Recently, pneumatic artificial muscles (PAMs), a lightweight and high-compliant actuator, have been increasingly used in assistive rehabilitation robots. PAM-based applications must overcome two inherent drawbacks. The first is the nonlinearity due to the compressibility of the air, and the second is the hysteresis due to its geometric construction. Because of these drawbacks, it is difficult to construct not only an accurate mathematical model but also a high-performance control scheme. In this paper, the discrete-time fractional order integral sliding mode control approach is investigated to deal with the drawbacks of PAMs. First, a discrete-time second order plus dead time mathematical model is chosen to approximate the characteristics of PAMs in the antagonistic configuration. Then, the fractional order integral sliding mode control approach is employed together with a disturbance observer to improve the trajectory tracking performance. The effectiveness of the proposed control method is verified in multi-scenario experiments using a physical actuator.
Along with the development of powerful microprocessors and microcontrollers, the applications of the model predictive controller, which requires high computational cost, to fast dynamical systems such as power converters and electric drives have become a tendency recently. In this paper, two solutions are offered to quickly develop the finite set predictive current control for induction motor fed by 3-level H-Bridge cascaded inverter. First, the field programmable gate array (FPGA) with capability of parallel computation is employed to minimize the computational time. Second, the hardware in the loop (HIL) co-simulation is used to quickly verify the developed control algorithm without burden of time on hardware design since the motor and the power switches are emulated on a real-time platform with high-fidelity mathematical models. The implementation procedure and HIL co-simulation results of the developed control algorithm shows the effectiveness of the proposed solution.
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