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In This work we use the Sub-optimal Approximation method of fractional order transfer function to design the parameters of a PID controller with fractionalized integrator. The performance analysis of the fractionalized PID controller over integer order PID controller is provided with simulation examples showing the effectiveness of the proposed technique against disturbances.
The scrutiny of boundaries isolation methods is presented in this paper. The newly developed algorithms, based on regression analysis and integral projection are compared with Hough transform in order to analyze their effectiveness for the specific problem of moving logs control. The comparative analysis of the methods was carried out on the database of images obtained from video sequence of real...
Fractional order adaptive controllers are gathering a great interest in the control research community mainly because of the additional tools and freedom offered to the designer in order to respond to more severe control specifications, for processes under control in real-time. The present work introduce a new innovation for a particular regulator in this class of controllers namely the classical...
Gene expression data are widely used in classification tasks for medical diagnosis. Data scaling is recommended and helpful for learning the classification models. In this study, we propose a data scaling algorithm to transform the data uniformly to an appropriate interval by learning a generalized logistic function to fit the empirical cumulative density function of the data. The proposed algorithm...
Adversarial examples are augmented data points generated by imperceptible perturbation of input samples. They have recently drawn much attention with the machine learning and data mining community. Being difficult to distinguish from real examples, such adversarial examples could change the prediction of many of the best learning models including the state-of-the-art deep learning models. Recent attempts...
In the subspace approximation problem, we seek a k-dimensional subspace F of Rd that minimizes the sum of p-th powers of Euclidean distances to a given set of n points a1, an ε Rd, for p ≥ 1. More generally than minimizing Σi dist(ai, F)p, we may wish to minimize Σi M(dist(ai, F)) for some loss function M(), for example, M-Estimators, which...
This work improves algorithms for finding network flows both sustainable and robust against multilink-attack (MLA). It brings out the relationship between sustainability (flow solution before attack known as MLA-reliable flow) and robustness (flow value after attack known as MLA-robust flow). Both problems are known to be NP-hard. However, exact polynomial time algorithms exist for certain categories...
While recent approaches have shown that it is possible to do template matching by exhaustively scanning the parameter space, the resulting algorithms are still quite demanding. In this paper we alleviate the computational load of these algorithms by proposing an efficient approach for predicting the match ability of a template, before it is actually performed. This avoids large amounts of unnecessary...
In this paper, We present a blind image watermarking method based on DCT domain and independent component analysis (ICA). First of all, an approximation of cover image is created using ICA. We divide approximation image to equal 8×8 blocks and then apply DCT transform to each block. We use spread spectrum (SS) method for embedding the watermark bits. In our method a group of random bits are generated...
Outlier detection is now widely used in various fields. It attracts more and more interests in research. The density based outlier detection methods and the distance based outlier detection methods are the most frequently used outlier detection methods. In big data, the size and dimensions of data is very large. Those features make the conventional methods not suitable for big data. According to the...
In this paper, we address the problem of the distributed multi-target tracking with labelled set filters in the framework of generalized Covariance Intersection (GCI). Our analyses show that the label space mismatching phenomenon, which means the same realization drawn from label spaces of different sensors does not have the same implication, is quite common in practical scenarios and may bring serious...
Control of active magnetic bearings is an important area of research. In this paper authors present the methodology of design, discretization and implementation PIλD controller for magnetic levitation system. Implementation on the laboratory system was performed to validate the presented methodology. The presented methodology is promising and can be successfully used in other control systems.
A spectral shaping technique is adopted to expand the operating frequency range for DWT-based blind audio watermarking. The process is performed framewisely over the 3rd level approximation subband, of which the spectrum spans from 0 to 2756 Hz. The effectiveness of the proposed scheme is demonstrated using the perceptual evaluation of audio quality and bit error rates of recovered watermarks under...
We develop a robust multiuser detector for a Frequency Division Multiplexing (FDM) system where each user employs a binary continuous phase modulation (CPM) generated through a low-cost transmitter, thus characterized by a significant modulation index uncertainty, and sent over a channel affected by phase noise. In this FDM system the spectral efficiency can be increased by reducing the spacing between...
The statistical test rule induction method (STRIM) has been proposed as a method for effectively inducing if-then rules from a decision table. Its usefulness has been confirmed by a simulation experiment and comparison with conventional methods. However, real-world datasets often contain missing and contaminated values. This issue has been examined and addressed by various conventional methods. This...
An efficient and robust FETI-2λ domain decomposition method (DDM) framework for electromagnetic (EM) modeling is outlined. The proposed framework uses randomized algorithms to approximate the low-rank discrete Dirichlet-to-Neumann (DtN) map interations that arise in FETI-2λ. The resulting approach is also combined with effective and robust local and global DDM preconditioners. A realistic numerical...
Dynamic optimization techniques for nonlinear systems can provide the process industry with sustainable and efficient operating regimes. However, these regimes often lie close to the operating limits. It is therefore critical that these model based operating conditions are robust with respect to process noise, i.e, unmodeled time-varying random disturbances. Besides the effect of uncertainty in the...
Aggregations of electric loads, like heating and cooling systems, can be controlled to help the power grid balance supply and demand, but the amount of balancing reserves available from these resources is uncertain. In this paper, we investigate data-driven optimization methods that are suited to dispatching power systems with uncertain balancing reserves provided by load control. Specifically, we...
We consider robust predictive control of continuous-time, constrained, nonlinear systems by means of a discrete-time control scheme. The key idea is to discretize the system first and to explicitly bound the arising discretization error. Taking this error into account a robustly stabilizing predictive controller is proposed that guarantees constraint satisfaction at the sampling instances and via...
A new policy-iteration algorithm based on neural networks (NNs) is proposed in this paper to synthesize optimal control laws online for continuous-time nonlinear systems. Latest advances in this field have enabled synchronous policy iteration but require an additional tuning loop or a logic switch mechanism to maintain system stability. A new algorithm is thus derived in this paper to address this...
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