Spider Search Algorithms for MIMO System and Assessment Using Simatic PCS7

This paper shows two optimization methods that are built on a spider optimization algorithm to enhance the proportional integral and derivative (PID) gain values for multiple-input-multiple-output (MIMO) arrangement which is automated with SIMATIC PCS7 Distributed Control System (SDCS). The leading methodologies are the Spider Search Algorithm (SSA) and Social Spider Optimization (SSO) which is meant primarily for optimizing PID gain values. The SSA is based on foraging strategy of colonial spiders and SSO works on the combined plan of the male and female spiders that removes the episodes of local optimization and exploration elusion. Thus, SSA and SSO are contrived for the ideal fine-tuning of PID conditions in the benchmark MIMO procedure. The system performance is understood by minimizing the integral absolute error (IAE) and the integral square error (ISE) as its objective functions. The time-domain features are examined for the aforesaid methods and thereafter compared with the previous genetic algorithm (GA). The settling time is 60s for the proposed method which is lesser than the other techniques. For illustrating the implemented controller\u27s strength, interference is manually presented in the real-time system. Findings indicate that the SSO surpasses output measures and performance indices beyond the presupposed SSA and GA intervals

A Brief Survey on Intelligent Swarm-Based Algorithms for Solving Optimization Problems

This chapter presents an overview of optimization techniques followed by a brief survey on several swarm-based natural inspired algorithms which were introduced in the last decade. These techniques were inspired by the natural processes of plants, foraging behaviors of insects and social behaviors of animals. These swam intelligent methods have been tested on various standard benchmark problems and are capable in solving a wide range of optimization issues including stochastic, robust and dynamic problems

A new design algorithm for hybrid active power filter

The correct determination of the parameters of Hybrid Active Power Filter (HAPF) plays a decisive role in its performance. Therefore, this paper proposes a new design algorithm for HAPF based on the Social Spider Algorithm (SSA). This algorithm has the advantage that it is possible to determine the parameters of both the power circuit part and the control circuit part of HAPF. The achieved results are multi-purpose, such as: minimum total harmonic distortion of the supply current and source voltage, the maximum reactive power compensation into the system and satisfy many constraints such as: system stability, resonance conditions of the branches and the limits of the parameters. Compared to traditional design method using the Particle Swarm Optimization algorithm, the proposed algorithm shows the advantages of smaller total harmonic distortion of supply current and source voltage, and higher reactive power compensation into the grid while still meeting the constraints

A state-of-art optimization method for analyzing the tweets of earthquake-prone region

With the increase in accumulated data and usage of the Internet, social media such as Twitter has become a fundamental tool to access all kinds of information. Therefore, it can be expressed that processing, preparing data, and eliminating unnecessary information on Twitter gains its importance rapidly. In particular, it is very important to analyze the information and make it available in emergencies such as disasters. In the proposed study, an earthquake with the magnitude of Mw = 6.8 on the Richter scale that occurred on January 24, 2020, in Elazig province, Turkey, is analyzed in detail. Tweets under twelve hashtags are clustered separately by utilizing the Social Spider Optimization (SSO) algorithm with some modifications. The sum-of intra-cluster distances (SICD) is utilized to measure the performance of the proposed clustering algorithm. In addition, SICD, which works in a way of assigning a new solution to its nearest node, is used as an integer programming model to be solved with the GUROBI package program on the test data-sets. Optimal results are gathered and compared with the proposed SSO results. In the study, center tweets with optimal results are found by utilizing modified SSO. Moreover, results of the proposed SSO algorithm are compared with the K-means clustering technique which is the most popular clustering technique. The proposed SSO algorithm gives better results. Hereby, the general situation of society after an earthquake is deduced to provide moral and material supports