Graphic IMC-PID tuning based on maximum sensitivity for uncertain systems

Chu, Minghui; Xu, Chi; Chu, Jizheng

doi:10.1177/0142331218775491

Cited by 14 publications

(13 citation statements)

References 21 publications

(26 reference statements)

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“…The maximum sensitivity (

M_{s}

) has been characterised as a robustness index, which can limit the gain margin and phase margin, simultaneously [24]. Most importantly,

M_{s}

has been used to design the controller in comparison to other robustness indices [24, 25].…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, current research on CRA based control schemes for the power system is still underway. Aiming to address above problems, the concept of maximum sensitivity (

M_{s}

) based controller design has been used to show the trade‐off between robustness and performance [24, 25]. In addition,

M_{s}

based controller design is more effective for disturbance rejection [24, 25].…”

Section: Introductionmentioning

confidence: 99%

“…Aiming to address above problems, the concept of maximum sensitivity (

M_{s}

) based controller design has been used to show the trade‐off between robustness and performance [24, 25]. In addition,

M_{s}

based controller design is more effective for disturbance rejection [24, 25]. Hence, this type of controller design is more effective in LFC task of power system networks because power system network needs that the frequency and tie‐line power deviations are zero with respect to the consumer load disturbances, i.e.…”

Section: Introductionmentioning

confidence: 99%

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Graphic RCRA‐PIDA tuning based on maximum sensitivity for automatic generation control of thermal and hydro power systems

Kumar

Hote

2020

IET gener. transm. distrib.

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The frequency control is the mandatory task in a modern power system because of load demand variation and the integration of renewable energy sources (RESs). The main objective of automatic generation control (AGC) scheme is to maintain the balance between generation and load demand. This study proposes a graphical robust characteristic ratio assignment (RCRA) approach for PIDA controller tuning based on maximum sensitivity (M s) for AGC. The basic feature of this graphical approach is that characteristic ratios (γ i) in RCRA scheme are calculated in terms of M s. The important part of this design is that the analytical expressions for coefficient gains of PIDA controller are derived in terms of γ i and system parameters. Here, the non-reheat steam-turbine and hydro-turbine based single and multi-area power systems are considered for validation of the proposed control scheme. The critical issue in controller design for a hydro-turbine based power system is the non-minimum phase behaviour. The robustness and performance of RCRA-PIDA controller are examined under system non-linearities, parametric uncertainty and disturbances. Further, the performance of proposed approach is evaluated in the presence of RESs. Finally, it is observed that the proposed control approach performs better in comparison to the recently published control schemes.

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“…The maximum sensitivity (

M_{s}

) has been characterised as a robustness index, which can limit the gain margin and phase margin, simultaneously [24]. Most importantly,

M_{s}

has been used to design the controller in comparison to other robustness indices [24, 25].…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, current research on CRA based control schemes for the power system is still underway. Aiming to address above problems, the concept of maximum sensitivity (

M_{s}

) based controller design has been used to show the trade‐off between robustness and performance [24, 25]. In addition,

M_{s}

based controller design is more effective for disturbance rejection [24, 25].…”

Section: Introductionmentioning

confidence: 99%

“…Aiming to address above problems, the concept of maximum sensitivity (

M_{s}

) based controller design has been used to show the trade‐off between robustness and performance [24, 25]. In addition,

M_{s}

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Graphic RCRA‐PIDA tuning based on maximum sensitivity for automatic generation control of thermal and hydro power systems

Kumar

Hote

2020

IET gener. transm. distrib.

View full text Add to dashboard Cite

show abstract

“…The block diagram of IMC structure for a multivariable system is exposed in Figure 1 (Chu et al 2018).…”

Section: Imc Designmentioning

confidence: 99%

A comparative study on existing and new methods to design internal model controllers for non-square systems

Saidi

Touati

Dhahri

et al. 2019

Transactions of the Institute of Measurement and Control

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This paper focuses on a challenging problem in the internal model control (IMC) strategy: the model inversion to design the IMC controller for non-square systems. Several existing approaches for the synthesis of a specific inversion of the identified model will be presented in this paper to deal with the differences between the system’s inputs and outputs numbers. The non-square effective relative gain is firstly presented. It consists of the measurement of interactions between the loops of the system in order to square the system and make it invertible. The equivalent transfer function method is presented as well. It is based on tuning the pseudo-inverse of the process to design the internal model controller. These methods are then compared with a novel proposed model inversion approach based on virtual outputs method. Virtual adding is considered in order to obtain an invertible square transfer matrix to design the internal model controller. This simple yet effective method ensures robust control performance. Its efficiency and availability, as compared with other presented methods, is illustrated through simulations on an overactuated system with three inputs/two outputs.

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“…Ma and Chen (2018) provides guidelines in the analytical design of PID controllers. Based on the maximum sensitivity, a graphical tuning method based on an internal model control strategy and PID controller is proposed in Chu et al (2019). The problem of tuning the parameters of a PID controller for the first-order plus dead time plant is solved in Atherton and Boz (2009).…”

Section: Introductionmentioning

confidence: 99%

Add-on integration module-based proportional-integration-derivative control for higher precision electro-optical tracking system

Duan

Mao

Zhang

et al. 2021

Transactions of the Institute of Measurement and Control

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This paper concerns the improvement on proportional-integration-derivative (PID) control for the electro-optical tracking system for high-mobility targets. To achieve higher tracking precision and stronger disturbance rejection while fully utilizing the existing PID loop, the add-on integration module is proposed and seamlessly integrated into the conventional PID loop. It is proven that for any given conventional PID controller parameters, the add-on integration module based PID control can improve the ability of error attenuation at low frequency and keep the stability of resulting closed-loop system. More importantly, the feasible set of all parameters in the added module is explicitly given. Based on the feasible set, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain the globally optimal controller’s parameter under certain performance indices. The experiments are carried out for a typical electro-optical tracking test bed with several reference signals. It is shown that the proposed method has much smaller tracking errors than the existing PID method.

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Graphic IMC-PID tuning based on maximum sensitivity for uncertain systems

Cited by 14 publications

References 21 publications

Graphic RCRA‐PIDA tuning based on maximum sensitivity for automatic generation control of thermal and hydro power systems

Graphic RCRA‐PIDA tuning based on maximum sensitivity for automatic generation control of thermal and hydro power systems

A comparative study on existing and new methods to design internal model controllers for non-square systems

Add-on integration module-based proportional-integration-derivative control for higher precision electro-optical tracking system

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