Abstract
As a clean energy engine, the gas turbine is widely used for the generation of the power plant and the propulsion of the warship. Its control is becoming more and more challenging for the reason that internal coupling exists and the load command changes frequently and extensively. However, advanced controllers are difficult to implement on the distributed control system and conventional proportional–integral–derivative controllers are unable to handle with aforementioned challenges. To solve this problem, this article designs a decentralized active disturbance rejection control for the power and exhaust temperature of the gas turbine. Simulation results illustrate that the decentralized active disturbance rejection control is able to obtain satisfactory tracking and disturbance rejection performance with strong robustness. Eventually, a numerical simulation is carried out which shows advantages of active disturbance rejection control in the control of power and exhaust temperature when the gas turbine is under variable working condition. This successful application of decentralized active disturbance rejection control to the gas turbine indicates its promising prospect of field tests in future power industry with increasing demand on integrating more renewable energy into the grid.
Highlights
The gas turbine (GT) is a typical internal combustion engine which is widely used for the generation of power plants and the propulsion of warships
The decentralized Active disturbance rejection control (ADRC) is designed for the control of power and exhaust temperature of the GT in order to solve these problems
Based on the decentralized structure, numerical simulations are carried out to illustrate that ADRC is able to obtain satisfactory tracking performance and disturbance rejection performance at the nominal operating point
Summary
The gas turbine (GT) is a typical internal combustion engine which is widely used for the generation of power plants and the propulsion of warships. The rest of this paper is organized as follows: the mechanism model and transfer function models are established to describe the multivariable process of the power and exhaust temperature of the GT. To analyze the characteristics and control difficulties of the GT, we identify the transfer function matrix under four different working conditions including 100% load, 76% load, 60% load, 51% load, and 31% load. Note that control difficulties of the GT such as strong nonlinearity and coupling are all analyzed based on transfer functions of aforementioned working conditions. Since the big gap represents the significant difference between two systems, it is easy to understand that the transfer function of 31% load is irrelevant to those of other working conditions. The decentralized control structure is able to be applied to this TITO system
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