorithms, and logic developed for the ENIGMA CSS design. The CSS was subjected to two test cases using MIL demonstration, and based on the test results, the performance of the ENIGMA CSS is verified and validated

Control of linear systems with input and state constraints

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Control of linear systems with input and state constraints

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