Start modelling your plant, namely the induction motor. make clear what are your control inputs and measurement outputs. You can then compute your H infinitiy controller (e.g.with the hinfsyn-command in matlab) from the extended fictive plant including the influence from disturbances and to non-measureable errors respectively (However, defining an appropriate fictive plant is the challenging engineering task). In fact, that gets you a p-cross-m state space model of the controller (where m is the number of real system outputs and p is the number of control inputs) that you can easily implement in simulink using a common state space-block. now just complete your control loop in simulink and you're done.

you can design H-infinity method to control of induction motor. you also can to follow some of my paper related to robot , motor and IC engine  in academia education or some of my papers also add in research gate.

I think you should to find lagrangian formulation for induction motor and implement it in simulink and after that design H infinity controller

Start modelling your plant, namely the induction motor. make clear what are your control inputs and measurement outputs. You can then compute your H infinitiy controller (e.g.with the hinfsyn-command in matlab) from the extended fictive plant including the influence from disturbances and to non-measureable errors respectively (However, defining an appropriate fictive plant is the challenging engineering task). In fact, that gets you a p-cross-m state space model of the controller (where m is the number of real system outputs and p is the number of control inputs) that you can easily implement in simulink using a common state space-block. now just complete your control loop in simulink and you're done.

There are available non-linear models for induction motors in textbooks like "Principles of energy conversion" of J. Meisel. First you have to linearize this model around an equilibrium point, and second you have to consider weighting functions, disturbance bandwidth and level, and uncertainty level into an augmented system as point out Gunter Diehm. In this general H-inf control configuration you can apply the robust control toolbox of Matlab. For can implement on Matlab the linearized state space model of the induction motor and the state space realization of the controller, to test your controller under uncertainties and disturbace. After that take into account that an equilibrium point is different to an operating point in order to compensate it as in "Linearization: Students Forget the Operating Point" of J. Roubal, P. Husek, and J. Stecha. Also, you can implement the non-linear model and test your controller on this model.