Search Results (4)

Pneumatic artificial muscle (PAM) is attractive in rehabilitation and biomimetic robots due to its flexibility. However, there exists a strong hysteretic nonlinearity in PAMs and strong coupling between the output displacement and the output force. At present, most commonly used hysteresis models can be treated as two-dimensional models, which only consider the nonlinearity between the input and the output displacement of the PAM without considering the coupling of the output force. As a result, high-precision modeling and estimation of the PAM’s behavior is difficult, especially when the external load of the system varies significantly. In this paper, the influence of the output force on the displacement is experimentally investigated. A three-dimensional model based on the modified Prandtl–Ishlinskii (MPI) model and the Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX) model is proposed to describe the relationship and couplings among the input, the output displacement, and the output force of the PAM. Experiments are conducted to verify the modeling accuracy of the proposed model when the external load of the PAM varies across a wide range. The experimental results show that the proposed model captures well the hysteresis and couplings of the PAM and can precisely predict the PAM’s behavior. Full article

Self-sensing techniques are a commonly used approach for electromagnetic actuators since they allow the removal of position sensors. Thus, costs, space requirements, and system complexity of actuation systems can be reduced. A widely used parameter for self-sensing is the position-dependent incremental inductance. Nevertheless, this parameter is strongly affected by electromagnetic hysteresis, which reduces the performance of self-sensing. This work focuses on the design of a hysteresis-compensated self-sensing algorithm with low computational effort. In particular, the Integrator-Based Direct Inductance Measurement (IDIM) technique is used for the resource-efficient estimation of the incremental inductance. Since the incremental inductance exhibits a hysteresis with butterfly characteristics, it first needs to be transformed into a B-H curve-like hysteresis. Then, a modified Prandtl–Ishlinskii (MPI) approach is used for modeling this hysteretic behavior. By using a lumped magnetic circuit model, the hysteresis of the iron core can be separated from the air gap, thus allowing a hysteresis-compensated estimation of the position. Experimental studies performed on an industrial switching actuator show a significant decrease in the estimation error when the hysteresis model is considered. The chosen MPI model has a low model order and therefore allows a computationally lightweight implementation. Therefore, it is proven that the presented approach increases the accuracy of self-sensing on electromagnetic actuators with remarkable hysteresis while offering low computational effort which is an important aspect for the implementation of the technique in cost-critical applications. Full article

Piezoelectric actuators are widely used in micromanipulation and miniature robots due to their rapid response and high repeatability. The piezoelectric actuators often have undesired hysteresis. The Prandtl–Ishlinskii (PI) hysteresis model is one of the most popular models for modeling and compensating the hysteresis behaviour. This paper presents an alternative digitized representation of the modified Prandtl–Ishlinskii with the dead-zone operators (MPI) hysteresis model to describe the asymmetric hysteresis behavior of piezoelectric actuators. Using a binary number with n digits to represent the classical Prandtl–Ishlinskii hysteresis model with n elementary operators, the inverse model can be easily constructed. A similar representation of the dead-zone operators is also described. With the proposed digitized representation, the model is more intuitive and the inversion calculation is avoided. An experiment with a piezoelectric stacked linear actuator is conducted to validate the proposed digitized MPI hysteresis model and it is shown that it has almost the same performance as compared to the classical representation. Full article

Dielectric electro-active polymer (DEAP) materials, also called artificial muscle, are a kind of EAP smart materials with extraordinary strains up to 30% at a high driving voltage. However, the asymmetric rate-dependent hysteresis is a barrier for trajectory tracking control of DEAP actuators. To overcome the barrier, in this paper, a Hammerstein model is established for the asymmetric rate-dependent hysteresis of a DEAP actuator first, in which a modified Prandtl-Ishlinskii (MPI) model is used to represent the static hysteresis nonlinear part, and an autoregressive with exogenous inputs (ARX) model is used to represent the linear dynamic part. Applying Levenberg-Marquardt (LM) algorithm identifies the parameters of the Hammerstein model. Then, based on the MPI model, an inverse hysteresis compensator is obtained to compensate the hysteresis behavior. Finally, a compound controller consisting of the hysteresis compensator and a novel discrete-time terminal sliding mode controller (DTSMC) without state observer is proposed to achieve the high-precision trajectory tracking control. Stability analysis of the closed-loop system is verified by using Lyapunov stability theorem. Experimental results based on a DEAP actuator show that the proposed controller has better tracking control performance compared with a conventional discrete-time sliding mode controller (DSMC). Full article