Gravitational Search Algorithm Optimization for PID Controller Tuning in Waste-water Treatment Process

2015 ◽  
Vol 73 (3) ◽  
Author(s):  
Mohamad Saiful Islam Aziz ◽  
Sophan Wahyudi Nawawi ◽  
Shahdan Sudin ◽  
Norhaliza Abdul Wahab ◽  
Mahdi Faramarzi ◽  
...  
Keyword(s):  
Pid Controller ◽  
Treatment Process ◽  
Search Algorithm ◽  
Waste Water Treatment ◽  
Gravitational Search Algorithm ◽  
Water Treatment Process ◽  
Pid Controller Tuning ◽  
Gravitational Search ◽  
Law Of Gravity

This paper presents a new approach of optimization technique in the controller parameter tuning for waste-water treatment process (WWTP) application. In the case study of WWTP, PID controller is used to control substrate (S) and dissolved oxygen (DO) concentration level. Too many parameters that need to be controlled make the system becomes complicated. Gravitational Search Algorithm (GSA) is used as the main method for PID controller tuning process. GSA is based on Newton's Law of Gravity and mass interaction. In this algorithm, the searcher agents survey the masses that interact with each other using law of gravity and law of motion. For WWTP system, the activated sludge reactor is used and this system is multi-input multi-output (MIMO) process. MATLAB is used as the platform to perform the simulation, where this optimization is compared to other established optimization method such as the Particle Swarm Optimization (PSO) to determine whether GSA has better features compared to PSO or vice-versa. Based on this case-study, the results show that transient response of GSA-PID was 20%-30% better compared to transient response of the PSO-PID controller.

Direct Gravitational Search Algorithm for Global Optimisation Problems

2016 ◽  
Vol 6 (3) ◽  
pp. 290-313 ◽  
Author(s):  
Ahmed F. Ali ◽  
Mohamed A. Tawhid
Keyword(s):  
Heuristic Algorithm ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Direct Method ◽  
Gravitational Search Algorithm ◽  
Optimal Solution ◽  
Slow Convergence ◽  
Gravitational Search ◽  
Law Of Gravity ◽  
Number Of Iterations

AbstractA gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed to the Nelder-Mead method to refine it and avoid running iterations that provide negligible further improvement. We test the DGSA on 7 benchmark integer functions and 10 benchmark minimax functions to compare the performance against 9 other algorithms, and the numerical results show the optimal or near optimal solution is obtained faster.

A Gravitational Search Algorithm Approach for Optimizing Closed-Loop Logistics Network

2012 ◽  
pp. 1768-1789
Author(s):  
Abdolhossein Sadrnia ◽  
Hossein Nezamabadi-Pour ◽  
Mehrdad Nikbakht ◽  
Napsiah Ismail
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimization Methods ◽  
Total Cost ◽  
Logistics Network ◽  
Network Problems ◽  
Gravitational Search ◽  
Law Of Gravity

Since late in the 20th century, various heuristic and metaheuristic optimization methods have been developed to obtain superior results and optimize models more efficiently. Some have been inspired by natural events and swarm behaviors. In this chapter, the authors illustrate empirical applications of the gravitational search algorithm (GSA) as a new optimization algorithm based on the law of gravity and mass interactions to optimize closed-loop logistics network. To achieve these aims, the need for a green supply chain will be discussed, and the related drivers and pressures motivate us to develop a mathematical model to optimize total cost in a closed-loop logistic for gathering automobile alternators at the end of their life cycle. Finally, optimizing total costs in a logistic network is solved using GSA in MATLAB software. To express GSA capabilities, a genetic algorithm (GA), as a common and standard metaheuristic algorithm, is compared. The obtained results confirm GSA’s performance and its ability to solve complicated network problems in closed-loop supply chain and logistics.

OPTIMAL TIMAH TASOH RESERVOIR IN, PERLIS: AN OPERATION USING THE GRAVITATIONAL SEARCH ALGORITHM (GSA)

2015 ◽  
Vol 77 (30) ◽  
Author(s):  
Asmadi Ahmad ◽  
Siti Fatin Mohd Razali ◽  
Ahmed El-Shafie ◽  
Zawawi Samba Mohamad
Keyword(s):  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Inertial Mass ◽  
Storage Condition ◽  
Sustainable Engineering ◽  
Release Policy ◽  
Gravitational Search ◽  
The Times ◽  
Law Of Gravity

The construction of a dam or a reservoir can have a serious impact the environment. When dealing with the increasing water demand from irrigation and water supply, alternative solution has to be sought way rather than building a new dam. Therefore, reservoir optimization can be employed as a new approach in sustainable engineering to solve this kind of problem. In this paper an optimization algorithm based on the Newton law of gravity, which is called Gravitational Search Algorithm (GSA), is introduced for optimal reservoir operation study. In GSA, every mass has four specifications, which are position, inertial mass, active gravitational mass, and passive gravitational.  The location of the mass is the solution of the problem, with the gravitational and inertial masses being determined by using a fitness function. Furthermore, The algorithm was applied to the Timah Tasoh reservoir and the release policy was tested by using simulation of demand and release. The result revealed that 72% of the times the reservoir managed to fulfill the demand to the users. Moreover, with the new optimized release policy, the dam operator can manage the reservoir release for the users by determining the inflow pattern, as well as by and observing the current storage condition as a guideline

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