Mehmood Ammara, Chaudhary Naveed Ishtiaq, Zameer Aneela, Raja Muhammad Asif Zahoor
Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad, Pakistan.
Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan.
ISA Trans. 2019 Aug;91:99-113. doi: 10.1016/j.isatra.2019.01.042. Epub 2019 Feb 6.
In this work, novel application of evolutionary computational heuristics is presented for parameter identification problem of nonlinear Hammerstein controlled auto regressive auto regressive (NHCARAR) systems through global search competency of backtracking search algorithm (BSA), differential evolution (DE) and genetic algorithms (GAs). The mean squared error metric is used for the fitness function of NHCARAR system based on difference between actual and approximated design variables. Optimization of the cost function is conducted with BSA for NHCARAR model by varying degrees of freedom and noise variances. To verify and validate the worth of the presented scheme, comparative studies are carried out with its counterparts DE and GAs through statistical observations by means of weight deviation factor, root of mean squared error, and Thiel's inequality coefficient as well as complexity measures.
在这项工作中，通过回溯搜索算法（BSA）、差分进化（DE）和遗传算法（GAs）的全局搜索能力，提出了进化计算启发式方法在非线性哈默斯坦控制自回归自回归（NHCARAR）系统参数识别问题中的新应用。基于实际设计变量与近似设计变量之间的差异，均方误差度量用于NHCARAR系统的适应度函数。通过改变自由度和噪声方差，利用BSA对NHCARAR模型进行成本函数优化。为了验证和确认所提方案的价值，通过统计观测，利用权重偏差因子、均方根误差、泰尔不等式系数以及复杂度度量等，与DE和GAs等同类方法进行了对比研究。
