Modified active disturbance rejection control for fluidized bed combustor

Wu, Zhenlong; Li, Donghai; Xue, Yali; Sun, Liming; Zheng, Shuang

doi:10.1016/j.isatra.2020.03.003

Cited by 32 publications

(14 citation statements)

References 37 publications

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“…In this article, the DDE‐PR PID is designed for the nonlinear model of an FBC unit which is established based on several dynamic equations depicted by the balance of matter and energy 42 . This nonlinear model of the FBC unit has been recognized widely 43,44 and its details are presented as follows.

\{\begin{matrix} leftlmatrix \\ \frac{d W_{c} false(t false)}{d t} = false(1 - V false) Q_{c} false(t false) - Q_{B} false(t false) \\ \frac{d C_{B} false(t false)}{d t} = \frac{1}{V_{B}} false[C_{1} F_{1} false(t false) - Q_{B} false(t false) X_{C} - C_{B} false(t false) F_{1} false(t false) false] \\ \frac{d T_{B} false(t false)}{d t} = \frac{1}{c_{I} W_{I}} false{H_{C} Q_{B} false(t false) + c_{1} F_{1} false(t false) T_{1} - α_{italicBt} A_{italicBt} false[T_{B} false(t false) - T_{italicBt} false] - c_{F} F_{1} false(t false) T_{B} false(t false) false} \\ \frac{d C_{F} false(t false)}{d t} = \frac{1}{V_{F}} false{C_{B} false(t false) F_{1} false(t false) + C_{2} F_{2} false(t false) T_{1} - {italicVQ}_{c} false(t false) X_{V} - C_{F} false(t false) false[F_{1} false(t false) \end{matrix}

…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

“…In this subsection, we only focus on the DDE‐PR design for the power loop of the FBC unit. Moreover, the proportional‐integral (PI) controller with fixed parameters which are given in Reference 44 is designed for the bed temperature loop. Figure 18 shows the control structure of the FBC unit with DDE PID.…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

“…In Figure 18, f ( x ) is denoted as the functional relationship between the load command and the set points of the output power and the bed temperature. Note that the PI controller is designed with the form of

- 0.01 - 10^{- 5} / s

in Reference 44.…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

“…Therefore, the set point of the output power is changing with the load command. During the daily operation of a power plant with FBC system, the unit operates in a wide load range of 50%–100% and the load command is regulated frequently 44 . However, as mentioned in Section 5.1, the nonlinearity of the FBC unit is strong.…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

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Desired dynamic equational proportional‐integral‐derivative controller design based on probabilistic robustness

Shi

Ding

et al. 2021

Intl J Robust & Nonlinear

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Uncertainties existing in industrial processes always result in many challenges for controller design. To enhance the ability of the closed-loop system to handle the uncertainties, a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller is designed based on probabilistic robustness (PR) in this article. The necessity of the proposed design method is demonstrated by introducing the problem formulation. Based on its fundamentals, DDE PID designed based on PR (DDE-PR PID) is proposed for uncertain systems and corresponding design procedure is summarized as a flow chart. Then the proposed DDE-PR PID is designed for several typical processes and simulation results indicate that the proposed DDE-PR PID cannot only achieve satisfactory control performance for nominal systems, but also satisfy control requirements for all uncertain systems with the maximum probability.Finally, the proposed DDE-PR PID is applied to the nonlinear model of a fluidized bed combustor unit and the level system of a water tank. Its superiority in robustness is validated by both simulations and experiments, which shows the promising prospect of DDE-PR PID in future power industry. On the other hand, the DDE method is extended to the generalized two-degree-of-freedom PID controller and its bandwidth-parameterization is proposed in this article as well.

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\{\begin{matrix} leftlmatrix \\ \frac{d W_{c} false(t false)}{d t} = false(1 - V false) Q_{c} false(t false) - Q_{B} false(t false) \\ \frac{d C_{B} false(t false)}{d t} = \frac{1}{V_{B}} false[C_{1} F_{1} false(t false) - Q_{B} false(t false) X_{C} - C_{B} false(t false) F_{1} false(t false) false] \\ \frac{d T_{B} false(t false)}{d t} = \frac{1}{c_{I} W_{I}} false{H_{C} Q_{B} false(t false) + c_{1} F_{1} false(t false) T_{1} - α_{italicBt} A_{italicBt} false[T_{B} false(t false) - T_{italicBt} false] - c_{F} F_{1} false(t false) T_{B} false(t false) false} \\ \frac{d C_{F} false(t false)}{d t} = \frac{1}{V_{F}} false{C_{B} false(t false) F_{1} false(t false) + C_{2} F_{2} false(t false) T_{1} - {italicVQ}_{c} false(t false) X_{V} - C_{F} false(t false) false[F_{1} false(t false) \end{matrix}

…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

- 0.01 - 10^{- 5} / s

in Reference 44.…”

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

Section: Application Of Dde‐pr Pid On An Fbc Unitmentioning

confidence: 99%

See 2 more Smart Citations

Desired dynamic equational proportional‐integral‐derivative controller design based on probabilistic robustness

Shi

Ding

et al. 2021

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

“…This simplification lays a foundation for the field application of ADRC. In recent years, the linear ADRC is widely used to solve problems in engineering, especially in the control of thermodynamic objects such as circulating fluidized bed (CFB) boilers [14], waste heat recovery systems [15], gasifiers [16], nuclear heating reactor [17], secondary air flow [18], proton exchange membrane fuel cell [19,20], vibration suppression [21] and heavy-duty diesel engine [22]. These applications show the developing prospects of ADRC in industry.…”

mentioning

confidence: 99%

Superheated Steam Temperature Control Based on a Hybrid Active Disturbance Rejection Control

Shi

Guo³

et al. 2020

Energies

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Superheated steam temperature (SST) is a significant index for a coal-fired power plant. Its control is becoming more and more challenging for the reason that the control requirements are stricter and the load command changes extensively and frequently. To deal with the aforementioned challenges, previously the cascade control strategy was usually applied to the control of SST. However, its structure and tuning procedure are complex. To solve this problem, this paper proposes a single-loop control strategy for SST based on a hybrid active disturbance rejection control (ADRC). The stability and ability to reject the secondary disturbance are analyzed theoretically in order to perfect the theory of the hybrid ADRC. Then a tuning procedure is summarized for the hybrid ADRC by analyzing the influences of all parameters on control performance. Using the proposed tuning method, a simulation is carried out illustrating that the hybrid ADRC is able to improve the dynamic performance of SST with good robustness. Eventually, the hybrid ADRC is applied to the SST system of a power plant simulator. Experimental results indicate that the single-loop control strategy based on the hybrid ADRC has better control performance and simpler structure than cascade control strategies. The successful application of the proposed hybrid ADRC shows its promising prospect of field tests in future power industry with the increasing demand on integrating more renewables into the grid.

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A Decoupling Design Method of Compensated Active Disturbance Rejection Control for Multivariable System

Wang

Dai

Xue

et al. 2022

Communications in Computer and Information Science

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Modified active disturbance rejection control for fluidized bed combustor

Cited by 32 publications

References 37 publications

Desired dynamic equational proportional‐integral‐derivative controller design based on probabilistic robustness

Desired dynamic equational proportional‐integral‐derivative controller design based on probabilistic robustness

Superheated Steam Temperature Control Based on a Hybrid Active Disturbance Rejection Control

A Decoupling Design Method of Compensated Active Disturbance Rejection Control for Multivariable System

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