Hysteresis Compensation-Based Intelligent Control for Pneumatic Artificial Muscle-Driven Humanoid Robot Manipulators With Experiments Verification

Zhang, Xinlin; Sun, Ning; Liu, Gendi; Yang, Tong; Fang, Yongchun

doi:10.1109/tase.2023.3263535

Cited by 5 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nonetheless, the CPI model fails to describe the asymmetric hysteresis loops, resulting in sluggish control performance. Some modified Prandtl-Ishlinskii models have been developed and applied to conventional pneumatic muscles [34,35], but rarely used in PSBAs.…”

Section: Introductionmentioning

confidence: 99%

Model-based linear control of nonlinear pneumatic soft bending actuators

Wang,

Xu,

Lai

et al. 2024

Smart Mater. Struct.

View full text Add to dashboard Cite

Advanced model-based control techniques hold great promise for the precise control of pneumatic soft bending actuators (PSBAs) with strong nonlinearities. However, most previous controllers were designed in a cumbersome nonlinear form. Considering the simplicity of linear system theory, this paper presents a novel perspective on using model-based linear control to handle nonlinear PSBAs, and for the first time, summarizes two methodologies, global linearization and pseudo-linear construction. Derived from them, Koopman-based and hysteresis-based linear control approaches are proposed, respectively. For the former, a novel fusion prediction equation is developed to build a high-fidelity Koopman model, realizing global linearization, and then the linear model predictive control (MPC) is deployed. For the latter, the inverse of the generalized Prandtl-Ishlinskii (GPI) model cascades with the PSBA to construct a pseudo-linear system, eliminating the asymmetric hysteresis, which activates the linear proportional–integral–derivative (PID) control. It is worth noting that the above two are based on data-driven models adapted to various PSBAs with material and structural customization. Finally, the two model-based linear control approaches are verified and compared through a series of experiments. The results show that the proposed linear controls, with more concise designs, achieve comparable or even superior performance than nonlinear controls.

show abstract

Section: Introductionmentioning

confidence: 99%

Model-based linear control of nonlinear pneumatic soft bending actuators

Wang,

Xu,

Lai

et al. 2024

Smart Mater. Struct.

View full text Add to dashboard Cite

show abstract

“…Pneumatic muscles are actuators adopted for the fabrication of prosthetic devices, exoskeletons, and, in general, humanoids and robots for different application fields spanning from mechanical industry to physical and rehabilitation medicine [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. In particular, the use of pneumatic muscles for collaborative robotics needs the highest levels of safety and reliability for applications designed to have frequent human–robot interactions.…”

Section: Introductionmentioning

confidence: 99%

A Current-Mode Analog Front-End for Capacitive Length Transducers in Pneumatic Muscle Actuators

Di Patrizio Stanchieri,

De Marcellis,

Faccio

et al. 2024

Micromachines

View full text Add to dashboard Cite

This paper reports on the design, implementation, and characterization of a current-mode analog-front-end circuit for capacitance-to-voltage conversion that can be used in connection with a large variety of sensors and actuators in industrial and rehabilitation medicine applications. The circuit is composed by: (i) an oscillator generating a square wave signal whose frequency and pulse width is a function of the value of input capacitance; (ii) a passive low-pass filter that extracts the DC average component of the square wave signal; (iii) a DC-DC amplifier with variable gain ranging from 1 to 1000. The circuit has been designed in the current-mode approach by employing the second-generation current conveyor circuit, and has been implemented by using commercial discrete components as the basic blocks. The circuit allows for gain and sensitivity tunability, offset compensation and regulation, and the capability to manage various ranges of variations of the input capacitance. For a circuit gain of 1000, the measured circuit sensitivity is equal to 167.34 mV/pF with a resolution in terms of capacitance of 5 fF. The implemented circuit has been employed to measure the variations of the capacitance of a McKibben pneumatic muscle associated with the variations of its length that linearly depend on the circuit output voltage. Under step-to-step conditions of movement of the pneumatic muscle, the overall system sensitivity is equal to 70 mV/mm with a standard deviation error of the muscle length variation of 0.008 mm.

show abstract