Pneumatic Actuation and Control System Techniques

Pneumatic actuation harnesses compressed air to generate mechanical force and motion with inherent compliance, high power density and rapid response. Traditional pneumatic cylinders remain ubiquitous in industrial automation for tasks demanding simple linear motion, while pneumatic artificial muscles (PAMs) emulate biological muscle behaviour, offering lightweight, soft actuation for rehabilitation robotics and wearable devices. Recent advances focus on overcoming intrinsic challenges such as air compressibility, nonlinear dynamics, hysteresis and time delays. Control strategies have evolved from classical proportional–integral–derivative (PID) schemes towards more sophisticated approaches including sliding-mode control, model predictive control (MPC), adaptive and fuzzy algorithms, and hybrid pneumatic-electric designs. These methods seek to improve precision, robustness and energy efficiency by compensating for uncertainties, reducing overshoot, minimising chattering and predicting future system behaviour. Integration of optimisation techniques and machine-learning based parameter tuning further refines dynamic performance. Globally significant applications span automated manufacturing, haptic teleoperation, prosthetic limbs, lower-limb rehabilitation and high-speed humanoid manipulators. Ongoing research interconnects actuator modelling, valve technology and control theory to deliver versatile, safe and cost-effective pneumatic systems for next-generation automation and assistive devices.

Research from Nature Portfolio

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Research from all publishers

An improved PID method combining a back-propagation neural network and a Smith predictor has been applied to a compliant constant-force cylinder actuator. By repeatedly adjusting the neural network weights to model pneumatic nonlinearity and using the Smith predictor to compensate for time delays, the controller achieves reduced overshoot and faster settling under variable loads, demonstrating markedly enhanced force stability compared with a conventional PID scheme.

A trajectory tracking strategy for a lower-limb rehabilitative parallel mechanism integrates feedforward/feedback control with length-pressure hysteresis compensation of PAMs. The approach derives inverse kinematics from human gait data and employs a two-stage control law that anticipates hysteresis in the air-muscle interface. Experimental results show tighter path following and improved transparency, indicating strong potential for assistive walking devices.

A discrete-valued model predictive control algorithm (DVMPC2) for double-acting pneumatic cylinders using only on/off valves employs a flexible cost function and refined prediction to directly switch valves when needed. Compared with sliding-mode control, this method reduces time-weighted error by over 80 %, lowers overshoot by 43 % and decreases valve switching rate, thereby extending valve life while maintaining high positioning accuracy.

Pneumatic Actuation and Control System Techniques publication trend

The graph below shows the total number of articles in pneumatic actuation and control system techniques across all publications each year (not limited to Nature Index journals).

Technical terms

Pneumatic artificial muscle (PAM): A soft actuator that contracts under pressure, mimicking biological muscle behaviour.

Hysteresis: A lagging of output response behind input changes, causing path-dependent behaviour in actuators.

Smith predictor: A control structure that compensates for known time delays by predicting future plant outputs.

Model predictive control (MPC): An optimisation-based method that uses a dynamic model to forecast and optimise control moves over a future horizon.

On-off valve: A binary pneumatic valve that alternates between fully open and fully closed states to regulate airflow.

References

1. An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor. Applied Sciences (2021).
2. A Trajectory Tracking Control of a Robot Actuated With Pneumatic Artificial Muscles Based on Hysteresis Compensation. IEEE Access (2020).
3. Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control. Actuators (2019).