This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization ...
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This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters initiatively applied to ensure the uncertain nonlinear humanoid robot walks robustly and steadily. The efficiency of the proposed Jaya-based identification approach is compared with the central force optimization and improved differentialevolution (modifieddifferentialevolution) algorithms. The simulation and experimental results tested on the original small-sized biped robot HUBOT-4 convincingly demonstrate that the novel proposed algorithm offers an efficient and stable gait for humanoid robots with precise height of foot-lift value.
A controlled nonlinear system, in which the feed rates of glycerol and alkali are taken as the control function, is proposed to formulate the fed-batch culture of 1,3-propanediol(1,3-PD) production. To maximize the 1,...
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A controlled nonlinear system, in which the feed rates of glycerol and alkali are taken as the control function, is proposed to formulate the fed-batch culture of 1,3-propanediol(1,3-PD) production. To maximize the 1,3-PD concentration at the terminal time, an optimal control problem subject to constraints of continuous state and control is then presented. A solution approach is developed to seek the optimal feed rates based on control parameterization method and modified differential evolution algorithm. Numerical results show that the concentration of 1,3-PD at the terminal time can be increased considerably compared with previous results.
A modifieddifferentialevolution (MDE) algorithm, for solving short-term hydrothermal scheduling problem is presented. Hydrothermal scheduling involves the optimisation of a nonlinear objective function with a set of...
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A modifieddifferentialevolution (MDE) algorithm, for solving short-term hydrothermal scheduling problem is presented. Hydrothermal scheduling involves the optimisation of a nonlinear objective function with a set of operational and physical constraints. differentialevolution, an improved version of a genetic algorithm, is a very simple, fast and robust global optimisation technique. The differentialevolutionalgorithm is modified in order to handle the reservoir end volume constraints in the hydrothermal scheduling. The transmission losses are also accounted for through the use of loss coefficients. The study is extended for the combined economic emission dispatch. The performance of the proposed approach is validated by illustration with two test systems. The results of the proposed approach are compared with those of dynamic programming, nonlinear programming, genetic algorithm and evolutionary programming techniques. From the numerical results, it is found that the modified DE based approach is able to provide a better solution at a lesser computational effort.
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