A Novel Modified Adaptive Controller Design for Non Negative DC-DC Converter Using Meta-Heuristic Algorithms for Bio Medical Hybrid Application

M. Moses, S. Rajarajacholan
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Abstract

Purpose: Meta-heuristic (MH) methods are used to develop an adaptive sliding mode controller for a POEL converter. MH algorithms have been used to address a variety of engineering optimization problems. Which will use for Bio medical hybrid systems applications. Design/Methodology: Particle Swarm Optimization (PSO) approach is well known and it could expedite the convergence characteristic in numerous applications. By means of amending PSO parameters like, inertia mass, social and perceptive agents at every generation, Modern Parameter Improved Particle Swarm Optimization (MPIPSO) algorithm which is a more enhanced version of PSO is developed. Findings: Since the converter output voltage’s integral squared error (ISE) has been chosen as a neutral function, the optimal PI controller design may be expressed in terms of optimization problems. Originality/Value: The superiority of the proposed MPIPSO based sliding mode controller has been shown by comparing the results with other existing MH optimization methodologies.
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基于元启发式算法的非负型DC-DC变换器自适应控制器设计
目的:采用元启发式(MH)方法开发一种自适应滑模控制器。MH算法已被用于解决各种工程优化问题。这将用于生物医学混合系统的应用。设计/方法:粒子群优化(PSO)方法是众所周知的,它可以加快收敛特性在许多应用中。通过每一代修正粒子群算法的惯性质量、社会主体和感知主体等参数,提出了一种改进粒子群算法(MPIPSO)。研究结果:由于转换器输出电压的积分平方误差(ISE)被选择为中性函数,因此最优PI控制器设计可以用优化问题来表示。独创性/价值:通过将结果与其他现有的MH优化方法进行比较,表明了所提出的基于MPIPSO的滑模控制器的优越性。
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