## 1 Introduction
This specification can be hardly achieved with pneumatic actuated devices and different actuators (e.g., electric or electromechanical) have to be explored to optimize the performance of the system. Theoretically, using a linear electric motor provides several advantages over pneumatics: the nonlinearities due to airflow and friction of pneumatic actuators are no longer present, resulting in more robust control strategies. Moreover, due to the lack of compressed air supply, the system's compactness and portability can be improved. The implementation of control architectures in human-machine interface applications can rely either on linear controllers or on complex, non-linear controllers, depending on the complexity of the systems considered and on the level of performance to achieve. Examples of control architectures developed for similar applications are hybrid force/position [32; 33] and impedance [34] or admittance [35] controllers. In addition, more complex control schemes have been developed to enhance the performance of traditional control schemes [36; 37]. Although a more refined, articulated control logic can be particularly more effective with respect to simpler architectures, the ease of implementation and reliability of such structures have to be considered during the design process. With respect to pneumatics, electric actuation includes different aspects to be investigated, that may require the definition of more robust control logics, as Model Predictive Control (MPC) [38; 39], Generalized Predictive Control [40], Sliding Mode Control [41; 42], Adaptive Control [43]. In these control architectures, the quality of the results can be directly influenced by the accuracy of the plant model. Moreover, their implementation can also require a deep knowledge about the state of the system, which brings the necessity for additional transducers (if compared to simpler, linear controllers) to monitor the system's variables. In some cases, when such physical quantities cannot be directly measured in a convenient way, software observers aimed at calculating the unknown variables on the basis of the measured ones can be developed. Among the different approaches available, MPC allows designing a controller that is able to operate the system with proficiency within a certain set of constraints (e.g., the maximum peak force achievable by the actuator under safety conditions) by implementing the ability to predict the system's behavior. With respect to other approaches, this solution can help to avoid saturation problems of the control input, and simultaneously taking into account the variability of unknown parameters of the plant through proper state observers. The aim of this paper is to investigate if electric actuation, in combination with MPC, can be used to develop an automatic perturbation device, able to impart accurate short-lasting forces (that we refer to as impulsive forces, with a limited duration of about 75 ms), to be used in dynamic posturographic trials to assess balance recovery skills. With respect to similar systems presented in the literature, which typically are bulky and provide a loss of balance through the BoS, this novel handheld device should enable customizable and repeatable perturbations by regulating the contact force raising from the impact between the human body and the perturbator itself. By accurately setting both the point of application and the magnitude of the perturbation, clinicians can adapt the characteristics of the postural disturb to the physical characteristics of the patient, define wide conditions of investigation, and explore the patterns of postural reactions in a comprehensive and clinically systematic way. The linearized model required to design the control logic is briefly described, as well as the test-bench used to test the control architecture. The model simulations and the experimental trials performed are discussed, with a particular focus on the accuracy and repeatability of the perturbations imparted.