Delay-robust distributed secondary frequency control for next-generation power systems: Stability analysis and controller synthesis

Power systems worldwide are undergoing major transformation to enable a low-carbon future. These developments require new procedures for advanced control to ensure a stable and efficient system operation. Consensus-based distributed secondary frequency control schemes have the potential to ensure real-time frequency restoration and economic dispatch simultaneously in future power systems with significant contribution of renewable energy sources. However, owing to their distributed nature, these control schemes critically depend on communication between different controlled units. Thus, robustness against communication uncertainty is crucial for their reliable operation. In this work, control design and stability analysis of delay-robust secondary frequency control in next-generation power systems are studied. The main contributions of the present thesis can be summarised as follows: (i) A design procedure for a consensus-based secondary frequency controller in microgrids is proposed that ensures robustness with respect to heterogeneous fast-varying communication delays and simultaneously provides the option to trade off the L2-gain performance against the number of required communication links; (ii) The conditions for robust stability of a consensus-based frequency control scheme applied to a power system model with second-order turbine-governor dynamics in the presence of heterogeneous time-varying communication delays and dynamic communication topology are derived; (iii) The performance of the proposed consensus-based secondary frequency controller is analysed in a detailed model capturing the dynamic behaviour of a real system. The results provide insights to the robustness of the closed-loop system with respect to unmodelled (voltage and higher-order generator) dynamics as well as communication delays

Nonlinear control and perturbation compensation in UAV quadrotor

The great interest in the field of flying robotics encouraged a lot of research work to improve its control strategies. This thesis is about modelling and design of controllers and perturbation compensators for a UAV quadrotor. Four approaches are built in this purpose. The first approach is perturbation attenuation system in a UAV quadrotor. Hierarchical Perturbation Compensator (HPC) is built to compensate for system uncertainties, non-modelled dynamics and external disturbances. It comprises three subsystems designed to provide continuous and precise estimation of perturbation. Each subsystem is designed to avoid the drawbacks of the other. This approach has superior proficiency to decrease unknown perturbation either external or internal. The second approach is a Three Loop Uncertainties Compensator (TLUC), designed to estimate unknown time- varying uncertainties and perturbations to reduce their effects and in order to preserve stability. The novelty of this approach is that the TLUC can estimate and compensate for uncertainties and disturbances in three loops made to provide tracking to residual uncertainty in order to achieve a higher level of support to the controller. Exponential reaching law sliding mode controller is proposed and applied. It is integrated based on Lyapunov stability theory to obtain fast response with lowest possible chattering. The performance is verified through analyses, simulations and experiments. The third approach is Feedback Linearization based on Sliding Mode Control (FLSMC). The purpose is to provide nonlinear control that reduces the effect of the highly coupled dynamic behavior and the hard nonlinearity in the quadrotor. The proposed controller uses a Second Order sliding mode Exact Differentiator SOED to estimate the velocity and the acceleration. The fourth approach proposes an improved Non-Singular Terminal Super-Twisting Control for the problem of position and attitude tracking of quadrotor systems. The super-twisting algorithm is an effective control used to provide high precision and less chattering. The proposed method is based on a non-singular terminal sliding surface with new exponent that solves the problem of singularity in terminal sliding mode control. Design procedure and the stability analysis using Lyapunov theory are detailed for the considered approaches. The performance is verified through analyses, simulations and experiments

Distributed model-independent consensus of Euler-Lagrange agents on directed networks

This paper proposes a distributed model-independent algorithm to achieve leaderless consensus on a directed network where each fully-actuated agent has self-dynamics described by Euler–Lagrange equations of motion. Specifically, we aim to achieve consensus of the generalised coordinates with zero generalised velocity. We show that on a strongly connected graph, a model-independent algorithm can achieve the consensus objective at an exponential rate if an upper bound on the initial conditions is known a priori. By model-independent, we mean that each agent can execute the algorithm with no knowledge of the equations describing the self-dynamics of any agent. For design of the control laws which achieve consensus, a control gain scalar and a control gain matrix are required to satisfy several inequalities involving bounds on the matrices of the agent dynamic model, bounds on the Laplacian matrix describing the network topology and the set of initial conditions; design of the algorithm therefore requires some knowledge on the bounds of the agent dynamical parameters. Because only bounds are required, the proposed algorithm offers robustness to uncertainty in the parameters of the multiagent system. We systematically show that additional relative velocity information improves the performance of the controller. Numerical simulations are provided to show the effectiveness of the algorithm.This work was supported by the National Natural Science Foundation of China (grant 61375072), and by Data61-CSIRO (formerly NICTA)

Systems Structure and Control

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc