Evolution of motion plan for helicopter model using Model Predictive Control

This paper uses Model Predictive Control (MPC) technique to generate a safe motion plan for model helicopter. MPC is a feedback control scheme in which a trajectory optimization is solved at each time step. The first control input of the optimal sequence is applied and the optimization is repeated at each subsequent step. Recent developments in modeling helicopter motion planning have shown that trajectory generation including collision avoidance can be defined by a linear program subject to mixed integer constraints, known as a mixed-integer linear program. In the same way, we may give another approach to generate the trajectory by using quadratic programming. Linear programming and quadratic programming problems can be solved by using the model predictive control. This work generated safe motion plan by using linear and quadratic programming subject to mixed-integer constraints. In this paper, evolution of motion plan is shown with the help of MPT toolbox by using the model predictive control. MPT toolbox supports a number of techniques to support MPC. The motion plan results are shown with evolution of states, evolution of outputs, evolution control moves and active dynamics.