China
Africa
Explore chapters and articles related to this topic
Design of Microgrids
Published in Sasi K. Kottayil, Smart Microgrids, 2020
H-Infinity Controller: H∞ control is adopted when robust performance is expected in spite of system parameter variations and large disturbances. An optimization process is formulated from the problem which will be subsequently solved by the controller. The design requirements like disturbance rejection, robustness, tracking performance, etc., are to be formulated as constraints in different control loop transfer functions. The weighting functions are selected so as to tune these loops until the desired performance is reached. This control works well even with unbalanced load, exhibits reduced THD and high tracking accuracy and is easy to implement. Slow dynamic response and requirement of multiple control loops are the disadvantages of H∞ controller.
Robustness in Residual Generation
Published in Janos J. Gertler, Fault Detection and Diagnosis in Engineering Systems, 2017
During the past fifteen years, much attention has been paid in the control community to robust controller design, using the so called H-infinity (H∞) approach. Several attempts have also been made at applying this technique to fault detection and isolation, in order to achieve robustness. In this section, we will outline the main ideas of residual generator design by the H∞ methodology, as applied to additive faults and disturbances. We will also comment on some of the limitations of this approach. Because of these and the complex mathematics involved, we will not venture into a full-blown description of the design procedure.
H
Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
In the latter case the problem may be attacked by linear-quadratic game theoretic approach resulting in a set of Riccati equations. H (H infinity) methods may be used in robust stabilization, robust performance design, disturbance attenuation, optimal tracking, model following, optimal sensitivity design, etc. H infinity design See H design.
Nonlinear optimal control of a multi-rotor wind power unit with PMSGs and AC/DC converters)
Published in Journal of Control and Decision, 2023
Gerasimos Rigatos, Pierluigi Siano, Bilal Sari, Masoud Abbaszadeh, Mohamed Assaad Hamida
The linearisation process was repeated at each sampling instance around a temporary operating point that was defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. For the linearised model of the wind power system dynamics, a stabilising H-infinity feedback controller was designed. This controller represents a min–max differential game which takes place between (i) the control inputs of the system that try to minimise a cost function comprising a quadratic term of the state vector's tracking error, (ii) the modelling uncertainty and external perturbation terms which try to maximise this cost functions. To select the feedback gains of the H-infinity controller an algebraic Riccati equation had to be solved at each time-step of the control algorithm. The global stability properties of the control scheme were proven through Lyapunov analysis. Moreover, to implement state estimation-based control without the need to measure the entire state vector of the system, The H-infinity Kalman has been used a robust state estimator. The H-infinity control method retains the advantages of linear optimal control, that is fast and accurate tracking of reference setpoints under moderate variations of the control inputs.
Non-linear optimal control for four-wheel omnidirectional mobile robots
Published in Cyber-Physical Systems, 2020
G. Rigatos, K. Busawon, M. Abbaszadeh, P. Wira
The proposed H-infinity controller implements a solution to the optimal control problem of the omnidirectional robotic vehicle under model uncertainty and external perturbations. Actually, the H-infinity control method represents a min-max differential game in which the controller tries to minimise a quadratic cost function of the state vector’s tracking error, whereas the model uncertainty terms and external perturbations try to maximize this cost function. To compute the feedback gains of a stabilising H-infinity controller an algebraic Riccati equation has to be repetitively solved at each time-step of the control method [34–36]. The stability properties of the control scheme are proven through Lyapunov analysis. First, it is demonstrated that the control loop satisfies the H-infinity tracking performance criterion, which signifies elevated robustness against modelling errors and exogenous disturbances [37,38]. Moreover, it is proven that under moderate conditions the control loop is globally asymptotically stable. Finally, to implement H-infinity feedback control without the need to measure the entire state vector of the mobile robot, the H-infinity Kalman Filter is proposed as a robust state estimator [39,40].
Robust Load Frequency Control of Interconnected Power System in Smart Grid
Published in IETE Journal of Research, 2021
Santosh K. Tripathi, Vijay P. Singh, A. S. Pandey
The H-infinity controller’s performance requirements are based on bounded disparities between the real and nominal plants, resulting in a loop shaping methodology. H-infinity is mainly used for multiple input and multiple output systems. It is observed that the PI controller used won’t be able to reduce disturbances alone in the system. The steady-state error was not minimized with the conventional controller. Here, x is the extrinsic input, which includes the disturbance and the reference signal and r is the controller variable. There are two outputs of the above system, one is y which is the error signal which is to be minimized and another one is measured variables that will be used to control the system.