Control and Optimization
Masoomeh Ebrahimipour; Saeed Nezhadhosein; Seyed Mehdi Mirhosseini-Alizamini
Abstract
This paper presents an optimal robust adaptive technique for controlling a certain class of uncertain nonlinear affine systems. The proposed approach combines sliding mode control, a linear quadratic regulator for optimality, and gradient descent as an adaptive controller. ...
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This paper presents an optimal robust adaptive technique for controlling a certain class of uncertain nonlinear affine systems. The proposed approach combines sliding mode control, a linear quadratic regulator for optimality, and gradient descent as an adaptive controller. The convergence of the sliding mode control process is proven using two theorems based on the Lyapunov function. Simulation results for pendulum and inverted pendulum systems demonstrate that the proposed method outperforms both the linear quadratic regulator technique and the sliding mode control regarding reduced chattering and improved reaching time.
Abbas Bashiri; Seyed Mehdi Mirhosseini-Alizamini; Mohammad Mehdi Nasrabadi
Abstract
Evaluation of advertising marketing campaigns is a very important and complex task, so far no comprehensive model has been presented in this regard. The present study aims to provide a decision framework for evaluating marketing campaigns. This article collects real-world ...
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Evaluation of advertising marketing campaigns is a very important and complex task, so far no comprehensive model has been presented in this regard. The present study aims to provide a decision framework for evaluating marketing campaigns. This article collects real-world data from an Iranian bank deposit marketing campaign. For this purpose, 250 cases were considered to extract the rules and 60 cases were considered as test data. Information is provided on 15 important parameters of marketing education, defaults, age, occupation, marriage, day, contact, balance, housing, loans, previous contact, previous outcome, month, call duration, and campaigns. A fuzzy expert system was designed with 12 rules after reviewing the rules and removing similar and contradictory rules by using their degree calculation. In this system, by integrating some factors, finally, 6 input variables and one output variable were considered that were used by the product inference engine, singleton fuzzifier, and center average defuzzifier. It was observed that the designed fuzzy expert system provides very good results.
