Unknown Sign Research Articles

Output-feedback global tracking for unknown control direction plants with application to extremum-seeking control

This paper addresses the design of a sliding mode tracking controller for single-input–single-output (SISO) uncertain plants with relative degree one and unknown control direction, i.e., with unknown sign of the high frequency gain (HFG). We demonstrate that, for a class of linear plants with nonlinear output function, it is possible to achieve global exact tracking using only output-feedback by combining a recently introduced periodic switching function with a well-known control parameterization of Model Reference Control (MRC). Simulation results are presented to illustrate the good tracking performance. One significant advantage of the new scheme is its robustness to time-varying control direction which is here theoretically justified for jump variations of the HFG and successfully tested by simulation in more general conditions. This property makes it adequate for solving extremum-seeking problems. Theoretical justification is presented for a class of systems with nonlinear output function using only output-feedback. An application to the wheel slip control in Antilock Braking Systems (ABSs) illustrates the practical viability of the proposed control scheme.

Adaptive Fuzzy Dynamic Surface Control for a Class of Nonlinear Systems with Unknown Time-delays

摘要: 针对一类具有未知方向增益函数的严格反馈非线性时滞系统, 提出了一种自适应模糊动态面控制(Dynamic surface control, DSC)算法. 通过利用DSC设计技术和Lyapunov-Krasovskii函数, 该算法不仅克服了计算膨胀的问题, 而且补偿了未知的时滞. 采用Nussbaum函数解决了虚拟控制增益的符号问题, 并且避免了控制器的奇异性. 所设计的控制器保证了闭环系统所有的状态和信号是半全局有界的, 并且通过选择合适的设计参数可使跟踪误差为任意小. 仿真结果表明了所提出控制器的有效性. 关键词: 自适应控制 / 时滞 / 模糊系统 / 动态面控制

Coexistence of polyarteritis nodosa and psoriatic arthritis in a child: an unreported association

Polyarteritis nodosa (PAN) is a non-frequent vasculitis of small- and medium-sized vessels. Psoriatic arthritis (PA) is described as a "unique inflammatory arthritis associated with psoriasis" with an inexact prevalence rate due to the lack of widely accepted classification criteria. We describe the case of an 11-year-old boy that presented with fever of unknown origin plus clinical signs of sacroiliitis, bilateral enthesitis of the plantar fascia, and skin psoriasis. He acutely developed erythematous and tender nodular lesions in the lower limbs that lasted around 3 weeks and spontaneously disappeared at the same time as the fever. He was diagnosed as having PAN and PA according to clinical and histological criteria. This is the first report of the coexistence of PAN and PA in a child indicating a possible relation (maybe cross-reactivity of an infectious agent) between PAN and spondiloarthritis.

Image Segmentation and Shape Analysis for Road-Sign Detection

This paper proposes an automatic road-sign recognition method based on image segmentation and joint transform correlation (JTC) with the integration of shape analysis. The presented system is universal, which is able to detect traffic signs of any countries with any color and any of the existing shapes (e.g., circular, rectangular, triangular, pentagonal, and octagonal) and is invariant to transformation (e.g., translation, rotation, scale, and occlusion). The main contributions of this paper are: 1) the formulation of two new criteria for analyzing different shapes using two basic geometric properties, 2) the recategorization of the rectangular signs into diamond or nondiamond shapes based on the inclination of the four sides with the ground and 3) the employment of the distortion-invariant fringe-adjusted JTC (FJTC) technique for recognition. There are three main stages in the proposed algorithm: 1) segmentation by clustering the pixels based on the color features to find the regions of interest (ROIs); 2) traffic-sign detection by using two novel shape classification criteria, i.e., the relationship between area and perimeter and the number of sides of a given shape; and 3) recognition of the road sign using FJTC to match the unknown signs with the known reference road signs stored in the database. Experimental results on real-life images show a high success rate and a very low false hit rate and demonstrate that the proposed framework is invariant to translation, rotation, scale, and partial occlusions.

Adaptive fuzzy backstepping output feedback control of nonlinear time-delay systems with unknown high-frequency gain sign

In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and single-output (SISO) strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.

Patterns on an ancient artifact: a coincidence?

The Phaistos Disk is an ancient artifact from Crete. At each side of the disk, a series of unknown signs is written along a spiral. Professional archaeologists expect that we will only learn what it is until similar objects are found. A statistical analysis in this article shows what it is not: it is not a one-dimensional text, since there are relations between the signs in adjacent windings of the spiral. Three patterns of such relations have been identified. A Monte Carlo simulation of one of them has been performed, using a model of the spiral form. It is concluded that the probability of this pattern being coincidental is small, well below the conventional threshold.

Eigen-based traffic sign recognition

This study's purpose is to introduce eigen-based traffic sign recognition. This technique is based on invoking the principal component analysis (PCA) algorithm to choose the most effective components of traffic sign images to classify an unknown traffic sign. A set of weights are computed from the most effective eigen vectors of the traffic sign. By using the Euclidean distance, unknown traffic sign images are then classified. The approach was tested on two different databases of traffic sign's borders and speed limit pictograms that were extracted automatically from real-world images. A classification rate of 96.8 and 97.9% was achieved for these two databases. To check the robustness of this approach, non-traffic sign objects and occluded signs were invoked. A performance of 71% was achieved when occluded signs are used. When signs were rotated 10 degrees around their centre, the performance became 89% when traffic signs' outer shapes were used and for rotated speed limit pictograms the result was 80%.

Eigen Based Traffic Sign Recognition Which Aids In Achieving Intelligent Speed Adaptation

Speed is one of the major factors by which the traffic safety is affected. If the speed limit traffic signs on the road are recognised and displayed to a driver, this will be a motivation to keep the vehicle's speed within the permitted range. The purpose of this paper is to investigate Eigen-based traffic sign recognition which can aid in the development of Intelligent Speed Adaptation. This system is based on invoking the PCA technique to detect the unknown speed limit traffic sign and computes its best effective Eigen vectors. The traffic sign is then recognized and classified by using the shortest Euclidean distance to the different speed limit traffic sign classes. The system was trained using 24 037 images which were collected in different light conditions. To check the robustness of this system, it was tested against 1429 images and it was found that the accuracy of recognition was 97.5% which indicates clearly the high robustness targeted by this system.

Observer-Based Adaptive Neural Control for a Class of Nonlinear Non-affine Systems with Unknown Gain Sign

AbstractThis paper presents an adaptive neural network output feedback controller for a class of uncertain SISO nonlinear non-affine systems. Since the system states are not required to be available for measurement, an observer is designed to estimate the system states. Comparing to existing results, this method does not require a priori knowledge about the sign of control gain direction. To deal with the unknown sign of the control gain, the Nussbaum-type function is used. By using neural network, the unknown nonlinear function is approximated and a robustifying term is used to reduce the approximation error and compensate the effect of external disturbance. The stability of the closed-loop system is analyzed by using Lyapunov method. Theoretical results are illustrated through simulation example. Numerical simulations confirm the effectiveness of the proposed method.

Fuzzy adaptive robust backstepping stabilization for SISO nonlinear systems with unknown virtual control direction

In this paper, a direct fuzzy adaptive robust control approach is proposed for a class of SISO nonlinear systems with completely unknown virtual control directions, unknown nonlinearities, unmodeled dynamics and dynamic disturbances. In the backstepping recursive design, fuzzy logic systems are employed to approximate the combined nonlinear uncertainties, a dynamic signal and Nussbaum gain technique are introduced into the control scheme to dominate the dynamic uncertainties and solve the unknown signs of virtual control directions, respectively. It is proved that the proposed robust fuzzy adaptive scheme can guarantee the all signals in the closed-loop system are semi-globally uniformly ultimately bounded. The effectiveness of the proposed approach is illustrated via three examples.

Heftetjernite, a new scandium mineral from the Heftetjern pegmatite, Tordal, Norway

Heftetjernite, ideally ScTaO 4 , is a new scandium mineral from the Heftetjern pegmatite, Tordal, Telemark, Norway. In the type specimen, it occurs as minute, elongate tabular, very dark brown crystals in a single small void in albite. Other associated minerals are fluorite, muscovite, altered milarite, a metamict, dark greyish brown mineral of the pyrochlore-microlite group, and an unidentified, orange-brown, tabular, nearly X-ray amorphous Ti-Y-Ta-Nb-mineral. Electron-microprobe analysis yielded the empirical formula (Sc 0.64 Sn 0.13 Mn 0.12 Fe 0.08 Ti 0.06 ) ∑1.03 (Ta 0.69 Nb 0.30 ) ∑0.99 O 4 which clearly demonstrates the charge-balanced substitution scheme 2Sc 3+ = (Sn,Ti) 4+ + (Mn,Fe) 2+ . The mineral crystallises in the wolframite structure type, with space group P 2/ c and a = 4.784(1), b = 5.693(1), c = 5.120(1) A, β = 91.15(3)°, V = 139.42(5) A 3 ( Z = 2). A synthetic equivalent is known. Strongest lines in the calculated X-ray powder diffraction pattern of heftetjernite are [ d in A( I ) ( hkl )]: 3.000 (100) (11–1), 2.9570 (97) (111), 3.662 (53) (110), 2.4877 (34) (02–1), 4.783 (33) (100), 3.807 (32) (01–1). The crystal structure was refined to R ( F ) = 1.39 % from single-crystal X-ray diffraction data (293 K). It is based on two types of edge-sharing, distorted octahedra occupied predominantly by Sc and Ta, respectively. Heftetjernite is translucent to transparent, with a dark brownish (with a reddish hue) streak and adamantine lustre. It is brittle, has a perfect {010} cleavage, irregular fracture and a Mohs hardness estimated to be around 4.5 by comparison to ferberite; D x = 6.44 g/cm 3 (from crystal-structure analysis). Optically, the mineral is biaxial with an unknown optical sign, weakly pleochroic (yellowish brown with a reddish tint to reddish brown), with no observable dispersion. A mean refractive index of 2.23 was calculated from the Gladstone-Dale relationship using the X-ray density. Heftetjernite is named after its type locality. The mineral is compared with synthetic ScTaO 4 , ScNbO 4 , iwashiroite-(Y) and formanite-(Y) (both nominally YTaO 4 ), and some comments are made on the relation to Sc-bearing ixiolite.

Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change

Anthropogenic land cover change (ALCC) is one of the few climate forcings with still unknown sign of their climate response. Major uncertainty results from the often counteracting temperature responses to biogeochemical as compared to biogeophysical effects. Here, we separate the strength of these two effects for ALCC during the last millennium. We add unprecedented detail by (i) using a coupled atmosphere/ocean general circulation model (GCM), and (ii) applying a high‐detail reconstruction of historical ALCC. We find that biogeophysical effects have a slight cooling influence on global mean temperature (−0.03 K in the 20th century), while biogeochemical effects lead to strong warming (0.16–0.18 K). During the industrial era, both effects cause significant changes in certain regions; only few regions, however, experience biogeophysical cooling strong enough to dominate the overall temperature response. This study therefore suggests that the climate response to historical ALCC, both globally and in most regions, is dominated by the rise in CO2 caused by ALCC emissions.

The Estimation of Poverty and Inequality through Parametric Estimation of Lorenz Curves: An Evaluation

Poverty and inequality are often estimated from grouped data as complete household surveys are neither always available to researchers nor easy to analyze. In this study we assess the performance of functional forms proposed by Kakwani (1980a) and Villasenor and Arnold(1989) to estimate the Lorenz curve from grouped data. The methods are implemented using the computational tools POVCAL and Sim-SIP, developed and distributed by the World Bank. To identify biases associated with these methods, we use unit data from several household surveys and theoretical distributions. We find that poverty and inequality are better estimated when the true distribution is unimodal than multimodal. For unimodal distributions, biases associated with poverty measures are rarely larger than one percentage point. For data from multi-peaked or heavily skewed distributions, the biases are likely to be higher and of unknown sign.

Fuzzy adaptive controller for MIMO nonlinear systems with known and unknown control direction

This paper investigates fuzzy adaptive control schemes for a class of multi-input multi-output (MIMO) unknown nonlinear systems with known and unknown sign of the control gain matrix. Three fuzzy adaptive control schemes are developed. In the design of the second and third controller, we will exploit a decomposition of the control gain matrix into a symmetric positive-definite matrix, a diagonal matrix with diagonal entries + 1 or - 1 and a unity upper triangular matrix. The Nussbaum-type function is used to deal with the unknown control direction (i.e. the unknown sign of the control gain matrix). For updating the parameters of the fuzzy system, an adaptation proportional-integral (PI) law is proposed. Theoretical results are illustrated through two simulation examples.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh ( ⋅ ) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Adaptive fuzzy controller design of nonlinear systems with unknown gain sign

For a class of uncertain nonlinear non-affine systems, an adaptive fuzzy controller is proposed in this paper. Compared with the existing results, the proposed controller does not require a priori knowledge about the sign of the control gain coefficient. It can be shown that all the signals in the closed-loop system are bounded and the tracking error converges to a bounded compact sets by choosing design parameters appropriately. A simulation example is given to guarantee the effectiveness of the proposed controller.

Primary Cardiac Lymphoma Presenting with Cardiac Tamponade

Primary cardiac lymphoma (PCL) is rare and occurs more commonly in immunocompromised patients. It can present in various ways, and diagnosis is particularly challenging, especially for the unsuspecting physician. We report a case of PCL in an immunocompetent 55-year-old man who initially presented with pyrexia of unknown origin, chest pain, dyspnea, and few early clinical signs, but who was later found to have cardiac tamponade and a large cardiac mass on echocardiography and cardiovascular magnetic resonance. A high index of suspicion is needed to diagnose PCL, and echocardiogram remains an important diagnostic tool.

A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters

The sign of unknown input coefficients is assumed to be known in most papers about the input uncertainties. In this paper, a Nussbaum gain method is adopted to cope with the situation that both the sign and the value of input are unknown. And the unknown parameters can be estimated under the situation of unknown sign of control. The synchronization is achieved for a class of hyperchaotic systems with unknown parameters and input uncertainties by adopting of the Nussbaum gain method and the global terminal adaptive method. And the conclusions are made as follows: First, the proposed method is effective in the situation that the sign of input is unknown. Second, the estimation of unknown parameters can be achieved only when the number of unknown parameters satisfied some condition and no uncertainty exist in the input of systems. Third, the unknown parameters cannot be estimated correctly with common adaptive method when there are input uncertainties in the system. But the Nussbaum gain method can get good result in the estimation of unknown parameters. At last, numerical simulations are done to show the effectiveness of the proposed method.

Sequential Detection of Drift Change for Brownian Motion with Unknown Sign

Abstract We study tests of power one for the following change-point problem. Suppose one observes a process 𝑊 which is either a Brownian motion without drift or a Brownian motion that has zero drift up to a random time τ after which with equal probability the drift becomes either θ or –θ, where the value of θ > 0 is known. The distribution of τ is also assumed to be known. We search for a stopping time 𝑇* that minimizes an appropriate Bayes risk and give a solution that is asymptotically optimal, when the cost of observation tends to zero.

Implicit dual control based on particle filtering and forward dynamic programming

This paper develops a sampling-based approach to implicit dual control. Implicit dual control methods synthesize stochastic control policies by systematically approximating the stochastic dynamic programming equations of Bellman, in contrast to explicit dual control methods that artificially induce probing into the control law by modifying the cost function to include a term that rewards learning. The proposed implicit dual control approach is novel in that it combines a particle filter with a policy-iteration method for forward dynamic programming. The integration of the two methods provides a complete sampling-based approach to the problem. Implementation of the approach is simplified by making use of a specific architecture denoted as an H-block. Practical suggestions are given for reducing computational loads within the H-block for real-time applications. As an example, the method is applied to the control of a stochastic pendulum model having unknown mass, length, initial position and velocity, and unknown sign of its dc gain. Simulation results indicate that active controllers based on the described method can systematically improve closed-loop performance with respect to other more common stochastic control approaches.