## Abstract  
In applications where high precision in micro- and nanopositioning is required, piezoelectric actuators (PEA) are an optimal micromechatronic choice. However, the accuracy of these devices is affected by a natural phenomenon called \"hysteresis\" that even increases the instability of the system. This anomaly can be counteracted through a material re-shape or by the design of a control strategy. Through this research, a novel control design has been developed; the structure contemplates an artificial neural network (ANN) feedforward to contract the non-linearities and a robust close-loop compensator to reduce the unmodelled dynamics, uncertainties and perturbations. The proposed scheme was embedded in a dSpace control platform with a Thorlabs PEA, the parameters were tuned online through specific metrics. The outcomes were compared with a conventional proportional-integral-derivative (PID) controller in terms of control signal and tracking performance. The experimental gathered results showed that the advanced proposed strategy had a superior accuracy and chattering reduction. m pacs: 11.45.Hc, 11.  
and or situations; thus, several ways have been suggested to tune these. For instance, the authors of [9] proposed the usage of particle swarm optimisation (PSO) in a simulation with a suitable PEA model. The obtained gains were used in an experimental platform with a commercial PEA where the results showed an improvement in the position accuracy. However, online tuning algorithms for experimental rigs can require a significant amount of computational resources, and certainly, there are other non-linear controllers that manage the compensation with better performance. Sliding mode control (SMC) is a non-linear strategy with a discontinuity that drives the system in a sliding surface [10]. The main advantage is the robustness against uncertainties and external disturbances. The classic SMC has been implemented in PEAs for force control by the authors of [11], where they found suitable outcomes with sine signals as references. A similar approach was carried out in the research of [PERSON] et al. [12], where SMC based with a PID surface was implemented in a commercial PEA where they tested different reference signals, such as the ramp, constants and sine wave. In spite of the improvements of error reduction in the ramp and constant references, the sine wave showed an error of around 5%. However, in the analysed background, it was shown that the main disadvantage of SMC is the chattering that is generated by the discontinuous property. This is an unwanted effect because it increases the energy loss and also the wear in the actuator [13]. Certainly, the chattering can only be reduced and not eliminated because the discontinuity (produced by a sign function) is on of the main features of SMC. Thus, in the recent years, many proposals have been published to trim this effect. For instance, the authors of [14] changed the discontinuity by a hyperbolic function, and in comparison with conventional approaches, the enhancement was acknowledged in the results. Another advance strategy is the usage of high order sliding mode controllers (HOSMC), where high order derivatives are used in the sliding surface, and as a result, the chattering is relieved [15; 16]. An example of implementation has been carried out by the authors of [17], where they used an HOSMC as an observer for error compensation in a PEA test rig. The results showed significant improvements in comparison with other conventional types of SMC strategies in simulation and experiments. Regardless of the enhancement of HOSMC over conventional SMC, the design of sliding controllers establishes that the control law is split into a switching and an equivalent term that are aimed to maintain and compensate the sliding motion [18]. The equivalent is commonly achieved through a mathematical model that describes the system, and this would imply the use of a proper hysteresis description.