1,721,069 research outputs found
Fuzzy control of a biomass-fired and solar-powered fluidized bed prototype as a residential cogeneration System
No full textA fuzzy PI controller is proposed as an alternative to a PI traditional controller for regulation and control of a small-scale fluidized bed cogeneration system driven by two renewable energy sources: direct solar and biomass combustion. The design of the fuzzy logic controller, with Sugeno inference method, was based on the knowledge of the more relevant continuity diagrams of the process model, characterized by nonlinearity and parameter variability. The simulation results show that the PI fuzzy logic controller delivers a higher performance, in terms of robustness and response speed, compared with the traditional PI controller. It is proved that the use of PI fuzzy controllers can be a good choice for the control of nonlinear processes with parameters varying in tim
Distillation Control: type-1 and type-2 fuzzy control
No full textTwo advanced controllers were developed in this paper, i.e., a type-1 and a type-2 fuzzy
logic controller and their performances compared in simulation for a case study, i.e., a binary
distillation column, which is characterized by high nonlinearities and parameter uncertainties in the
underlying mathematical model. Priority was given to the type-2 fuzzy controller, with special
attention to input fuzzy sets and type-2 Gaussian membership functions. All the simulation results
confirmed the robustness and the effectiveness of the fuzzy control action, with evident advantages for
the type-2 fuzzy controller
Nonlinear fuzzy control of a fed-batch reactor for penicillin production
No full textThe process of penicillin production is characterized by nonlinearities and parameter
uncertainties that make it difficult to control. In the paper the development and testing of a
multivariable fuzzy control system that makes use of type-2 fuzzy sets for the control of pH and
temperature are described. The performance of the type-2 fuzzy logic control system (T2FLCS) is
compared by simulation with that of a type-1 fuzzy logic control system (T1FLCS) and that of a control
system with traditional proportional-integral-derivative (PID) controllers proposed in the literature.
The fuzzy controllers are optimized using an ANFIS algorithm. The best results are obtained with the
T2FLCS particularly when uncertainties are present in the control system
Control of a Non-isothermal CSTR by Type-2 Fuzzy Logic Controllers
No full textThe paper describes the application of a type-2 fuzzy logic
controller to a non-isothermal continuous stirred tank reactor (CSTR)
characterized by the presence of saddle node and Hopf bifurcations, and its
performance compared with a type-1 fuzzy logic controller performance. A full
analysis of the uncontrolled CSTR dynamic was carried out and used for the
feedback-feedforward fuzzy controllers development. Simulation results
confirmed the effectiveness and the robustness of the type-2 FLCs which
outperform their type-1 counterparts, particularly when uncertainties are present
in the system
An Analysis of Long-Tailed Network Latency Distribution and Background Traffic on Dragonfly+
No full textA design methodology for adaptive type-2 fuzzy controllers
No full textThe main objective of the study is to provide a valid and effective methodology for the design and development of adaptive type-2 fuzzy controllers (AT2FLCs). The methodology is based on an in depth analysis of the process dynamics and the use of an Adaptive Neuro Fuzzy Inference System (ANFIS) technique for the optimization of controllers. The application of the methodology is shown in the design and development of AT2FLCs for two biochemical processes characterized by uncertainty and time varying parameters. The simulation results show that the union of the ANFIS optimization method with the adaptive fuzzy algorithm operating on the output scaling factor, allows to obtain robust AT2FLCs, with fewer rules than traditional type-2 FLCs, that minimize the negative effects of all system parameter changes and achieve in all cases a very high control performance
Control of a Nonlinear Continuous Bioreactor with Bifurcation by a Type-2 Fuzzy Logic Controller
No full textThe object of this paper is the application of a type-2 fuzzy logic controller to a nonlinear system that
presents bifurcations. A bifurcation can cause instability in the system or can create new working conditions
which, although stable, are unacceptable. The only practical solution for an efficient control is
the use of high performance controllers that take into account the uncertainties of the process. A type-2
fuzzy logic controller is tested by simulation on a nonlinear bioreactor system that is characterized by a
transcritical bifurcation. Simulation results show the validity of the proposed controllers in preventing
the system from reaching bifurcation and instable or undesirable stable conditions
Portable cost modeling for auto-vectorizers
No full textCompiler optimization passes employ cost models to determine if a code transformation will yield performance improvements. When this assessment is inaccurate, compilers apply transformations that are not beneficial, or refrain from applying ones that would have improved the code. We analyze the accuracy of the cost models used in LLVM's and GCC's vectorization passes for two different instruction set architectures. In general, speedup is over-estimated, resulting in mispredictions and a weak to medium correlation between predicted and actual performance gain. We therefore propose a novel cost model that is based on a code's intermediate representation with refined memory access pattern features. Using linear regression techniques, this platform independent model is fitted to an AVX2 and a NEON hardware. Results show that the fitted model significantly improves the correlation between predicted and measured speedup (AVX2: +52% for training data, +13% for validation data), as well as the number of mispredictions (NEON: -15 for training data, -12 for validation data) for more than 80 code patterns
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