A novel model predictive control scheme based on bees algorithm in a class of nonlinear systems: Application to a three tank system

• A bees algorithm is used to solve the open loop optimization problem in a MPC.
• Application to nonlinear autonomous systems with continuous and discrete inputs.
• Main features of the method are computation time reduction and control management.
• The proposed method has been applied to a three tank system as a case study.
• Comparison with a traditional optimization method (MILP) has been provided.

This paper proposes a novel algorithm for utilizing bees algorithm in a model predictive control (MPC) in order to control a class of nonlinear systems. The bees algorithm is utilized in order to solve the open loop optimization problem (OOP), and it is based on the foraging behavior of honey bees. The proposed algorithm makes use of the bees algorithm for minimizing a predefined cost function in order to find the best input signals subject to constraints and a model of the system. The class of systems considered in this paper includes autonomous nonlinear systems without delay and with continuous and discrete inputs. The proposed algorithm is validated by simulating a three tank system as a case study. A comparison between the proposed novel MPC with different predictive horizons and a conventional MPC demonstrates the potential advantages of the proposed method such as reduction in computation time, good convergence toward desired values and ability of control management. Simulations also show the simplicity of applying and efficiency of the proposed algorithm for designing an MPC based on the bees algorithm.