Luenberger Observer Gain Optimization in Model Predictive Control System for Car Active Suspension

MPC Driven control systems very often are requiring the introduction of a mechanism predicting the state of the object unavailable for measurements. Depending on the case, a different number of state variables will be unobtainable. Widely used systems to obtain essential data of the condition of an object are Luenberger state observer and different types of Kalman filters. The authors propose a new method of Luenberger observer synthesis based on Luenberger gain optimization using performance index corresponding to generalized system performance. The developed method allows us to obtain better-performing observer from the point of view of the adopted criterion, compared to similar estimators derived from the Sylvester equation and classic Kalman filters, even despite the occurrence of disturbances. The developed method will be presented on an example of an active suspension system with MPC.

Entropy based C4.5-SHO algorithm with information gain optimization in data mining

Information efficiency is gaining more importance in the development as well as application sectors of information technology. Data mining is a computer-assisted process of massive data investigation that extracts meaningful information from the datasets. The mined information is used in decision-making to understand the behavior of each attribute. Therefore, a new classification algorithm is introduced in this paper to improve information management. The classical C4.5 decision tree approach is combined with the Selfish Herd Optimization (SHO) algorithm to tune the gain of given datasets. The optimal weights for the information gain will be updated based on SHO. Further, the dataset is partitioned into two classes based on quadratic entropy calculation and information gain. Decision tree gain optimization is the main aim of our proposed C4.5-SHO method. The robustness of the proposed method is evaluated on various datasets and compared with classifiers, such as ID3 and CART. The accuracy and area under the receiver operating characteristic curve parameters are estimated and compared with existing algorithms like ant colony optimization, particle swarm optimization and cuckoo search.

High data rates in optic fiber systems based on the gain optimization techniques

The signal gain is improved by nearly about 15 dB by using the hybrid optical amplifiers technique. The gain flattened filter technique has outlined a larger value of signal gain than the hybrid optical amplifiers technique by about 17 dB whereas the Glass Composition method in the hybrid modified model has a better increase in the optimum value of signal gain that reached to about 70 dB. Fiber Bragg Grating (FBG) technique has outlined optimum gain value that is reached to about 50 dB. The combination of these techniques are used for the best optimized value of signal gain.

A Novel PID Robotic for Speed Controller Using Optimization Based Tune Technique

One of the most significant issue of proportional integral derivative (PID) controller is the efforts to optimize coefficient gains. Based on survey, massive tuning methods were proposed to resolve this problem but there is little pay attention to maximize minimization time response significantly. This study proposed a novel technique to maximize optimization PID gains for the DC motor controller by combining both proper tuning method with signal input signal output (SISO) optimization toolbox using optimization based tune (OBT) techniques, that could be utilized for the highest precision controller. The comparative study has been carried out by applying five different tuning methods to obtain a proper tuning controller, then to be combined with SISO optimization toolbox. The utilized tuning methods are Robust Auto tune (RAT), Ziegler–Nichols (Z-N), Skogestad Internal Model Control (SIMC), Chien Hroues Reswick (CHR), and Approximate M-Constrained Integral Gain Optimization (AMIGO). The performance of each tuning methods based OBT are analyzed and compared using MATLAB/SISO tool environment, where the efficiency has been assessed on a basis of time response characteristics (Ti) in terms of dead time (td), rise time (tr), settling time (ts), peak time (tp) and peak overshoot (Pos). The simulation results of AMIGO based proposal show a significant reduction time response characteristic to be measured in the Microsecond unit (μs). The novelty feature of the proposed is that provides superior balancing between robustness and performance. This study has been completely rewritten to account for the robotic controller development that has been taken place in the last years.