Energy-Aware Performance Evaluation of Nonlinear Mechatronic Systems Under Matched

Electrical Engineering and Systems Science > Systems and Control
[Submitted on 8 Jul 2026]
Title:Energy-Aware Performance Evaluation of Nonlinear Mechatronic Systems Under Matched-Tracking Conditions
View PDF HTML (experimental)Abstract:Trajectory-tracking metrics such as root-mean-square error (RMSE), overshoot, and settling time are widely used to evaluate control performance in mechatronic systems. However, these measures describe output tracking alone and do not account for the actuator effort required to produce the observed motion. This limitation becomes more pronounced in nonlinear systems, where stiffness and dissipation depend on the system state. This paper examines how these effects influence actuator energy under similar tracking conditions. An energy-aware evaluation framework is introduced that combines tracking error with cumulative actuator energy and enables comparison between systems with approximately matched performance. A simple index (EAPI) is used to capture both aspects in a single measure. Simulation results for linear and nonlinear systems under proportional-derivative control show that comparable tracking accuracy can correspond to significantly different actuator energy. The nonlinear system consistently requires more energy across matched operating points, reflecting the influence of nonlinear stiffness and friction. These results suggest that trajectory-based metrics alone may not fully capture differences in system effort, and that including energy provides a more informative basis for performance evaluation.
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Facts Only

* Trajectory-tracking metrics used include root-mean-square error (RMSE), overshoot, and settling time for control performance evaluation in mechatronic systems.
* These metrics evaluate output tracking but do not account for actuator effort.
* Limitations in these measures are more pronounced in nonlinear systems where stiffness and dissipation depend on the system state.
* An energy-aware evaluation framework is introduced combining tracking error with cumulative actuator energy.
* A simple index, Energy-Aware Performance Index (EAPI), is used to capture both aspects in a single measure.
* Simulation results for linear and nonlinear systems under proportional-derivative control showed comparable tracking accuracy corresponding to different actuator energies.
* The nonlinear system consistently required more energy across matched operating points compared to linear systems.
* This difference reflects the influence of nonlinear stiffness and friction.

Executive Summary

Trajectory-tracking metrics like root-mean-square error (RMSE), overshoot, and settling time are commonly used to assess control performance in mechatronic systems by evaluating output tracking. However, these metrics only measure motion accuracy and fail to account for the energy expended by the actuators to achieve that motion. This limitation is amplified in nonlinear systems where stiffness and dissipation vary with system state. The research introduces an energy-aware evaluation framework that integrates tracking error with cumulative actuator energy to enable comparisons between systems with similar tracking performance. A single index, Energy-Aware Performance Index (EAPI), is proposed to combine these factors. Simulation results demonstrate that linear and nonlinear systems can exhibit comparable tracking accuracy while requiring significantly different amounts of actuator energy. Specifically, the nonlinear system consistently demands more energy across matched operating points due to the influence of nonlinear stiffness and friction. The findings suggest that performance evaluation must incorporate energy consumption alongside trajectory metrics for a complete assessment of system effort.

Full Take

The research pivots the standard evaluation paradigm from purely kinematic performance (tracking) to dynamic performance (energy). The core implication is that in complex, real-world systems, what looks identical on an output plot can hide vastly different underlying physical costs. Trajectory metrics alone create a form of deceptive equivalence; they allow engineers to treat a system that requires high energy as equally 'good' if it meets the same positional goal as a low-energy alternative, ignoring the intrinsic difficulty or efficiency of the control action itself. The introduction of EAPI suggests a necessary shift toward holistic assessment where physical effort is not an afterthought but an integral component of performance. This challenges the heuristic reliance on easily calculated metrics by demanding the inclusion of state-dependent physical constraints (stiffness and friction) in performance comparison. The pattern observed—that nonlinearities systematically increase energy demand without changing tracking quality at matched points—suggests that simplifying assumptions about linearity introduce significant potential for misallocation of resources and overlooking system complexity, which is a critical failure mode in control engineering when systems are not perfectly linearized or modeled.

Sentinel — Human

Confidence

The text presents a focused technical argument within an academic context, exhibiting the characteristic structure and depth of peer-reviewed scientific writing.

Signals Detected

Moderate sentence length variance; academic tone is consistent but avoids robotic uniformity.

Clear logical progression from problem statement (tracking metrics insufficient) to solution (energy-aware framework), demonstrating focused argumentation.

Standard academic structure; no readily apparent verbatim replication or vague attribution.

Content appears to be a standard, well-structured academic abstract/summary of research findings.

Human Indicators

Use of specialized, nuanced terminology (nonlinear mechatronic systems, actuator effort, nonlinear stiffness) integrated into a specific scientific argument.

The conceptual leap from standard metrics to energy-aware evaluation shows domain-specific insight rather than generic synthesis.