Browsing by Author "Sidek, S. N."

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    Design And Implementation of Dsp-Based Intelligent Controller For Automobile Braking System
    (IIUM Engineering Journal, 2001) Sidek, S. N.; Salami, Momoh-Jimoh E.
    An intelligent braking system has great potential applications especially, in developed countries where research on smart vehicle and intelligent highways are receiving ample attention. The system when integrated with other subsystems like automatic traction control, intelligent throttle, and auto cruise systems, etc will result in smart vehicle maneuver. The driver at the end of the day will become the passenger, safety accorded the highest priority and the journey optimized in term of time duration, cost, efficiency and comfortability. The impact of such design and development will cater for the need of contemporary society that aspires to a quality drive as well as to accommodate the advancement of technology especially in the area of smart sensors and actuators. The emergence of digital signal processor enhances the capacity and features of universal microcontroller. This paper introduces the use of TI DSP, TMS320LF2407 as an engine of the system. The overall system is designed so that the value of inter-vehicle distance from infrared laser sensor and speed of follower car from speedometer are fed into the DSP for processing, resulting in the DSP issuing commands to the actuator to function appropriately.
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    Design of intelligent braking system
    (IEEE, 2000-09-24) Sidek, S. N.; Salami, Momoh-Jimoh E.
    It is anticipated that a variety of cars with diversified features that include anti-lock braking system (ABS), traction control system (TCS), antiskid Steering, collision warning system (CWS) will be more commercially produced to satis@ the consumer needs in the near future. This is parallel to the trend of current technology of manufhcturing smart cars and the &sires of people who always want to have comfortable and safe ride in their vehicles. Mower this type of vehicles can fit much better into the intelligent highway that Malaysian government is planning to have in the near future. Consequently, there is a need to modify the current conventional braking system so as to make it work automatically. This paper considers the use of intelligent controller to achieve the above objective. To ensure high speed of system response, the DSP controller TMS320C24x with - fuzzy algorithm is used in the implementation of this new device. Results of simulation studies using the MATLAB have demonstrated the feasibility of this new system under investigation.
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    Fuzzy logic based intelligent temperature controller for cassava post-harvest storage system
    (International Conference on Artificial Intelligence, Electrical & Electronics Engineering (AIEE ‘15), 2015-05-14) Babawuro, Adamu Y.; Umar, Sambo A.; Fatai, Sado; Salami, Momoh-Jimoh E.; Sidek, S. N.
    Significant amount of stored agricultural products are lost as a result of poor and inefficient storage systems in most developing countries, especially in tropical regions of the world. Improvements on the existing storage methods is important to guarantee food security. This study proposes the development of intelligent temperature control technique for fresh cassava roots crop post-harvest storage system using fuzzy logic controller (FLC). The intelligent controller which has two inputs (error in temperature and rate of change in the error) and one output (change in fan speed) was simulated with the developed storage system model for temperature control of fresh cassava roots crop. The results obtained shows that the controller can track appropriately the reference temperature and also gives good stability and robustness towards input disturbances. Faster response to maintain the storage temperature within acceptable limit close to reference point was also achieved successfully.
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    Parameter estimation of multicomponent transient signals using deconvolution and arma modelling techniques
    (Academic Press, 2003-11-01) Salami, Momoh-Jimoh E.; Sidek, S. N.
    Parameter estimation of transient signals, having real decaying exponential constants, is a difficult but important problem that often arises in many areas of scientific disciplines. The frequency domain method of analysis that involves Gardner transformation and conventional inverse filtering often degrades the quality of the deconvolved data, leading to inaccurate results, especially for noisy data. An improved method that is based on the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined. The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule–Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. The effect of sampling conditions, noise level, number of components and relative sizes of the signal parameters on the performance of this modified method of analysis is examined in this paper. Simulation results show that high-resolution estimates of decay constants can be obtained when the above signal processing techniques are used to analyse multiexponential signals with varied signal-to-noise ratio (SNR). This approach also provides a graphical procedure for detecting and validating the number of exponential signals present in the data. Some computer simulation results are presented to justify the need for this modified method of analysis.
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    Performance evaluation of the deconvolution techniques used in analyzing multicomponent transient signals
    (IEEE, 2000-09-24) Salami, Momoh-Jimoh E.; Sidek, S. N.
    Deconvolution is an important preprocessing procedure often needed in the spectral analysis of transient exponentially decaying signals. Three deconvolution techniques are studied and applied to the problem of estimating the parameters of multiexponential signals observed in noise. Both the conventional and optimal compensated inverse filtering approaches produce data which are further analyzed by SVD-based autoregressive moving average (ARMA) modeling techniques. The third procedure is based on homomorphic filtering and it is implemented by fast Fourier transform (FFT) technique. A comparative study of the performance of the above deconvolution techniques in analyzing multicomponent exponential signals with varied signal-to-noise ratio (SNR) is examined in this paper. The results of simulation studies show that the homomorphic deconvolution technique is most computationally efficient, however, it produces inaccurate estimates of signal parameters even at high SNR, especially with closely related exponents. Simulation results show that the optimal compensation deconvolution technique is indeed a generalized form of the conventional inverse filtering and has the potential of producing accurate estimates of signal parameters from a substantial wide range of SNR data.