Nonlinear Optimal Control for a Gas Compressor Actuated by a Five-Phase Induction Motor

Author:

Rigatos G.1ORCID,Abbaszadeh M.2,Sari B.3,Siano P.4

Affiliation:

1. 1 Unit of Industrial Automation, Industrial Systems Institute , Rion Patras 26504 , Greece

2. 2 Department of ECS Engineering , Rensselaer Polytechnic Institute , New York , USA

3. 3 Department of Electrical Engineering , University of Setif I , Setif , Algeria

4. 4 Department of Innovation Systems , University of Salerno , Fisciano , Italy

Abstract

Abstract The article proposes a nonlinear optimal control method for the dynamic model of a gas centrifugal compressor being actuated by a five-phase induction motor (5-phase IM). To achieve high torque and high power in the functioning of gas compressors, 5-phase IM appear to be advantageous in comparison to three-phase synchronous or asynchronous electric machines. The dynamic model of the integrated compression system, which comprises the gas compressor and the 5-phase IM, is first written in a nonlinear and multivariable state-space form. It is proven that the electrically driven gas-compression system is differentially flat. Next, this system is approximately linearised around a temporary operating point that is recomputed at each sampling interval. The linearisation is based on first-order Taylor series expansion and uses the computation of the Jacobian matrices of the state-space model of the integrated system. For the linearised state-space description of the compressor and 5-phase IM, a stabilising optimal (H-infinity) feedback controller is designed. This controller achieves a solution to the nonlinear optimal control problem of the compressor and 5-phase IM system under model uncertainty and external perturbations. The feedback gains of the controller are computed by solving an algebraic Riccati equation at each iteration of the control method. Lyapunov analysis is used to demonstrate global stability for the control loop. Additionally, the H-infinity Kalman filter is used as a robust state estimator, which allows for implementing sensorless control for the gas compression system.

Publisher

Walter de Gruyter GmbH

Subject

General Medicine

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