Alireza Karimi

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Vaibhav Gupta, Alireza Karimi, Philippe Louis Schuchert

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outputs is approximated by a convex optimization problem involving Linear Matrix Inequalities (LMIs). A very general controller parametrization is used for continuous and discrete-time controllers with matrix transfer function or state-space representation. Numerical results indicate that the proposed data-driven method gives equivalent performance to model-based approaches when a parametric model is available.

2023

Closed-loop data-driven modeling and distributed control for islanded microgrids with input constraints

Alireza Karimi, Seyed Sohail Madani, Dongdong Zheng

In this paper a new nonlinear identification method for microgrids based on neural networks is proposed. The system identification process can be done using the available closed-loop system input/output data recorded during normal operation without additional external excitation, while disturbances between different distributed energy resources are considered to improve the identification accuracy. Moreover, Based on the nonlinear identified model, a novel distributed frequency/voltage regulation and active/reactive power sharing control framework is developed. The new control strategy does not rely on the classical droop -based hierarchical control structure, such that improved transient performance and accurate power sharing for microgrid with mixed lines can be achieved. Furthermore, the anti-windup technique is incorporated into the controller design process to guarantee that the input constraints are satisfied and the voltage deviations are within an acceptable range. The effectiveness of the proposed method is demonstrated via simulations.

PERGAMON-ELSEVIER SCIENCE LTD2022

Data-driven distributed online learning control for islanded microgrids

Alireza Karimi, Seyed Sohail Madani, Dongdong Zheng

In this paper, a new discrete-time data-driven distributed learning control strategy for frequency/voltage regulation and active/reactive power sharing of islanded microgrids is proposed. Instead of using the static droop relationship and the conventional primary-secondary hierarchical control structure, a new control framework is adopted and a neural network is used to learn the control law. The neural network is tuned online using the operational system input/output data with no training phase. As a result, the transient performance of microgrids is improved and a remarkable plug-and-play capability is also achieved. Moreover, the stability of the closed-loop system is analyzed through the Lyapunov approach, where the interactions between different distributed energy resources are considered. The effectiveness of the proposed method is demonstrated by real-time hardware-in-the-loop experiment of a typical microgrid.

2022

Frequency-domain data-driven position-dependent controller synthesis for Cartesian Robots

Alireza Karimi, Philippe Louis Schuchert

Cartesian robots have position-dependent dynamics that should be accounted for in high performance applications. Traditional methods design Linear Time Invariant (LTI) controllers which are robustly stable with respect to position variations, but require a trade-off in performance to account for the changing dynamics. Advanced methods require Linear Parameter Varying (LPV) models and LPV controller design methods that are not well established in industry. On the other hand, classical model-based gain-scheduled technique requires paramet- ric identification, design of high performance controllers for each position, interpolation of the controller parameters and real-time validation of the gain-scheduled controller, which takes costly engineering time. We propose a new approach, using the frequency response of a system at different operating points, to design a Linear Parameter Varying (LPV) controller. The controller parameters are optimised by a convex optimisation algorithm based on second-order cone programming. The approach is applied to an industrial 3-axis Cartesian robot, showing significant improvements over state-of-the-art control design strategies. Data acquisition and controller design can be performed automatically, reducing significantly the engineering costs for controller synthesis

2022

Linear Parameter-Varying Control of A Power-Synchronized Grid-Following Inverter

Behrooz Bahrani, Alireza Karimi

This paper proposes a Linear Parameter-Varying loop-shaping controller for a power-synchronized grid-following inverter (PSGFLI). This control strategy regulates the inverter output active and reactive power at the terminal instead of the point of connection and does not require a phase-locked loop (PLL) for extracting the voltage phase angle. Hence, the prevalent stability issues exhibited when GFLIs are connected to weak grids are not present, and the proposed PSGFLI control strategy can work under both very weak and strong grid conditions without being prone to instability. In this approach, the controller parameters are functions of the operating point and are changed during the real-time operation such that the closed-loop performance is preserved in all operating points. Furthermore, since the grid impedance is a factor in the design process, a robustness analysis against grid impedance estimation error is conducted, and it is shown that discrepancies in the estimated and real grid impedances are unlikely to make the system unstable. The performance of the proposed control design is validated in MATLAB/PLECS and experiments for both strong and weak grids.

2022

Data-Driven LPV Controller Design for Islanded Microgrids

Alireza Karimi, Seyed Sohail Madani

This paper presents a data-driven multivariable Linear Parameter Varying (LPV) controller design method. The synthesis process is based on frequency-domain data corresponding to different operating points of the plant. The performance and also stability constraints for frozen scheduling parameter are convexified around an initial stabilizing controller and solved using a convex optimization solver. This method has been applied to the combined primary and secondary controller design problem of electrical microgrids. The performance of the proposed method has been validated through simulating a microgrid including a synchronous generator, a battery storage and a photo-voltaic unit. The results show that using this method, high performance is achieved in different operating points. Copyright (C) 2021 The Authors.

ELSEVIER2021

Nonlinear Transient Stability Analysis of Phased-Locked Loop Based Grid-Following Voltage Source Converters Using Lyapunov’s Direct Method

Behrooz Bahrani, Alireza Karimi

In this paper, using Lyapunov’s stability theorem, the transient stability conditions for a grid-following Voltage Source Converter (VSC) are found. These conditions take into account both the grid specifications and the VSC’s dynamics. The derived conditions are based on a well-known nonlinear model of the VSC’s Phase-Locked Loop. To evaluate the stability of the nonlinear system, Lyapunov’s direct method is employed. To this end, a new Lyapunov function is proposed, and its characteristics are analysed. Using this Lyapunov function, the domain of attraction of the system’s equilibrium point is calculated. Additionally, a novel system strength index based on the domain of attraction of the system is proposed. The privilege of this index over the conventional indices are absoluteness, VSC’s dynamics consideration, and comparability of different VSCs with each other from a stability point of view. In the end, the correctness of the proposed stability analysis is validated via simulation in Matlab/PLECS and experiment.

2021

Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Alireza Karimi, Seyed Sohail Madani

Power-Hardware-In-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed algorithms and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model via a feedback loop may make the closed-loop system unstable. In this paper, a systematic method is proposed to design a digital filter such that the closed-loop stability of PHIL setup is guaranteed and its performance is optimised. The design of the filter is formulated as a specific controller synthesis problem that maximises the accuracy and ensures a certain robustness margin. The design problem is written as a convex optimization and solved efficiently using available solvers. Due to the data-driven characteristic of the proposed method, there is no need for the model of the Hardware Under the Test (HUT) to guarantee the stability and performance. This method is also extended to a multi-scenario case including different combinations of hardware and simulated systems. The PHIL experimental results validate the performance of the proposed method while satisfying the required stability margin and improving the accuracy significantly compared to conventional filters.

2021

Data-Driven Distributed Combined Primary and Secondary Control in Microgrids

Christoph Manuel Kammer, Alireza Karimi, Seyed Sohail Madani

This paper presents a comprehensive data-driven distributed combined primary/secondary controller design method for microgrids. This method provides transient and steady-state performance including power-sharing and voltage and frequency restoration while guaranteeing stability for fixed communication delay. The measured data is directly used for controller design with no need for knowledge about the order or structure of the system and grid physical parameters. Moreover, no assumption is made on X/R-ratio of feeders. All the control specifications are formulated as frequency-domain constraints on the 2-norm of weighted sensitivity functions. Then, using a recently developed frequency-domain robust control design method, a distributed fixed-structure controller is synthesized in one step. The performance of the obtained controller is validated using Hardware-In-the-Loop (HIL) experiments. The results show considerable improvement in transient performance, while providing power-sharing and voltage and frequency restoration using distributed implementation.

2020