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Titlebook: Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes; Limin Wang,Ridong Zhang,Furong Gao Book 2020 Springer Nat

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Iterative Learning Control of Nonlinear Batch Processes,r methods and the immaturity of research, research on nonlinear batch process control is rare. The famous Takagi-Sugeno (T-S) fuzzy system was proposed by Japanese scholars Takagi and Sugeno [.] in 1985, and the method of approximating nonlinear system using T-S fuzzy model was proposed. At present,
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Iterative Learning Fault-Tolerant Control of Linear Batch Processes,evitable, which affects the operation of the process, reduces system performance, and even endangers life. Therefore, under the fault, it is particularly important that the equipment can run smoothly. Faults are roughly classified into system internal faults, actuator faults, and sensor faults, amon
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Limin Wang,Ridong Zhang,Furong Gao and maintenance. System models may represent an existing physical part – for example an existing robot installation – and a software simulated part – for example a possible future extension of the physical industrial automation setup. We call such systems cyber-virtual systems. Here, we present our
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Limin Wang,Ridong Zhang,Furong Gao for locating appropriate components. The architecture of the framework comprises of five interrelated layers, namely Description, Location, Analysis, Recommendation and Build. The scope of this work is to describe in detail the first and third layers, and provide the means to evaluate the suitabili
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Limin Wang,Ridong Zhang,Furong Gao software quality. NFRs tend to interfere, conflict, and contradict with one another and this conflict is widely acknowledged as one of the key characteristics of NFRs. Several models of NFRs conflicts have been proposed and the interacting nature of NFRs has been characterized as either positive or
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