Effective PID controller design using a novel hybrid algorithm for high order systems.

Area of Science:

• Engineering and Technology
• Computational Intelligence
• Optimization Algorithms

Background:

• Optimization algorithms are crucial for solving complex engineering problems.
• Atom Search Optimization (ASO) and Particle Swarm Optimization (PSO) are established algorithms with distinct search mechanisms.
• Balancing exploration and exploitation remains a challenge in optimization.

Purpose of the Study:

• To develop a hybrid optimization algorithm, hybrid atom search particle swarm optimization (h-ASPSO), by merging ASO and PSO.
• To improve the exploration-exploitation balance for enhanced search efficiency.
• To validate the performance of h-ASPSO on high-order real-world engineering problems.

Main Methods:

• Integration of the core principles of Atom Search Optimization and Particle Swarm Optimization.
• Development of the hybrid atom search particle swarm optimization (h-ASPSO) algorithm.
• Application and testing of h-ASPSO on automatic voltage regulator and doubly fed induction generator systems.

Main Results:

• h-ASPSO demonstrated superior convergence speed compared to the original ASO.
• The hybrid algorithm achieved a higher quality of solution in the tested engineering problems.
• h-ASPSO provided promising results for high-order engineering systems with comparable computational cost.

Conclusions:

• The proposed h-ASPSO effectively combines the strengths of ASO and PSO.
• h-ASPSO offers an improved approach for optimizing complex engineering systems.
• The hybrid method shows potential for broader application in advanced engineering design.