Forthcoming articles


International Journal of Process Systems Engineering


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International Journal of Process Systems Engineering (2 papers in press)


Regular Issues


  • A Non-Minimum Phase Robust Non-linear Neuro-Wavelet Predictive Control Strategy for a Quadruple Tank Process.   Order a copy of this article
    by Kayode OWA, Asiya Khan, Sanjay Sharma, Robert Sutton 
    Abstract: In process industries model-plant mismatch is a significant problem. Quadruple Tank Process (QTP) can be configured both in minimum phase and non-minimum phase (NMP). However, in NMP, the control of QTP poses a challenge. This paper addresses that and presents a novel robust wavelet based non-minimum phase control (NMPC) strategy for the challenging QTP using genetic algorithm to find the optimised value of the manipulated variables in NMPC at every sampling time. The QTP is modelled based on wavelet neural network. The simulation results indicate that significant improvements have been achieved both in modelling and control strategies for a QTP system compare to conventional approaches such as the Levenberg-Marquardt.
    Keywords: Wavelet Neural Network (WNN); right hand plane zero (RHPZ); non-minimum-phase (NMP); Non-linear Model Predictive Control (NMPC); quadruple-tank process (QTP) Genetic Algorithms (GA); Multi Input Multi Output (MIMO); model-plant mismatch (MPM); Non-linear Optimisation; Coupled Tank System (CTS).

    by Bikram Jit Singh, Rahul Singla 
    Abstract: In recent times, focus has been on developing fast and efficient processes that are environment friendly. The spotlight has been turned on Friction Stir Welding as a joining technology, capable of providing welds that do not have defects normally associated with fusion welding processes. The basic principle of FSW involves simultaneous application of pressure and relative motion, generally in a rotational mode, between the components to be joined. From the available literature, it has been observed that the effect of welding parameters on desired characteristics was determined by taking into consideration one parameter at a time or by using conventional methods. So without ignoring the limitations of earlier researches, the main focus in this study has been kept on welding of dissimilar aluminium alloys (AA6061 and AA5086) by using Design of Experiments which is quite rarely used Multi-Factor at a Time technique. Therefore, the ultimate objective of the work is to optimize critical to process parameters of FSW process for achieving mechanical characteristics within ranges. Fractional Factorial Design of Experiments tool has been used to achieve required optimization in FSW of non-similar aluminium alloys by using well known statistical software known as Minitab-16. The key characteristicsresponse parameters were identified as mechanical properties i.e. tensile strength and hardness of the welded specimen. The statistical optimization values so achieved for tensile strength were 0.165 KN/mm
    Keywords: Aluminium Alloys; Critical to Process Parameters; Design of Experiments; Feed; Friction Stir Welding; Hardness; Optimization; Tensile Strength; Tilt Angle; Tip Plunge Depth; Tool Rotation Speed; Tool Shape; Two Sample t-test; Shoulder Diameter; Weld Specimen.