No description available.

In this master’s thesis we study how Model Predictive Control (MPC) can be fitted into an existing control system to handle state constraints. We suggest the use of reference governing based on the predictive control methodology. The platform for the survey is Saabs unmanned helicopter Skeldar. We develop and investigate different Reference Governor(RG) formulations that can be used together with the already existing stabilizing control system. These different setups show various features regarding model predictive control. One setup is complemented with a pre-filter to prevent aggressive actuator control in response to set-point changes, while the other is developed to handle this in the MPC framework. We also show that one of these RGs can be extended to guarantee stability and convergence. Implementation and real time requirements are also considered in this thesis. For this two different QP-solvers have been used for online solving of the optimization problem that arises from the MPC formulations. For evaluation and analysis the solutions are implemented in an advanced simulation environment developed at Saab and in a hardware-in-the-loop avionics test rig for the Skeldar system.

This thesis proposes, validates, and compares low-complexity algorithms for the fast-and-safe charge and balance of Li-ion batteries both for the single cell case and for the case of a serially-connected string of battery cells. The proposed algorithms are based on a reduced-order electrochemical model (Equivalent Hydraulic Model, EHM), and make use of constrained-control strategies to limit the main electrochemical degradation phenomena that may accelerate aging, namely: Lithium plating in the anode and solvent oxidation inthe cathode. To avoid the computational intensiveness of solving an online optimization as in the Model Predictive Control (MPC) framework, this thesis proposes the use of Reference Governor schemes. Variants of both the Scalar Reference Governors (SRG) and the Explicit Reference Governors (ERG) are developed to deal with the non-convex admissible region for the charge of a battery cell, while keeping a low computational burden. To evaluate the performance of the proposed techniques for the single cell case, they are experimentallyvalidated on commercial Turnigy LCO cells of 160 mAh at four different constant temperatures (10, 20, 30 and 40 °C). In the second part of this thesis, the proposed charging strategies are extended to take into account the balance of a serially-connected string of cells. To equalize possible mismatches, a centralized policy based on a shunting grid (active balance) connects or disconnects the cells during the charge. After a preliminary analysis, a simple mixed-integer algorithm was proposed. Since this method is computationally inefficient due to the high number of scenarios to be evaluated, this thesis proposes a ratio-based algorithm based on a Pulse-Width Modulation (PWM) approach. This approach can be used within both MPC and RG schemes. The numerical validations of the proposed algorithms for the case of a string of four battery cells are carried out using a simulator based on a full-order electrochemical model. Numerical validations show that the PWM-like approach charges in parallel all the cells within the pack, whereas the mixed-integer approach charges the battery cells sequentially from the battery cell with the lowest state of charge to the ones with the highest states of charge. On the basis of the simulations, an algorithm based on a mixed logic that allows to charge in a “sequential parallel” approach is proposed. Some conclusions and future directions of research are proposed at the end of the thesis. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished