_design-of-a-bioreactor-pid-controller-using-a-hybrid-algorithm-of-particle-swarm-optimization-and-genetic-algorithm.jpg "Design of a bioreactor PID controller using a hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm from velocity engineers Video Screenshot Preview")
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⏲ Duration: 11 min 63 sec
✓ Published: 22-Oct-2020
✓ Published: 22-Oct-2020
Description:
With the advent of robust computational tools that can handle calculations in real-time, engineers have already started developing smart controllers. This paper reports--a hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm (PSOGA) to design a Proportional, Integration, Differentiation (also known as PID) controller for a multiphase bioreactor operating regions. The PSO algorithm models the social behavior of the particles, including velocity, fitness, and the collective memory
With the advent of robust computational tools that can handle calculations in real-time, engineers have already started developing smart controllers. This paper reports--a hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm (PSOGA) to design a Proportional, Integration, Differentiation (also known as PID) controller for a multiphase bioreactor operating regions. The PSO algorithm models the social behavior of the particles, including velocity, fitness, and the collective memory
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