Robotic manipulators are extremely nonlinear complex and, uncertain systems. They have multi-input multi-output (MIMO) dynamics, which makes controlling manipulators difficult. Robotic manipulators have wide applications in many industries like processes, medicine, and space. Effective control of these manipulators is extremely important to perform these industrial tasks. Researchers are working on the control of robotic manipulators using conventional and intelligent control methods. Conventional control methods are proportional integral and derivative (PID), Fractional order proportional integral and derivative (FOPID), sliding mode control (SMC), and optimal & robust control while intelligent control method includes Artificial Neural network (ANN), Fuzzy logic control (FLC) and metaheuristic optimization algorithms based control schemes. This paper presents the trajectory control of a robotic manipulator using a PID controller. Four different meta-heuristic algorithms namely Sooty tern optimization (STO), Spotted Hyena optimizer (SHO), Atom Search optimization (ASO), and Arithmetic Optimization algorithm (AOA) are used to optimize the gains of PID controller for trajectory control of a two-link robotic manipulator and a novel hybrid sooty tern and particle swarm optimization (STOPSO) has been designed. These optimization techniques are nature-inspired algorithms that give the optimal gain values while minimizing the performance indices. A performance index comprising Integral time absolute error (ITAE) having weights for both links has been considered to achieve the desired trajectory. These optimization techniques are stochastic in nature so statistical analysis and Freidman’s ranking test has been performed to evaluate the effectiveness of these algorithms. The proposed hybrid STOPSO provided a fitness value of 0.04541 and showed a standard deviation of 0.0002. A comparative study of these optimization techniques is presented and as a result, hybrid STOPSO provides the best results with minimum fitness value followed by STO, AOA, ASO, and SHO algorithms.
Development and progression of metastasis comprises synchronized erroneous expressions of several composite pathways, which are difficult to manage simultaneously with the representative anticancer molecules. The emergence of the drug resistance and the complex interplay between these pathways further potentiates cancer related complexities. Barbiturates and their derivatives present a commendable anticancer profile by attenuating the cancer manifesting metabolic and enzymatic pathways including, but not limited to matrix metalloproteinases, xanthine oxidase, amino peptidases, histone deacetylases, and Ras/mitogen‐activated protein kinase. The derivatization and conjugation of barbiturates with pharmacophores delivers a suitable hybrid profile in containing the anomalous expression of these pathways. The present report presents a succinct collation of the barbiturates and their derivatives in managing the various cancer causing pathways.
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