An Arithmetic-Trigonometric Optimization Algorithm with Application for Control of Real-Time Pressure Process Plant.

Area of Science:

• Computational Intelligence
• Optimization Algorithms
• Real-time Systems

Background:

• Complex real-time problems require advanced optimization techniques.
• Existing algorithms like Sine Cosine Algorithm (SCA) and Arithmetic Optimization Algorithm (AOA) have limitations in convergence and search area.
• Hybrid approaches can potentially overcome these limitations.

Purpose of the Study:

• To propose a novel hybrid arithmetic-trigonometric optimization algorithm (ATOA).
• To enhance the convergence rate and optimal search area for complex and continuously evolving real-time problems.
• To evaluate the performance of ATOA on diverse optimization test problems and a real-time pressure process plant.

Main Methods:

• Developing a hybrid optimization algorithm (ATOA) by integrating sine, cosine, and tangent functions with SCA and AOA.
• Simulating ATOA on 33 distinct multi-dimensional optimization test problems.
• Applying different variants of ATOA to tune controller parameters for a real-time pressure process plant.

Main Results:

• ATOA demonstrated improved convergence rate and expanded optimal search area compared to conventional methods.
• The algorithm showed remarkable performance improvements across 33 diverse optimization test problems.
• ATOA variants effectively obtained controller parameters for the real-time pressure process plant.

Conclusions:

• The proposed hybrid arithmetic-trigonometric optimization algorithm (ATOA) is effective for complex real-time optimization.
• ATOA offers significant advantages in convergence and search efficiency over existing algorithms.
• ATOA shows practical applicability in real-world engineering problems, such as process control.