Model Predictive Control

Model Predictive Control (MPC) is a control strategy that uses a mathematical model of the system to predict its future behavior and optimize a control action over a finite time horizon. MPC is widely used in process control, robotics, and autonomous systems. The mathematical model is used to predict the future behavior of the system based on the current state and the control inputs. The optimization problem is solved at each time step to find the optimal control action that minimizes a cost function while satisfying constraints. The cost function can be designed to achieve various objectives such as tracking a reference trajectory, minimizing energy consumption, or maximizing the system performance. MPC is a powerful control strategy that can handle complex systems with nonlinear dynamics and constraints. It can also handle disturbances and uncertainties in the system by updating the model and the control action in real-time.
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