Papers by Dur Muhammad Pathan
Communications in Computer and Information Science, 2012
MPC (Model Predictive Control) techniques, with constraints, are applied to a nonlinear vehicle m... more MPC (Model Predictive Control) techniques, with constraints, are applied to a nonlinear vehicle model for the development of an ACC (Adaptive Cruise Control) system for transitional manoeuvres. The dynamic model of the vehicle is developed in the continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. A parametric study for the MPC method is conducted to analyse the response of the ACC vehicle for critical manoeuvres. The simulation results show the significant sensitivity of the response of the vehicle model with ACC to controller parameter and comparisons are made with a previous study. Furthermore, the approach adopted in this work is believed to reflect the control actions taken by a real vehicle.
Mehran University Research Journal of Engineering and Technology, 2012
This paper provides the finite-difference solutions for closed contra-rotating discs flows at dif... more This paper provides the finite-difference solutions for closed contra-rotating discs flows at different disc speed ratios for a fixed value of rotational Reynolds number of order five. The flow structure reveals that when two discs rotate in opposite directions, the fluid mass outside the boundary layers is divided between two regions, which give rise to the formation of two-cell flow structure. In order to assess the different level of closures, two turbulence models low Reynolds number k-? model and low Reynolds number second moment closure have been employed to predict the essential features of the closed contra-rotating disc system. The most significant differences between the predictions of the two turbulence models occur at the peak of slower disc boundary layer, because flow is more complex and turbulent on this side. The comparison of predicted velocity profiles of two turbulence models show that the low Reynolds number second moment closure produce a better agreement with m...
Mehran University Research Journal of Engineering and Technology, 2012
Two different control algorithms, sliding mode and MPC (Model Predictive Control) are employed to... more Two different control algorithms, sliding mode and MPC (Model Predictive Control) are employed to analyse the performance of a linear vehicle model equipped with an ACC (Adaptive Cruise Control) system. Both controllers are analysed under critical TM (Transitional Maneuvers) to investigate their suitability for the ACC system. The simulation results, for the same scenario, from both controllers' approach have been compared. The results show that the MPC is more robust than the SMC (Sliding Model Controller). The results show that the SMC algorithm is not suitable for the proposed vehicle model. The shortcomings of the SMC have been highlighted and the comparisons are made with the previous studies. The proposed approach can be useful for the selection of the appropriate controller for the given application.
Sindh University Research Journal, 2013
In this paper, design, development and validation of a test rig to characterise shape memory allo... more In this paper, design, development and validation of a test rig to characterise shape memory alloy (SMA) actuators is presented. Sensors for measurement of strain, force and temperature were selected and calibrated. The test rig used a CCD (charge coupled device) based laser displacement sensor to accurately measure strain. An enclosure was also developed for isolating actuators from the ambient air currents. Laboratory Virtual Instrument Workbench (LabVIEW) software was used to actuate the wire actuators and record the test data. To validate the rig, two Nickel-Titanium based SMA actuators 0.2 mm in diameter were tested. The results of those tests were found compatible with the data sheet provided by the manufacturer.
Mehran University Research Journal of Engineering and Technology, 2012
PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control) algorithms are used to ... more PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control) algorithms are used to synthesize the upper-level controller of a vehicle equipped with an ACC (Adaptive Cruise Control) system. Both controllers are analysed, with and without constraints, using a simple vehicle model under critical TM (Transitional Manoeuvres). A comparative analysis of both controllers’ results has been conducted. The comparison gives the suitability of MPC for ACC application over PID controller. The flaws of PID control approach for the given application are highlighted. This approach can be helpful for selecting the suitable controller for the given application.
IET Radar, Sonar & Navigation, 2019
In heavily cluttered environments, it is difficult to estimate the uncertain motion of an unknown... more In heavily cluttered environments, it is difficult to estimate the uncertain motion of an unknown number of targets with low detection probabilities. In particular, for tracking multiple targets, standard multi-target data association algorithms such as joint integrated probabilistic data association (JIPDA), face complexity and severely limited applicability due to a combinatorially increasing number of possible measurement-to-track associations. Smoothers refine the target estimates based on future scan information. However, in this complex surveillance scenario, existing smoothing algorithms often fail to track the true target trajectories. To overcome such difficulties, this study proposes a new smoothing joint measurement-to-track association algorithm called fixed-interval smoothing JIPDA for tracking extended target trajectories (FIsJIPDA). The algorithm employs two independent JIPDA filters: forward JIPDA (fJIPDA) and backward JIPDA (bJIPDA). fJIPDA tracks the target state forward in time and is computed after the smoothing is achieved. bJIPDA estimates the target state in the backward time sequence. The numerical simulation is performed in a heavily populated cluttered environment with low target-detection probabilities. The results show better target trajectory accuracy and false-track discrimination performance of FIsJIPDA compared with that of existing algorithms for tracking multiple extended targets.
This paper explores the potential of fuzzy logic and neural networks controllers for heading moti... more This paper explores the potential of fuzzy logic and neural networks controllers for heading motions of ship and analyses the performance of both controllers. For this purpose two separate; neural network and fuzzy logic controllers are developed. For neural network Multi-Layer Perceptron (MLP) network is used. The training of network is carried out by using back-propagation algorithm. For fuzzy logic controller Mamdani type Fuzzy Inference System (FIS) is used. The fuzzification of variables is based on triangular functions and the defuzzification is carried out by using centroid method. The processing of Inference system is carried out by developing 49 rules. For comparative analysis of both controllers during developing of controllers the parameters of controllers are kept same.
This paper presents the implementation of Multi-layer Preceptron (MLP) Feed-forward Neural Networ... more This paper presents the implementation of Multi-layer Preceptron (MLP) Feed-forward Neural Networks for direction control of an oil tanker, whose parameters vary with depth of water and randomly varying waves. The development of Artificial Neural Networks (ANN) controller is based on learning of networks, for this purpose back-propagation algorithm is used. For training, a nonlinear sliding mode controller is used as a supervisor. A network having one input, one hidden and one output layer has provided the satisfactory performance. The input layer has four neurons, the hidden layer has seven neurons and output layer has one neurons. The controller is developed for ideal conditions, to assure the robustness of controller the performance of controller is tested in different operating conditions; varying depth of water and in presence of wind generated waves. It has been demonstrated that the performance of controller remained satisfactory in all operating conditions.
This paper presents the performance of ANN (Artificial Neural Networks) technique for the develop... more This paper presents the performance of ANN (Artificial Neural Networks) technique for the development of controller for heading motions of submarine. A MLP (Multi-Layer Preceptron) FFNN (Feed-Forward Neural Network) is used for development of controller. Supervised type of learning is used for training of network by using back-propagation Algorithm. The training is performed by providing a nonlinear sliding mode controller as a supervisor. The development of controller is based on nonlinear decoupled heading model of a submarine without consideration of external environmental disturbances. To demonstrate the robustness of controller the performance of controller is tested in different operating conditions: course changing, track keeping and under the influence of sea currents. Simulations results show that in all cases, the heading error comes to zero, which indicates that the actual heading converges to the desired heading in finite time. The maximum error is observed 0.5 o for 45 o command angle, in presence of sea currents. The result demonstrates that the performance neural network controller has been robust.
Arabian Journal of Geosciences, 2014
Precise determination of engineering properties of soil is essential for proper design and succes... more Precise determination of engineering properties of soil is essential for proper design and successful construction of any structure. The conventional methods for determination of engineering properties are invasive, costly, and time-consuming. Geoelectrical survey is a very attractive tool for delineating subsurface properties without soil disturbance. Proper correlations of various soil parameters with electrical resistivity of soil will bridge the gap between geotechnical and geophysical engineering and also enable geotechnical engineers to estimate geotechnical parameters from electrical resistivity data. The regression models of relationship between electrical resistivity and various soil properties used in the current research for the purpose of comparison with artificial neural network (ANN) models were adopted from the work of Siddiqui and Osman (Environ Earth Sci 70:259-26, 2013). In order to obtain better relationships, ANN modeling was done using same data as regression analysis. The neural network models were trained using single input (electrical resistivity) and single output (i.e., moisture content, plasticity index, and friction angle). Twenty (20) multilayer feedforward (MLFF) networks were developed for each properties, ten (10) each for two different learning algorithms, Levenberg-Marquardt (LM) and scaled conjugate gradient (SCG). The numbers of neurons in hidden layer were experimented from 1 to 10. Best network with particular learning algorithm and optimum number of neuron in hidden layer presenting lowest root mean square error (RMSE) was selected for prediction of various soil properties. ANN models show better prediction results for all soil properties.
2005 Pakistan Section Multitopic Conference, 2005
In under ocean research, submarine plays indispensable role for collecting the facts and operatin... more In under ocean research, submarine plays indispensable role for collecting the facts and operating under sea. Due to working under ocean the task of submarine is risky for crew as well as for submarine itself. Therefore a dire investigation is needed for accurate and reliable maneuvering of submarine. A reliable and autonomous control system guarantees the safety of mission. Due
3C Tecnología_Glosas de innovación aplicadas a la pyme, 2019
For the intake of air fuel mixture and exhaust of gases camshaft operated valves are mounted on t... more For the intake of air fuel mixture and exhaust of gases camshaft operated valves are mounted on the cylinder head. In this paper, we have proposed a novel physical model of a shutter valve to replace the traditional camshaft operated valve resulting in a camless four-stroke engine. The lift control for the opening and closing of the intake and exhaust valves are monitored traditionally by a camshaft which is a mechanical component having a fixed shape. A camless engine replaces the camshaft by allowing the control of valves through the Electronic Control Unit (ECU). The already developed valves have limitations in terms of lift, life expectancy or higher costs. This research work proposes a novel shutter valve design instead of a poppet valve for intake and exhaust of fourstroke engines. These valves are then operated directly by an ECU and controlled through pulse width modulation. The proposed variation in shutter valve design optimally adjusts and controls the fuel intake amount and the flow of exhaust gases in and out of the cylinder respectively. The opening of the valve can be set to maximum or at the desired angle so that the engine can run according to the driver's requirement. The novel design of the shutter valve will reduce the engine cost and will improve the fuel economy. At the same time, providing complete control to the driver's performance preferences.
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Papers by Dur Muhammad Pathan