Fault-Tolerant Robust Model-Predictive Control of Uncertain Time-Delay Systems Subject to Disturbances

Khan, Owais; Mustafa, Ghulam; Khan, Abdul Qayyum; Abid, Muhammad; Ali, Muhammad Zulqarnain Haider

doi:10.1109/tie.2020.3029469

Cited by 26 publications

(17 citation statements)

References 24 publications

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“…The involved comparisons in Table 1 are explained from the following aspects. Firstly, as shown in the second row of Table 1, both component faults and actuator faults are considered in this paper, while only actuator faults are considered in [13,16,20]. In general, the component faults can significantly affect the system dynamics.…”

Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

“…In terms of the design and implementation of fault-tolerant methods (i.e., rows 5-7 in Table 1), the MPC optimization problems in [13] are constructed by relying on ellipsoidal constraint sets and LMI, which belongs to SDP and whose solution tends to be more time-consuming. In addition, approximating the feasible domain with ellipsoidal sets is generally more conservative than polyhedral sets.…”

Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

“…The penultimate row of Table 1 illustrates that the soft-constrained FTC method is further integrated into Algorithm 1 and used to deal with some unanticipated situations, such as uncertain fault amplitudes, system parameter drifts, disturbance overruns, etc. The last row of Table 1 implies that the design of the FTC method in [13] is more intuitive and better scalable than the FTC methods in Algorithm 1, [16,20]. It should be noted that the above comparisons are discussed mainly for the characteristics of the involved faulttolerant methods and not for the contents of the overall studies in [13,16,20].…”

Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

“…Among these methods, the MPC-based FTC method is widely considered, since MPC has the inherent and flexible capacity to address constrained optimization problems. The representative studies include FTC based on min-max MPC [13], FTC based on explicit MPC [14], multi-actuator/sensor FTC based on set theoretic MPC [15][16][17][18], FTC based on dual model MPC [19,20], etc.…”

Section: Introductionmentioning

confidence: 99%

“…Compared with the recent results on constrained AFTC studies (e.g., [13,16,20]), our main contributions can be reflected in the follows aspects: (i) A new and efficient AFDbased AFTC approach for component/actuator faults is proposed. In this work, only one observer is applied in real time to achieve FD and FI, while most of the existing studies use multiple observers for online parallel diagnosis; the fault mode separation is achieved by using auxiliary signals and separating hyperplanes designed offline, rather than by solving receding horizon optimizations and set membership discriminations online; the real-time control reconfiguration-based AFTC is achieved by solving simple LP problems instead of solving quadratic or semi-definite positive programming problems.…”

Section: Introductionmentioning

confidence: 99%

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Constrained Active Fault Tolerant Control Based on Active Fault Diagnosis and Interpolation Optimization

Han

Chen

et al. 2021

Entropy

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A new active fault tolerant control scheme based on active fault diagnosis is proposed to address the component/actuator faults for systems with state and input constraints. Firstly, the active fault diagnosis is composed of diagnostic observers, constant auxiliary signals, and separation hyperplanes, all of which are designed offline. In online applications, only a single diagnostic observer is activated to achieve fault detection and isolation. Compared with the traditional multi-observer parallel diagnosis methods, such a design is beneficial to improve the diagnostic efficiency. Secondly, the active fault tolerant control is composed of outer fault tolerant control, inner fault tolerant control and a linear-programming-based interpolation control algorithm. The inner fault tolerant control is determined offline and satisfies the prescribed optimal control performance requirement. The outer fault tolerant control is used to enlarge the feasible region, and it needs to be determined online together with the interpolation optimization. In online applications, the updated state estimates trigger the adjustment of the interpolation algorithm, which in turn enables control reconfiguration by implicitly optimizing the dynamic convex combination of outer fault tolerant control and inner fault tolerant control. This control scheme contributes to further reducing the computational effort of traditional constrained predictive fault tolerant control methods. In addition, each pair of inner fault tolerant control and diagnostic observer is designed integratedly to suppress the robust interaction influences between estimation error and control error. The soft constraint method is further integrated to handle some cases that lead to constraint violations. The effectiveness of these designs is finally validated by a case study of a wastewater treatment plant model.

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Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

Section: Multi-performance Comparison and Discussion Of Active Fault-tolerant Control Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Constrained Active Fault Tolerant Control Based on Active Fault Diagnosis and Interpolation Optimization

Han

Chen

et al. 2021

Entropy

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Robust dynamic output feedback predictive fault‐tolerant control for discrete uncertain systems

Wang,

Li,

et al. 2024

Optim Control Appl Methods

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A robust predictive fault‐tolerance control method integrating dynamic output feedback is proposed for discrete industrial processes with unmeasurable states, actuator faults, uncertainties, and external disturbances. First, a new iterative error model is developed, which extends the output tracking error to increase the freedom of controller regulation and ensure the tracking performance of the system. Second, a robust dynamic output feedback predictive fault‐tolerant controller is designed based on the preceding model. According to the Lyapunov stability theory, the robust stability criterion of the system is performed in the case of actuator faults, and the stability conditions of the system in the form of linear matrix inequality are given. The real‐time optimal control law gains are obtained by solving the stability conditions online. This method can effectively suppress the effects of actuator faults, uncertainties and external disturbances on the system with unmeasurable states, which can guarantee the tracking performance and stability of the system. The effectiveness of the proposed method is finally verified by using an injection molding process as an example.

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Active fault-tolerant control of cable-driven parallel robots

et al. 2022

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Fault-Tolerant Robust Model-Predictive Control of Uncertain Time-Delay Systems Subject to Disturbances

Cited by 26 publications

References 24 publications

Constrained Active Fault Tolerant Control Based on Active Fault Diagnosis and Interpolation Optimization

Constrained Active Fault Tolerant Control Based on Active Fault Diagnosis and Interpolation Optimization

Robust dynamic output feedback predictive fault‐tolerant control for discrete uncertain systems

Active fault-tolerant control of cable-driven parallel robots

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