## 1 Introduction
Likewise, it is the case of ReWalk, an exoskeleton that combines robotics and human assistance for people who have suffered spinal cord injury [18]. Although several patients have shown huge improvements in their daily life, these kinds of devices have been scarcely developed for children [19]. This shows a lack of socio-philosophical perspective during the definition of the design principles of wearable robotic exoskeletons for people with DMD, which should include a patient-based approach to increase the acceptance of exoskeletons, reduce the stigmatization, and deal with the dilemma of assistance and acceptance of the technology [20]. The control strategy implemented into a gait exoskeleton is a pivotal point in the successful acceptance of a wearable exoskeleton. Specifically, control strategies for gait assistant exoskeletons vary according to the therapy objectives or the patient's mobility disorder. In general, the control architectures of wearable exoskeletons are divided into three hierarchy levels: (1) a supervisory level, (2) an impedance control level, and (3) a position/torque control level [21]. The top level performs a supervisory activity that defines the control objectives. In this part of the control architecture, a finite state machine is commonly used to determine the controller's operation mode. These operation modes could be selected based on technologies that use manual command devices that work as a patient interface to the exoskeleton [22; 23; 24], bio-electrical signals that act as event-triggers with myoelectric signals or brain-computer interfaces [25; 26], or motion and force sensors that identify movement intention [27; 28]. The intermediate control level focuses on impedance control, which is devoted to the interaction between the exoskeleton and the patient. This control level looks to promote the active participation of the patient during therapy in such a way that the exoskeleton assistswith motion as needed [29]. Although the impedance control could result in significant progress in the rehabilitation process, this is a technique not suitable for patients with low muscle strength. In these cases, low-level control takes special importance because it could impose a tracking control policy to follow a predefined trajectory. This activity has a strong influence on driving human motor learning by reinstating neuroplasticity and improving motor functions [30]. In this control level, feedback control strategies are used to guarantee that the exoskeleton performs motion along a predefined trajectory, which is generally adjusted by rehabilitation personnel according to the treatment required for each patient. Alternatively, nominal gaits of healthy people are used as a walking reference pattern. This reference pattern is adapted according to the interacting forces between the patient and exoskeleton to adjust the target trajectory and to adapt the gait pattern to the patient's needs [31]. This is the case of dynamic trajectory adjustments based on impedance control strategies [32]. Exhaustive reviews about control strategies used in assistance exoskeletons were presented in [33; 34; 35], where the use of predefined trajectories based on healthy people's gait was identified as a trend. Considering the loss of muscular strength that DMD patients suffer, this paper proposes a tracking trajectory control strategy with predefined gait pattern, and a supervisory system to define the operation mode. Here, the operation mode selection depends on the contact conditions between the feet and the ground, which must be recognized with external sensors installed to identify the support leg and the motion intention [36]. This research carries out a mechatronic design of an exoskeleton to aid the lower limbs movement of children that have been affected by DMD. The main contribution of this research is the development of a nonlinear control strategy for the hybrid system formed by the exoskeleton and the child's body.