Multivalued adaptive neuro-fuzzy controller for robot vehicle - art. no. 1406

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued adaptive neuro-fuzzy inference system behaviors.

Visual timing and adaptive behavior in a road-crossing simulation study

In this road-crossing simulation study, we assessed both participant's ability to visually judge whether or not they could cross a road, and their adaptive walking behavior. To this end, participants were presented with a road inside the laboratory on which a bike approached with different velocities from different distances. Eight children aged 5-7, ten children aged 10-12, and ten adults were asked both to verbally judge whether they could cross the road, and to actually walk across the road if possible. The results indicated that the verbal judgments were not similar to judgments to actually cross the road. With respect to safety and accuracy of judgments, groups did not differ from each other, although the youngest group tended to be more cautious. All groups appeared to use a strategy to cross the road based both on the distance and the velocity of the approaching bike. Young children waited longer on the curb before crossing the road than older children and adults. All groups adjusted their crossing time to the time-to-arrival of the bike. These findings are discussed in relation to the ecological psychological approach and the putative dissociation between vision for perception (i.e. verbal judgment) and vision for action (i.e. actual crossing). (c) 2004 Elsevier Ltd. All rights reserved.

Constrained optimization model for the design of an adaptive (X)over-bar chart

An economic-statistical model is developed for variable parameters (VP) (X) over bar charts in which all design parameters vary adaptively, that is, each of the design parameters (sample size, sampling interval and control-limit width) vary as a function of the most recent process information. The cost function due to controlling the process quality through a VP (X) over bar chart is derived. During the optimization of the cost function, constraints are imposed on the expected times to signal when the process is in and out of control. In this way, required statistical properties can be assured. Through a numerical example, the proposed economic-statistical design approach for VP (X) over bar charts is compared to the economic design for VP (X) over bar charts and to the economic-statistical and economic designs for fixed parameters (FP) (X) over bar charts in terms of the operating cost and the expected times to signal. From this example, it is possible to assess the benefits provided by the proposed model. Varying some input parameters, their effect on the optimal cost and on the optimal values of the design parameters was analysed.

An adaptive chart for monitoring the process mean and variance

Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.

An adaptive system based on artificial neural networks for NPK fluid fertilizer application

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt with training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision fanning. Copyright (C) 2000 IFAC.

Adaptive control charts: A Markovian approach for processes subject to independent disturbances

Recent studies have shown that adaptive X control charts are quicker than traditional X charts in detecting small to moderate shifts in a process. In this article, we propose a joint statistical design of adaptive X and R charts having all design parameters varying adaptively. The process is subjected to two independent assignable causes. One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. It is assumed that the quality characteristic is normally distributed and the time that the process remains in control has exponential distribution. Performance measures of these adaptive control charts are obtained through a Markov chain approach. (c) 2005 Elsevier B.V. All rights reserved.

Differential vascular adaptive response in spontaneously hypertensive and Wistar rats: Role of nitric oxide, and prehypertensive and hypertensive states

Stress-induced vascular adaptive response in SHR was investigated, focusing on the endothelium. Noradrenaline responses were studied in intact and denuded aortas from 6-week-old (prehypertensive) and 14-week-old (hypertensive) SHR and age-matched Wistar rats submitted or not to acute stress (20-min swimming and I-h immobilization 25 min apart), preceded or not by chronic stress (2 sessions 2 days apart of 1-h day immobilization for 5-consecutive days). Stress did not alter the reactivity of denuded aorta. Moreover, no alteration in the EC50 values was observed after stress exposure. In intact aortas, acute stress-induced hyporeactivity to noradrenaline similar between strains at both age. Chronic stress potentiated this adaptive response in 6- and 14-week-old Wistar but not in 6-week-old SHR, and did not alter the reactivity of 14-week-old SHR. Maximum response (g) in intact aortas [6-week-old: Wistar 3.25 +/- 0.12, Wistar/acute 1.95 +/- 0.12*, Wistar/chronic 1.36 +/- 0.21*(+), SHR 1.75 +/- 0.11, SHR/acute 0.88 +/- 0.08*, SHR/chronic 0.85 +/- 0.05*; 14-week-old: Wistar 3.83 +/- 0.13, Wistar/acute 2.72 +/- 0.13*, Wistar/chronic 1.91 +/- 0.19*', SHR 4.03 +/- 0.17, SHR/acute 2.26 +/- 0.12*, SHR/chronic 4.10 +/- 0.23; inside the same strain: *P < 0.05 relate to non-stressed rat, (+)P < 0.05 related to acute stressed rat; n = 6-18]. Independent of age and strain, L-NAME and endothelium removal abolished the stress-induced aorta hyporeactivity. Conclusion: the vascular adaptive response to stress is impaired in SHR, independently of the hypertensive state. Moreover, this vascular adaptive response is characterized by endothelial nitric oxide-system hyperactivity in both strains. (c) 2006 Elsevier B.V. All rights reserved.

A hierarchy of adaptive (X)over-bar control charts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

5-Lipoxygenase Deficiency Impairs Innate and Adaptive Immune Responses during Fungal Infection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comments, with reply on 'Continuous time relay-controlled model reference adaptive-system' by A. Abdulkareem and R. Nagarajam

An adaptive scheme is shown by the authors of the above paper (ibid. vol. 71, no. 2, pp. 275-276, Feb. 1983) for continuous time model reference adaptive systems (MRAS), where relays replace the usual multipliers in the existing MRAS. The commenter shows an error in the analysis of the hyperstability of the scheme, such that the validity of this configuration becomes an open question.

Another prefiltering algorithm for adaptive IIR filtering

An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.

New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks

The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).

Adaptive control charts for attributes

We develop a general model for adaptive c, np, u and p control charts in which one, two or three design parameters (sample size, sampling interval and control limit width) switch between two values, according to the most recent process information. For a given in-control average sampling rate and a given false alarm rate, the adaptive chart detects changes in the process much faster than a chart with fixed parameters. Moreover, this study also offers general guidance on how to choose an effective design.