In a world demanding increasing precision in motion control systems, irritant noise and vibration detrimentally impacts performance, accuracy/repeatability, and system component longevity across most sectors.

For equipment that relies on precise positioning and smooth operation, mitigating these issues is essential. Examples abound in aerospace, automotive, manufacturing, and robotics, where productivity, precision and lives depend on accuracy.

Noise and vibration cause mechanical wear, degraded sensor readings, and reduced effectiveness in control algorithms. This adds costs and negatively influences application-outcomes. Exploring strategies to identify, manage and reduce noise and vibration in precision motion control helps engineers ensure optimized system performance.

Noise in electromechanical systems comes in many forms and requires complex tools and imaginative solutions, to avoid system disruptions. Source: vitanovski/Adobe Stock

Understanding noise and vibration in motion control systems

Noise and vibration in motion control systems stem from a spectrum of interrelated and interacting sources. These include interplay between mechanical components, electrical disturbances, operational disturbances and environmental factors. In such systems, noise typically refers to any unwanted or extraneous electrical disturbances adversely influencing sensors or control signals, while vibration involves cyclic physical oscillations or mechanical jerks that can reduce positioning accuracy and cause component, bearing, or drive-train wear.

These disturbances can trigger several disruptive issues/consequences:

● Reduced accuracy: Vibrations commonly cause slight shifts/disturbances in component positions, even when firmly located, leading to positioning errors.

● Degraded component life: Continuous vibrations put stress on components, reducing their operational lifespan.

● Degraded outcomes at effectors: Vibration in cutters often results in chatter, where the cutter oscillations appear in material form as discontinuous and regular surface patterns. Similar disturbances in a laser cutter or welder can create poor quality cuts or bead paths

● Unstable feedback loops: Noise in sensor outputs, comms lines or control signals can disrupt fine adjustments in motion control positioning, exacerbating overshoot, instability or triggering excessive corrective actions that worsen performance.

● Operator safety and comfort: In applications like medical devices or factory automation, excessive noise and vibration can disrupt workflows, create user/operator/patient discomfort, and compromise safety.

To tackle these challenges, engineers and developers must understand the origins of noise and vibration, assess their impacts on system performance, and implement appropriate mitigation techniques to banish them or minimize their influence.

Sources of noise and vibration in precision motion control

There are several well defined potential sources of noise and vibration in motion control systems, falling into three categories: mechanical, electrical, and environmental.

Mechanical sources

Motion and drive components — motors, gears, belts, rails and bearings all introduce significant vibration. As these parts move and interact, they generate forces that, by their nature, create oscillations throughout the system.

● Motors: Servo and stepper motors, providing motive force in control/positioning applications, generate vibrations due to magnetic interactions, torque ripple, misalignment, eccentricity and mechanical imbalance. Each source can add to the total, and ringing between sources can complicate the harmonic range and obstruct analysis.

● Gears and bearings: Wear in gears and play between meshing components, can produce hysteresis and catch-up clunk or cyclic noise. Worn-out or improperly lubricated bearings also introduce vibrations, typically of higher primary frequency.

● Structural flexibility: Motion systems often have flexible components such as 'soft' drive couplings and vibration isolating supports that can deform under load. These deformations may lead to resonant vibrations, making the machine 'ring' when the device excitation frequency is close to a harmonic systems natural frequency.

Electrical sources

In electronic components, electromagnetic interference (EMI), magnetic interference and internal electrical noise can affect sensors, control circuits, and motor drivers, influencing system stability or accuracy in both subtle/transient and cyclic ways.

PWM (Pulse Width Modulation) noise: PWM drives control motor speed and torque, but the switching frequencies and poor shielding can create electrical noise that affects nearby sensors and control electronics.

EMI and RFI (Radio Frequency Interference): High-speed switching in power electronics generates electromagnetic fields that can interfere with sensitive components, resulting in signal distortion and stray 'data' that can be hard to source/control.

Environmental factors

External factors such as temperature fluctuations, floor vibrations, and ambient noise can also impact motion control systems, particularly in environments where multiple and complex sources can be overlayed.

● Ambient vibrations: External vibrations, such as those from nearby equipment, can travel through building structures and interfere with precision systems. The isolation of these from a system can itself create unintended consequences in terms of system vibrations.

● Temperature changes: Temperature variations lead to material expansion or contraction, affecting component alignment and causing thermal drift in sensors.

Strategies for reducing noise and vibration in precision motion control

Militating against noise and vibration causes/influences in motion control systems requires a balance of design strategies, component selection, and control techniques.

Structural design and material selection

The physical structure and materials used in a motion control system can have a profound impact on the internal ability to dampen and negate vibrations.

● Rigid design: Using stiffer structural materials, and more resilient and more self isolating design helps reduce the flexibility in structures that enables unwanted oscillations.

● Damping materials: Interconnecting using damping materials between at-risk components can absorb vibrational energy. Materials like rubber, foam, or viscoelastic compounds can dissipate vibrations, especially at critical points in the structure, while increasing the risk of adding overall flexibility at other excitation frequency ranges.

● Isolated mounting: Mounting precision equipment on vibration-isolated platforms reduces transmission of external environmental vibrations, but elevates the risk of complex system ringing and whole-machine displacement in response to high mass and high acceleration motions.

Advanced motor control techniques

Optimizing motor control algorithms and settings that minimize noise and vibration from motor-driven movements can be effective, often at the cost of speed/acceleration capability.

● Sinusoidal commutation: Sinusoidal commutation for brushless motors smoothens torque generation compared to traditional trapezoidal commutation, reducing torque ripple and vibrations.

● Closed-loop control: Closed-loop control systems integrate feedback that enables precise adjustments to motor commands, improving stability and reducing oscillations. PID controllers that can be tuned to minimize vibrations, sacrificing speed in favor of precision.

● Microstepping in stepper motors: Microstepping in stepper motor control allows for smoother motion and reduced vibrations by dividing each step into smaller increments. This raises the excitation frequency of the motor drive, which can take it out of range for the natural frequency of the local structure and components.

Sensor selection and placement

Noise and vibration adversely affect sensor readings, leading to feedback errors being introduced into control algorithms. Choosing the right sensors and positioning them optimally can mitigate these issues.

● High-resolution encoders: Using higher-resolution encoders will capture finer details of position changes, allowing for more accurate adjustments that counteract noise-induced deviations. This elevates the frequency of sensitivity of the encoder, moving it away from the at-risk excitation frequencies of typical mechanical systems.

● Accelerometers: Accelerometers detect and measure vibrations within the system. This data can be used in feedback loops to adjust motor commands dynamically, reducing the effects of vibrations. It can also be used as an analysis tool I diagnosing and correcting issues.

● Sensor placement: Positioning sensors in vibration-free areas of the system, or stiffening the areas where sensors must be placed, can reduce noise in feedback signals.

Filtering and signal processing

Noise in sensor signals and control inputs can be reduced through filtering techniques and improved signal processing, enhancing overall system performance/robustness without need for mechanical/structural alterations.

● Low-pass filters: Low-pass filters allow low-frequency signals to pass while blocking higher-frequency noise. They are particularly useful in removing electrical noise from sensor readings.

● Notch filters: For systems experiencing resonance at specific frequencies, notch filters can remove noise at those frequencies, reducing amplification of narrow-band resonant vibrations.

● Kalman filters: Kalman filters predict the most likely signal from noisy measurements, making them useful in high-precision applications where transient and hard to trace noise can obscure important data.

Thermal management

Thermal variations lead to material expansion or contraction, which often negatively influences system alignments and may introduce mechanical drift or variable noise sources. Effective thermal management can mitigate these issues.

● Active cooling systems: Incorporating fans, heat sinks, or liquid cooling systems helps regulate temperatures.

● Temperature compensation: Using sensors to monitor temperature changes enables the system to adjust control parameters dynamically, accounting for thermal expansion or contraction. This can be effective in ML based algorithm adjustments and in AI managed/tuned systems.

Implementing advanced control algorithms

Control algorithms are essential tools in managing vibrations and noise, mitigating their consequences in motion control systems. Beyond simple PID control, advanced algorithms are employed to optimize system performance.

● Adaptive control: Adaptive control algorithms adjust system parameters on-the-fly in real-time, improving responsiveness to unexpected disturbances and widely variable loading scenarios.

● Feedforward control: Feedforward control anticipates system disturbances and proactively adjusts motor commands, reducing reaction lag and enhancing dynamic stability.

● Model predictive control (MPC): MPC uses ML/AI predictive models to forecast system behavior, enabling preemptive system adjustments that actively manage oscillation risks, for smoother operation.

Testing and validation

Optimizing noise and vibration in vulnerable motion systems requires a comprehensive testing and validation process to assess effectiveness, adjust strategies and deliver long-term stability.

● Frequency response analysis: This testing identifies resonance frequencies in the system, allowing engineers to negate the excitation of these frequency vulnerabilities with localized damping or control strategies.

● Vibration analysis: Conducting vibration analysis during the design and validation phases helps detect potential issues early and refine solutions before full deployment. This strategy targets sources, complimenting frequency response analysis

● Environmental testing: Testing systems in real-world environments ensures that potential noise and vibration sources are identified and accounted for.

Future trends in noise and vibration management

As motion control continues to develop and evolve, new tools and techniques are required to handle new sources and sensitivities to noise and vibration.

● ML and AI: Machine learning algorithms can analyze sensor data to predict and mitigate noise and vibration issues, helping systems adapt to changing conditions. AI controls can rapidly compensate fir issues as they arise, without supervisory input delay.

● Smart materials: Materials with adaptive properties, such as shape-memory alloys, can reduce vibrations in real-time by altering their characteristics in response to environmental changes. This can allow intrinsic and seamless adjustment in system natural-frequencies to be hands-free.

● Integrated sensors and actuators: Combining sensors and actuators within a single component allows for more direct control, reducing potential sources of noise and improving response times by banishing additional lag-risk.

Conclusion: The path to optimal precision motion control

Mitigating noise and vibration is performance-critical in high-precision motion control systems. Without effective strategies, it's impossible to ensure accuracy, stability, and functional reliability.

By understanding the sources of disturbances and implementing targeted solutions — from advanced materials and structural designs to optimized motor control and filtering techniques — engineers can deliver motion control that performs optimally under challenging conditions.

As industries increasingly rely on precision in fine detail and high value operations and life-dependent functions, these strategies are becoming more essential, driving innovation in robotics, vehicles and manufacturing.

Embracing these varied techniques, along with new materials, edge computing, and artificial intelligence and machine learning help pave the way to quieter, more efficient, and more resilient motion control systems.