10,686 research outputs found
Performance Measurement Under Increasing Environmental Uncertainty In The Context of Interval Type-2 Fuzzy Logic Based Robotic Sailing
Performance measurement of robotic controllers based on fuzzy logic,
operating under uncertainty, is a subject area which has been somewhat ignored
in the current literature. In this paper standard measures such as RMSE are
shown to be inappropriate for use under conditions where the environmental
uncertainty changes significantly between experiments. An overview of current
methods which have been applied by other authors is presented, followed by a
design of a more sophisticated method of comparison. This method is then
applied to a robotic control problem to observe its outcome compared with a
single measure. Results show that the technique described provides a more
robust method of performance comparison than less complex methods allowing
better comparisons to be drawn.Comment: International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013
Zero overshoot and fast transient response using a fuzzy logic controller
In some industrial process control systems it is
desirable not to allow an overshoot beyond the setpoint or a threshold, this could be a safety constraint or the requirement of the system. This paper outlines our work in designing a fuzzy PID controller to achieve a step-response with zero overshoot while improving the output transient response. Our designed fuzzy PID controller is applied to stable, marginally stable and unstable systems and their step responses are compared with a tuned conventional PID controller. A comparative case study shows that the proposed fuzzy controller is highly effective and
outperforms the PID controller in achieving a zero overshoot response and enhancing the output transient response
Karektor guru pendidikan khas aliran kemahiran berlandaskan nilai retorik dari perspektif pelajar pendidikan khas masalah pendengaran di Malaysia
Latar Belakang: Pendidikan Khas di Malaysia adalah satu usaha
yang berterusan untuk melahirkan insan yang berkemahiran,
berpandangan jauh, berupaya, beriman, berdikari, mampu
merancang dan menguruskan kehidupan harian serta menyedari
potensi diri sendiri yang selaras dengan Falsafah Pendidikan
Kebangsaan. Aliran pendidikan teknikal dan vokasional juga tidak
dikecualikan pelajar yang mempunyai keperluan khas. Oleh itu,
guru pendidikan khas aliran kemahiran harus mempunyai
karektor yang istimewa untuk mendidik pelajar golongan ini.
Namun begitu, masih belum wujudnya satu model standard guru
pendidikan khas terutamanya aliran kemahiran. Objektif: Kajian
ini dijalankan untuk mengenal pasti tahap penerapan elemen dan
dimensi nilai retorik dalam proses pengajaran dan pembelajaran
guru aliran kemahiran bagi pelajar pendidikan khas masalah
pendengaran. Keputusan: Dapatan kajian ini menunjukkan
penerapan elemen nilai retorik ethos dan logos dalam kalangan
guru berada pada tahap tinggi, diikuti dengan pathos pada tahap
sederhana. Dapatan kajian juga menunjukkan penerapan nilai
retorik bagi kebanyakan dimensi pada tahap tinggi, hanya
dimensi perasaan dan visualisasi pada tahap sederhana.
Kesimpulan: Umumnyaa, guru pendidikan khas aliran kemahiran
telah menerapkan nilai retorik pada tahap yang tinggi. Setiap guru
digalak untuk menguasai nilai retorik supaya dapat membantu
para pelajar menerokai ilmu pengetahuan yang disampaikan oleh
mereka dengan berkesan dan seterusnya memberi impak yang positif terhadap pencapaian pelajar
PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles
There exists an increasing demand for a flexible and computationally
efficient controller for micro aerial vehicles (MAVs) due to a high degree of
environmental perturbations. In this work, an evolving neuro-fuzzy controller,
namely Parsimonious Controller (PAC) is proposed. It features fewer network
parameters than conventional approaches due to the absence of rule premise
parameters. PAC is built upon a recently developed evolving neuro-fuzzy system
known as parsimonious learning machine (PALM) and adopts new rule growing and
pruning modules derived from the approximation of bias and variance. These rule
adaptation methods have no reliance on user-defined thresholds, thereby
increasing the PAC's autonomy for real-time deployment. PAC adapts the
consequent parameters with the sliding mode control (SMC) theory in the
single-pass fashion. The boundedness and convergence of the closed-loop control
system's tracking error and the controller's consequent parameters are
confirmed by utilizing the LaSalle-Yoshizawa theorem. Lastly, the controller's
efficacy is evaluated by observing various trajectory tracking performance from
a bio-inspired flapping-wing micro aerial vehicle (BI-FWMAV) and a rotary wing
micro aerial vehicle called hexacopter. Furthermore, it is compared to three
distinctive controllers. Our PAC outperforms the linear PID controller and
feed-forward neural network (FFNN) based nonlinear adaptive controller.
Compared to its predecessor, G-controller, the tracking accuracy is comparable,
but the PAC incurs significantly fewer parameters to attain similar or better
performance than the G-controller.Comment: This paper has been accepted for publication in Information Science
Journal 201
Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm
Fuzzy rule based models have a capability to approximate any continuous
function to any degree of accuracy on a compact domain. The majority of FLC
design process relies on heuristic knowledge of experience operators. In order
to make the design process automatic we present a genetic approach to learn
fuzzy rules as well as membership function parameters. Moreover, several
statistical information criteria such as the Akaike information criterion
(AIC), the Bhansali-Downham information criterion (BDIC), and the
Schwarz-Rissanen information criterion (SRIC) are used to construct optimal
fuzzy models by reducing fuzzy rules. A genetic scheme is used to design
Takagi-Sugeno-Kang (TSK) model for identification of the antecedent rule
parameters and the identification of the consequent parameters. Computer
simulations are presented confirming the performance of the constructed fuzzy
logic controller
Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model
open4siSustainable control has begun to stimulate research and development in a wide range of industrial communities particularly for systems that demand a high degree of reliability and availability (sustainability) and at the same time characterised by expensive and/or safety critical maintenance work.
For heating systems such as HVAC plants, clear conflict exists between ensuring a high degree of availability and reducing costly maintenance times.
HVAC systems have highly non-linear dynamics and a stochastic and uncontrollable driving force as input in the form of intake air speed, presenting an interesting challenge for modern control methods. Suitable control methods can provide sustainable maximisation of energy conversion efficiency over wider than normally expected air speeds and temperatures, whilst also giving a degree of “tolerance” to certain faults, providing an important impact on maintenance scheduling, e.g. by capturing the effects of some system faults before they become serious.This paper presents the design of different control strategies applied to a heating element nonlinear model. The description of this heating element was obtained exploiting a data driven and physically meaningful nonlinear continuous time model, which represents a test bed used in passive air conditioning for sustainable housing applications. This model has low complexity while achieving high simulation performance. The physical meaningfulness of the model provides an enhanced insight into the performance and functionality of the system. In return, this information can be used during the system simulation and improved model based and data driven control designs for tight temperature regulation. The main purpose of this study is thus to give several examples of viable and practical designs of control schemes with application to this heating element model. Moreover, extensive simulations and Monte Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared in order to evaluate advantages and drawbacks of the considered solutions. Finally, the exploited simulation tools can serve to highlight the potential application of the proposed control strategies to real air conditioning systems.openTurhan, T.; Simani, S.; Zajic, I.; Gokcen Akkurt, G.Turhan, T.; Simani, Silvio; Zajic, I.; Gokcen Akkurt, G
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