HOW INTELLIGENT CONTROLS IMPROVE ACTUATOR PRECISION, REPEATABILITY, AND EFFICIENCY

As automation advances across industrial and mobile applications, growing demands for precision, flexibility, efficiency, and long-term reliability are driving more advanced actuator control capabilities. Modern smart machines are expected to execute complex motion and force profiles, adapt to varying process conditions, and deliver consistent results cycle after cycle.

 At the center of this shift are intelligent control features that tightly coordinate the interaction between the actuator, motor, drive, and overall machine control system. Whether deployed as part of a fully integrated system or paired with existing control platforms, advanced actuator controls enable higher levels of performance, programmability, and repeatability, forming the foundation for smarter, future-ready machine design.

CORE CONTROL CAPABILITIES THAT DRIVE PERFORMANCE

Advanced control systems enable a range of capabilities that directly influence machine performance, including:

• Position control for accurate, repeatable motion
• Controlled speed and motion profiles to support consistent cycle timing and smooth operation
• Force control for applications requiring consistent and repeatable load application
• Closed-loop feedback to maintain accuracy and performance over time

Together, these control capabilities form the foundation for more advanced functions, such as synchronized, multi-axis actuation in modern automated systems.

SYNCHRONIZATION IN MODERN ACTUATION SYSTEMS

As automation and robotics continue to advance, control requirements increasingly extend beyond individual actuators. Many modern machines rely on multiple actuators working together, often across a wide range of sizes, forces, and motion profiles.

In applications such as pressing and testing, precise control of both position and force is critical, not only at a single axis, but across multiple axes operating simultaneously. Synchronized actuation occurs when multiple actuators follow a defined reference, such as a primary axis (master) or a virtual axis (slave), remaining digitally locked through encoder feedback and drive-level programming. This approach is commonly referred to as electronic line shafting (ELS) or gearing.

From a controls perspective, synchronization enables:

• Coordinated position and force control across multiple actuators
• Precise timing and alignment throughout a machine cycle
• Repeatable performance in complex, multi-axis processes

SYNCHRONIZATION PERFORMANCE ACROSS ACTUATION TECHNOLOGIES

While synchronized motion is increasingly expected in automated systems, it is not equally achievable across all actuation technologies. Synchronizing actuation in pneumatic or hydraulic systems can be challenging and costly, often requiring additional hardware, complex valving, or extensive tuning to maintain alignment over time.

Electric actuators, both mechanical and hybrid designs, are inherently well suited for synchronized operation. Because motion and feedback are controlled electrically, multiple actuators can be coordinated accurately through the control system itself.

Sequencing and Synchronization in Real-World Applications

In many applications, synchronized actuation plays a critical role in achieving product quality and process consistency. Applications such as pressing, forming, and large-scale material processing often require multiple actuators to apply force and motion in a coordinated manner.

DATA-DRIVEN DIAGNOSTICS AND PREDICTIVE MAINTENANCE

Modern actuation control systems also provide valuable insight into the actuator and machine performance through data capture and diagnostics. By monitoring key operating parameters and signature analysis over time, engineers can:

• Implement cycle-level pass/fail detection using pre-programmed performance limits to ensure each operation meets defined force, position, and timing criteria
• Identify performance trends that indicate gradual wear, drift, or loss of efficiency before failures occur
• Enable predictive maintenance by defining acceptable thresholds for force, position accuracy, cycle time, and motion signatures, addressing inefficiencies proactively rather than reactively, minimizing downtime
• Leverage motion and force signature analysis for faster troubleshooting, using captured traces to pinpoint issues such as mechanical binding or misalignment
• Improve product quality and process consistency by detecting anomalies early before they impact process consistency or uptime

This data-driven shift from reactive maintenance to proactive system monitoring reduces unplanned downtime, improves system reliability, and extends overall equipment life.

CONTROL FEATURES DESIGNED FOR FUTURE-READY SMART MACHINES

Advanced control capabilities play a central role in modern automation systems. By combining precise position and force control, synchronized multi-axis operation, and actionable performance data, engineers can design automation systems that deliver consistent results and predictable performance over time.

This comprehensive approach to controls is central to hybrid linear actuator technology. By combining the power and robustness of hydraulics with the precision and controllability of electric actuation, hybrid linear actuators support modern machine architectures that require tight coordination between motion and force, simplified system design through reduced external hydraulic infrastructure, and predictable, repeatable performance, capabilities that enable smarter, future-ready machine operation.

These control features are available through a Total Solution Hybrid Actuation System – a fully integrated and factory tested actuation package, including the actuator, attached power unit, motor, drive/controller, software, cables, and supporting documentation. Hybrid linear actuators can also be paired with a customer’s preferred motor and drive, allowing machine builders flexibility to use the features of those control platforms to achieve intelligent position and force control, sequencing, synchronization, and data-driven diagnostics.