Actuator Technologies and Control: Materials, Devices and Applications

1. Motivation and Technical Context

Actuation technologies lie at the heart of modern engineering systems, providing the means by which computational intelligence and control decisions are translated into purposeful physical action. As technological systems increasingly move toward higher levels of autonomy, connectivity, and functional integration, the role of actuators is undergoing a profound transformation. No longer viewed as isolated hardware components, actuators are now integral elements of complex, intelligent systems, required to operate reliably and efficiently while interacting with uncertain environments, humans, and other machines.

This evolution is driven by growing expectations for adaptability, robustness, and performance across diverse application domains, including robotics, transportation, manufacturing, healthcare, and cyber–physical infrastructures. Advances in sensing, control theory, materials, and system integration are converging to enable actuators that can adjust their behavior in real time, compensate for disturbances and uncertainties, and seamlessly cooperate with higher-level decision-making frameworks. As a result, actuation research has become inherently interdisciplinary, bridging traditional boundaries between mechanical design, electronics, control, computation, and application-specific requirements.

A central pillar of this transformation is the development of advanced modeling and control methodologies for smart material and precision actuators. Smart material-based systems, such as piezoelectric, magnetostrictive, and shape memory actuators, offer high bandwidth and compact form factors yet present significant nonlinearities and hysteresis effects that complicate control design. Smith, in [1], highlights the fundamental modeling and control challenges associated with smart material actuation, emphasizing the need for accurate constitutive models and robust compensation strategies. In the domain of micro-scale actuation, Kanchan et al. [2] provide a comprehensive review of piezoelectric micro-actuators, detailing their design principles, dynamic characteristics, and control approaches, which are essential for applications in micro-manipulation and precision engineering.

Precision actuation systems, particularly those employed in high-performance positioning and manufacturing processes, must operate under stringent accuracy requirements despite disturbances and parameter variations. Disturbance observer-based control techniques have emerged as powerful tools for enhancing robustness and disturbance rejection, as discussed by Kim et al. [3]. Such approaches are increasingly complemented by data-driven and learning-based strategies. In [4], Li et al. explore data-driven control methods for intelligent actuator systems, demonstrating how machine learning and real-time data analytics can enhance adaptability and performance in complex and uncertain environments. In particular, this study proposes a data-driven modeling method for nonlinear factors.

As actuators become embedded within networked and cyber–physical systems, resilience and security considerations gain prominence. Network-induced delays, packet losses, and potential cyber threats pose significant challenges to stable and reliable operation. Jiao et al, in [5] address foam-based soft actuators are lightweight and highly compressible, which make them an attractive option for soft robotics In this context, Gorial, in [6], review and discuss smart actuation solutions. In fact, recent advances in series elastic actuator (SEA) research have focused on improving both mechanical design and control strategies to enhance compliance, robustness, and interaction performance in robotic systems. In [7], Sariyildiz et al. proposed a novel variable stiffness SEA that integrates an adjustable stiffness mechanism with a dedicated control framework to achieve improved force and position tracking. The design enables adaptability to varying task requirements and enhances safety in human–robot interaction by allowing modulation of the actuator stiffness.

Beyond mechanical design improvements, several studies have focused on advanced control methods to address the dynamic challenges introduced by actuator elasticity. For instance, [8] introduced a robust elastic structure-preserving control approach aimed at achieving high impedance rendering while maintaining the intrinsic elastic properties of SEAs. By explicitly preserving the actuator’s elastic dynamics, the proposed method improves robustness against disturbances and modeling uncertainties.

Adaptive control techniques have also been investigated to handle parameter variations and resonance phenomena in compliant actuators. In [9], an $\mathcal{L}1$ adaptive resonance ratio control strategy was developed to guarantee fast transient performance while mitigating resonance effects. The controller demonstrates improved tracking accuracy and robustness under uncertain system parameters.

Finally, disturbance rejection remains a critical challenge in SEA systems operating in dynamic environments. To address this, [10] proposed a robust motion control architecture that separates resonance suppression from robustness compensation, improving disturbance rejection while maintaining stable actuator behavior during interaction tasks.

Another major trend concerns safe and compliant interaction between actuators and humans. In collaborative robotics and assistive technologies, actuators must balance performance with safety and adaptability. Variable stiffness actuators (VSAs) have emerged as a promising solution, enabling modulation of mechanical impedance to achieve both precision and safe interaction. Reference [11], by Agostini et al., investigates energy efficiency and dynamic behavior through simulation and experiments of a compact electro-hydrostatic actuator system consisting of an electric motor, external gear pump/motors, hydraulic accumulator, and differential cylinder.

Within this broader and rapidly evolving context, the ten papers, assembled in this Special Issue, present representative and timely contributions that capture the current momentum of the field. The works span advanced control and optimization methodologies, resilient and secure actuation in networked systems, innovative and compliant actuator concepts, precision actuation technologies, and application-oriented sensing and actuation solutions. Together, these contributions not only reflect the state of the art in actuation research, but also point toward future directions in which actuators will play an increasingly central role in enabling intelligent, reliable, and adaptable engineering systems.

2. Contributions of the Special Issue

A major theme of this Special Issue is the development of advanced control and optimization strategies for electric drive systems. In review paper [12], Santos et al. provide a systematic review of smart insole prototypes incorporating artificial intelligence and wireless communication, underscoring the growing role of actuator and sensor technologies in biomechanics and healthcare applications.

In [13], Jiang et al. propose a torque oscillation attenuation method for permanent magnet synchronous motors based on sliding-mode control combined with an equivalent input disturbance approach, enhanced through continuous-domain ant colony optimization. Complementing this contribution, Kethiri et al. address efficiency optimization in BLDC motor drives through adaptive flux control strategies based on incremental conductance and fuzzy logic, demonstrating significant reductions in power losses under varying operating conditions [14].

Robustness and reliability are further explored in the context of cyber–physical systems and industrial robotics. Hassine et al. [15] introduce an event-triggered observer-based control framework that enhances resilience against Markovian cyberattacks, including denial-of-service and false data injection attacks, while reducing communication load. In parallel, Boldsaikhan and Birney present an optimal real-time toolpath planning method for industrial robots equipped with sparse sensing, enabling accurate adaptation to unknown surface variations with limited sensing and computational resources [16].

Accurate modeling and experimental characterization of actuators remain essential for control design and system integration. Abouseda et al. present in [17] an experimental study on a BLDC motor using system identification techniques to capture its dynamic behavior under fixed load torque and variable speed conditions, while also evaluating efficiency and battery state-of-charge effects.

Beyond traditional electric drives, several papers focus on novel actuator concepts and compliant mechanisms. Els et al. investigate the design of fluid elastomeric actuators for soft robotic end-effectors, emphasizing FEM-based optimization and application-specific design guidelines [18]. Xu et al. introduce in [19] a lightweight twisted string actuator with continuously variable transmission that automatically adapts its transmission ratio in response to external loads, demonstrating strong potential for robotic and wearable applications. Razek and Bernard provide a comprehensive review of piezoelectric actuators and sensors, highlighting their high precision and reliability in medical therapeutics, robotic interventions, and structural sensing [20].

The importance of application-driven actuation and sensing systems is illustrated in [21] by Craig and Ahmadian, who present the design and prototyping of a deployable actuation system for railcar-mounted sensors intended for automated railway inspection. In summary, the contributions in this Special Issue highlight the interdisciplinary nature of contemporary actuation research, spanning advanced control, optimization, modeling, emerging actuator technologies, and real-world applications. Together, these works provide valuable insights and directions for the development of efficient, resilient, and intelligent actuation systems.