Performance improvement of sensors response using piece-wise non-linear (PWL) A/D and pulse-width modulation (PWM) A/D techniques

Sensor generally refers to a device that measures or detects a real world condition or parameter such as temperature,- speed, pressure etc, and converts the condition into an analog or digital representation. Different methods based on varying physical properties are been employed for different parameter

Power supply interference in smart sensor microcontroller interface

Signal conditioning circuits otherwise referred to as sensor interface play important roles in data acquisition systems especially with microcontroller based systems. They are employed for signals conversion or translations to squeeze the acquired signal into a desirable range easily acceptable for the microcontroller. Many interfaces (signal conditioning circuits) have been proposed in the recent times in this regards, [1-3]; for instance, it is been employed to convert the measurand into a periodic modulated output signal which can be directly process by the microcontroller without needing an extrinsic AID converter [3]. In [1], relaxation oscillator based conditioning circuit was proposed for proper transmission of sensor output to microcontrolle

Two level Differential Evolution algorithms for ARMA parameters estimatio

The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. The results of both examples show the effectiveness of the proposed algorithm over a well known conventional technique

Intelligent Control for Automation of Yam Storage System Using Fuzzy Logic Controller

This paper presents the development of intelligent control technique for yam storage system based on fuzzy logic controller (FLC). The expert control of yam storage system is formulated in the form of fuzzy rules. The inputs to the controller are the outside and inside temperature, wind speed and presences of rain. The output is the window opening angle. Simulations were performed for different typical levels of input parameters and also for extreme fictitious conditions. The results shown that, the controller is capable of responding to the changes in temperature conditions by adjusting the window opening angle to keep the internal temperature within acceptable range. The controller also satisfies security requirements due to sudden changes in wind velocity and presence of rain

A matlab-based low-cost autopilot for autonomous helicopter development

The challenges associated with the software and hardware integration activities in development of flight autopilot system for autonomous helicopter have called for a change of tactics. The resulting effect is for example, a long time delay in autopilot system design, testing and deployment coupled with the fact that several other autonomous helicopter development tasks depend largely on availability of the autopilot system. Though, the use of off-the-shelf autopilot for a flight control system may ease these challenges, they are generally characterized with limited functionalities, and restrict the user’s design authority. As alternative approach, this paper presents the development of a MATLAB-based autopilot system for autonomous helicopter development. This approach provides an integrated design environment for rapid-prototyping of a low-cost autopilot system. The results of real-time application of the autopilot for flight data logging are presented. The performance shows the effectiveness of the developed autopilot system in small scale autonomous helicopter design and implementation. This is hope to reduce the design cycle time involves in the deployment of small scale autonomous helicopter in various civil low-cost, small payload applications

Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. The DE at the upper level is formulated as combinatorial optimization to search for the network architecture while the associated network weights that minimize the prediction error is provided by the GA at the lower level. The performance of the algorithm is evaluated on identification of a laboratory rotary motion system. The system identification results show the effectiveness of the proposed algorithm for nonparametric model development

Artificial intelligent based friction modelling and compensation in motion control system

The interest in the study of friction in control engineering has been driven by the need for 10 precise motion control in most of industrial applications such as machine tools, robot 11 systems, semiconductor manufacturing systems and Mechatronics systems. Friction has 12 been experimentally shown to be a major factor in performance degradation in various 13 control tasks. Among the prominent effects of friction in motion control are: steady state 14 error to a reference command, slow response, periodic process of sticking and sliding (stick-15 slip) motion, as well as periodic oscillations about a reference point known as hunting when 16 an integral control is employed in the control scheme. Table 1 shows the effects and type of 17 friction as highlighted by Armstrong et. al.(1994). It is observed that, each of task is 18 dominated by at least one friction effect ranging from stiction, or/and kinetic to negative 19 friction (Stribeck). Hence, the need for accurate compensation of friction has become 20 important in high precision motion control. Several techniques to alleviate the effects of 21 friction have been reported in the literature (Dupont and Armstrong, 1993; Wahyudi, 2003; 22 Tjahjowidodo, 2004; Canudas, et. al., 1986). 23 One of the successful methods is the well-known model-based friction compensation 24 (Armstrong et al., 1994; Canudas de Wit et al., 1995 and Wen-Fang, 2007). In this method, 25 the effect of the friction is cancelled by applying additional control signal which generates a 26 torque/force. The generated torque/force has the same value (or approximately the same) 27 with the friction torque/force but in opposite direction

Matlab-Based Algorithm for Real Time Analysis of Multiexponential Transient Signals

Multiexponential transient signals are particularly important due to their occurrences in many natural phenomena and human applications. For instance, it is important in the study of nuclear magnetic resonance (NMR) in medical diagnosis (Cohn-Sfetcu et al., 1975)), relaxation kinetics of cooperative conformational changes in biopolymers (Provencher, 1976), solving system identification problems in control and communication engineering (Prost and Guotte, 1982), fluorescence decay of proteins (Karrakchou et al., 1992), fluorescence decay analysis (Lakowicz, 1999). Several research work have been reported on the analysis of multicomponent transient signals following the pioneer work of Prony in 1795 (Prony, 1975) and Gardner et al. in 1959 (Gardner, 1979). Detailed review of several techniques for multicomponent transient signals’ analysis was recently reported in (Jibia, 2010)