Related papers: A New Approach in Optimal Control of Step-Down Con…
In this paper, design of current controller for a two quadrant DC motor drive was proposed with the help of model order reduction technique. The calculation of current controller gain with some approximations in the conventional design…
This paper presents a passivity-based control framework for AC-DC converters supplying non-passive Information Technology rack loads in DC data centers. Unlike conventional cascaded proportional-integral controllers that ensure stability…
This work is focused on optimal control of mechanical compression refrigeration systems. A reduced-order state-space model based on the moving boundary approach is proposed for the canonical cycle, which eases the controller design. The…
In this paper we prove optimality of a certain class of Analog to Digital Converters (ADCs), which can be viewed as generalized Delta-Sigma Modulators (DSMs), with respect to a performance measure that can be characterized as the worst-case…
Model predictive control (MPC) has established itself as the primary methodology for constrained control, enabling general-purpose robot autonomy in diverse real-world scenarios. However, for most problems of interest, MPC relies on the…
Many practical applications of optimal control are subject to real-time computational constraints. When applying model predictive control (MPC) in these settings, respecting timing constraints is achieved by limiting the number of…
Control Co-Design (CCD) considers the coupled effects of both the plant and control parameters to optimize a system's closed-loop transient performance during the design stage. This paper presents a new method for CCD with guarantees on…
This paper proposes a gray-box stability analysis mechanism based on data-driven dynamic mode decomposition (DMD) for commercial grid-tied power electronics converters with limited information on its control parameters and topology. By…
This paper presents development of an optimal feedback linearization control (OFLC) for interior permanent magnet (PM) synchronous machines operating in a non steady-sate operating point, i.e., varying torque and speed, to achieve precision…
Constant-power loads are notoriously known to destabilise power systems, such as DC microgrids, due to their negative incremental impedance. This paper equips distributed generation units with decentralised L1 adaptive controllers at the…
An MPC controller uses a model of the dynamical system to plan an optimal control strategy for a finite horizon, which makes its performance intrinsically tied to the quality of the model. When faults occur, the compromised model will…
This paper introduces a novel approach in designing prediction horizons on a generalized predictive control for a DC/DC boost converter. This method involves constructing a closed-loop system model and assessing the impact of different…
A centralized model predictive controller (MPC), which is unaware of local uncertainties, for an affine discrete time nonlinear system is presented. The local uncertainties are assumed to be matched, bounded and structured. In order to…
In this paper, we propose a harmonic-model based control approach for the three-phase grid-tied AC-DC converter. We derive a nonlinear harmonic domain model and demonstrate its efficacy in designing harmonic control with global stability…
The optimal power flow problem plays an important role in the market clearing and operation of electric power systems. However, with increasing uncertainty from renewable energy operation, the optimal operating point of the system changes…
This paper proposes Select-Data-driven Predictive Control (Select-DPC), a new method for controlling nonlinear systems using output-feedback for which data are available but an explicit model is not. At each timestep, Select-DPC employs…
A critical challenge in power conversion in electric vehicles is the efficient use of DC-DC buck converters that need to provide 12-V supply for load systems from 400/800-V batteries. This paper presents a literature review on the…
Parameter design is significant in ensuring a satisfactory holistic performance of power converters. Generally, circuit parameter design for power converters consists of two processes: analysis and deduction process and optimization…
One of the most important challenges facing an electric grid is to incorporate renewables and distributed energy resources (DERs) to the grid. Because of the associated uncertainties in power generations and peak power demands,…
Self-optimizing control is a strategy for selecting controlled variables, where the economic objective guides the selection and design of controlled variables, with the expectation that maintaining the controlled variables at constant…