Optimal disturbance predictive and rejection control of a parabolic trough solar field

Gao, Xianhua; Wei, Shangshang; Wang, Minli; Su, Zhi‐gang

doi:10.1002/rnc.6443

Cited by 3 publications

(3 citation statements)

References 35 publications

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“…The extended state observer (ESO), which is used in ADRC, estimates all uncertainties as “unknown disturbances,” which are then corrected in the loop. The development of linear ADRC 13 substantially aided the industrial use of ADRC 14‐17 . ADRC has been used for a long time to study the control of large inertial systems, 18 such as chemical production process, 19 fully distributed automatic generation control, 20 distributed parameter system, 21‐24 main steam temperature control 25 .…”

Section: Introductionmentioning

confidence: 99%

“…The development of linear ADRC 13 substantially aided the industrial use of ADRC. [14][15][16][17] ADRC has been used for a long time to study the control of large inertial systems, 18 such as chemical production process, 19 fully distributed automatic generation control, 20 distributed parameter system, [21][22][23][24] main steam temperature control. 25 In their work, 26 the authors achieved almost feedback-linearization by employing a low-power extended observer.…”

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confidence: 99%

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Robust compensation for active disturbance rejection control of a class of high‐order systems with large time delay: Simulation and experimental studies

Liu,

Wu,

Dai

et al. 2023

Intl J Robust & Nonlinear

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Rejection of unknown disturbances and uncertainties in high‐order nonlinear systems with large delays is an important control problem. Active disturbance rejection control (ADRC) solves disturbances and uncertainties in a simple and effective way. In engineering, low‐order ADRC is often used to control high‐order large‐delay systems because of its ease of implementation and simplicity of operation. However, this leads to the problem that the low‐order ADRC has a limited ability to configure the high‐order nonlinear systems. The desired dynamics and the closed‐loop dynamics are almost always very biased. For a class of high‐order nonlinear systems with delay, a bias feedback compensation (BFC) approach to ADRC is suggested. This strategy works by adding a feedback loop based on the desired dynamics over the ADRC loop. The BFC strategy can improve the poor performance of low‐order ADRC for higher‐order nonlinear systems. In addition, a synthesis parameter tuning procedure of BFC‐ADRC is proposed in this article. Then, the stability problem is analyzed in this article. Finally, high‐fidelity simulation studies on a 1000 MW power plant for superheater steam temperature control and experiments on three interacting water tanks for level control are performed to verify the tracking, disturbance rejection, and robustness of the control strategy. Both simulation and experiments show that the method is highly robust and significantly improves both disturbance rejection and tracking performance.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Robust compensation for active disturbance rejection control of a class of high‐order systems with large time delay: Simulation and experimental studies

Liu,

Wu,

Dai

et al. 2023

Intl J Robust & Nonlinear

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show abstract

“…There are several disturbance compensation mechanisms in the optimal control field. In [30,31], a real-time updated equilibrium according to the disturbances and set-points is calculated first to transfer the aim of disturbance rejection and set-point tracking to the updated equilibrium. In [32], a disturbance model is added to the predictive model to compress the adverse effect of lumped disturbances.…”

Section: Introductionmentioning

confidence: 99%

Receding Galerkin Optimal Control with High-Order Sliding Mode Disturbance Observer for a Boiler-Turbine Unit

Zhao

Sun

et al. 2023

Sustainability

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The control of the boiler-turbine unit is important for its sustainable and robust operation in power plants, which faces great challenges due to the control unit’s serious nonlinearity, unmeasurable states, variable constraints, and unknown time-varying lumped disturbances. To address the above issues, this paper proposes a receding Galerkin optimal controller with a high-order sliding mode disturbance observer in a composite scheme, in which a high-order sliding mode disturbance observer is first employed to estimate the lumped disturbances based on a deviation form of the mathematical model of the boiler-turbine unit. Subsequently, under the hypothesis of state constraint, a receding Galerkin optimal controller is designed to compensate the lumped disturbances by embedding their estimates into the mathematically based predictive model at each sampling time instant. With the help of an interpolation polynomial, Gauss integration, and nonlinear solvers, an optimal control law is then obtained based on a Galerkin optimization algorithm. Consequently, disturbance rejection, target tracking, and constraint handling performance of a controlled closed-loop system are improved. Some simulation cases are conducted on a mathematical boiler-turbine unit model to demonstrate the effectiveness of the proposed method, which is supported by the quantitative result analysis, such as tracking and disturbance rejection performance indexes.

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Constraint Optimal Model-Based Disturbance Predictive and Rejection Control Method of a Parabolic Trough Solar Field

Wei,

Gao,

2024

Energies

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The control of the field outlet temperature of a parabolic trough solar field (PTSF) is crucial for the safe and efficient operation of the solar power system but with the difficulties arising from the multiple disturbances and constraints imposed on the variables. To this end, this paper proposes a constraint optimal model-based disturbance predictive and rejection control method with a disturbance prediction part. In this method, the steady-state target sequence is dynamically corrected in the presence of constraints, the lumped disturbance, and its future dynamics predicted by the least-squares support vector machine. In addition, a maximum controlled allowable set is constructed in real time to transform an infinite number of constraint inequalities into finite ones with the integration of the corrected steady-state target sequence. On this basis, an equivalent quadratic programming constrained optimization problem is constructed and solved by the dual-mode control law. The simulation results demonstrate the setpoint tracking and disturbance rejection performance of our design under the premise of constraint satisfaction.

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Optimal disturbance predictive and rejection control of a parabolic trough solar field

Cited by 3 publications

References 35 publications

Robust compensation for active disturbance rejection control of a class of high‐order systems with large time delay: Simulation and experimental studies

Robust compensation for active disturbance rejection control of a class of high‐order systems with large time delay: Simulation and experimental studies

Receding Galerkin Optimal Control with High-Order Sliding Mode Disturbance Observer for a Boiler-Turbine Unit

Constraint Optimal Model-Based Disturbance Predictive and Rejection Control Method of a Parabolic Trough Solar Field

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