Industrial Servo Research Articles

Fixed-Time Adaptive Parameter Estimation for Hammerstein Systems Subject to Dead-Zone

The Hammerstein model has proven its ability for modeling many industrial servo systems, but the corresponding parameter estimation remains as a challenging problem, especially for the purpose of achieving fast convergence. This paper presents a fixed-time (FxT) adaptive parameter estimation scheme for Hammerstein systems with an asymmetric dead-zone to ensure the convergence of estimated parameters in fixed-time. A continuous piecewise linear (CPL) function is adopted to model the nonlinear dead-zone dynamics to remedy the use of intermediate variable. To avoid using the system state information, a K-filter is used to construct a relationship between the unknown system parameters and the input/output signals. Then a new adaptive law based on the parameter error and the FxT scheme is developed to online estimate the lumped unknown parameters and ensure the fixed-time convergence, where an online updated auxiliary variable of regressor is suggested to eliminate the impact of the regressor on the convergence performance. Both numerical simulations and experimental results are given to demonstrate the effectiveness of proposed methods.

Design and analysis of ELM-based predefined time sliding mode adaptive controller for PMLM position control under physical constraints

Achieving accurate position tracking for robotics and industrial servo systems is an extremely challenging task, particularly when dealing with control saturation, parameter perturbation, and external disturbance. To address these challenges, a predefined time convergent sliding mode adaptive controller (PTCSMAC) has been proposed for a permanent magnet linear motor (PMLM). A novel sliding mode surface (SMS) with predefined time convergence PDTC has been constructed, which ensures that the error converges to zero within the prescribed time. The system not only meets the expected performance standards but also has a uniformly bounded motor speed. The trajectory tracking error in SMS is proven to converge to zero within the predefined time. This predefined time stability of the closed-loop system has been demonstrated by using the Lyapunov stability criterion with PDTC. The convergence time (CT) can be arbitrarily set, and the upper bound of it is not affected by the initial value and control parameters of the system. A new updated version of extreme learning machine (ELM) is introduced to approximate the uncertain part of the system based on PDTC. The ELM is also provided with the hyperbolic tangent function to estimate the saturation constraint. This is done by converting the function into a linear function concerning the unconstrained control input variable. Then, based on established stability, a novel sliding mode adaptive controller (PTCSMAC) with predefined time convergence is designed. The convergence time (CT) of the controller is unaffected by the initial conditions as well as the control parameters. The rigorous numerical simulations on the PMLM model with complex disturbances verify the strong robustness and high-precision tracking characteristic of the proposed control law.

Empirical Transfer Function Estimation With Differential Filtering and Its Application to Fine Positioning Control of Galvano Scanner

Fast and precise point-to-point (PTP) positioning control is a critical technology for improving the throughput and product quality of industrial machines. This study aims to investigate the frequency response function (FRF) estimation method with differential filtering (ETFE-Diff: empirical transfer function estimation with differential filtering) that uses the input and output signals of PTP motion during processing operation and to apply ETFE-Diff to a feedforward (FF) compensation adjustment. In this study, the principle of ETFE-Diff for FRF estimation was clarified, compared to the existing FRF estimation methods, i.e., empirical transfer function estimation and local rational modeling. Moreover, the effectiveness of ETFE-Diff for FF compensation adjustment in improving positioning accuracy of a galvano scanner as an industrial servo system was experimentally demonstrated.

Development and Performance Evaluation of Integrated Hybrid Power Module for Three-Phase Servo Motor Applications.

This study aims to develop a 30 kHz/12 kW silicon carbide (SiC)/Si integrated hybrid power module (iHPM) for variable frequency drive applications, particularly industrial servo motor control, and, additionally, to theoretically and experimentally assess its dynamic characteristics and efficiency during operation. This iHPM integrates a brake circuit, a three-phase Si rectifier, and a three-phase SiC inverter within a single package to achieve a minimal current path. A space-vector pulse width modulation (SVPWM) scheme is used to control the inverter power switches. In order to reduce parasitic inductance and power loss, an inductance cancellation design is implemented in the Si rectifier and SiC inverter. The switching transients and their parasitic effects during a three-phase operation are assessed through an electromagnetic-circuit co-simulation model, by which the power loss and efficiency of the iHPM are estimated. The modeled parasitic inductance of the inverter is validated through inductance measurement, and the effectiveness of the simulated results in terms of switching transients and efficiency is verified using the experimental results of the double pulse test and open-loop inverter operation, respectively. In addition, the power loss and efficiency of the SiC MOSFET inverter are experimentally compared against those of a commercial Si IGBT inverter.

Two-Degree-of-Freedom Control of a Micro-Robot Using a Dual-Rate State Observer

This brief presents a novel tracking control algorithm for a micro-robot based on dynamics and positional measurements. The algorithm improves the tracking performance and response time. We designed a two-degree-of-freedom (TDOF) control, which is widely utilized in industrial servo systems, for a micro-robot. Our TDOF control prevents undesirable effects, such as model uncertainty. The dynamic characteristics of a micro-robot were analyzed using the frequency response function (FRF), and a dynamic model specific for micro-robot motion was derived. This brief also addresses the dual-rate problem of micro-robot control systems by designing a dual-rate state observer (DSO) that provides positional information for the micro-robot when no camera updates are available. Thus, the TDOF controller provides feedback control at higher sampling frequencies. The performance of the controller was experimentally verified.

Static sensor assisted rotor temperature estimation of permanent magnet machine for the low‐speed servo applications

AbstractA permanent magnet synchronous machine (PMSM) temperature estimation method fusing the classic lumped‐parameter thermal network (LPTN) and the stator sensor temperature information is investigated. With respect to the industrial servo applications, it is important to monitor the rotor magnet temperature to extend the machine thermal utilisation. A simple LPTN is developed and the quadratic programming is applied to identify the model parameters. The research work shows that the rotor temperature is sensitive to the rotor speed even at low speeds, and this simple estimation network can provide an accurate estimation. The winding sensor information can further improve the performance. A compound mechanism is built, by which the winding temperature estimation error is used as feedback to suppress the model‐based temperature estimation error accumulation. The estimation performance is compared with a regular constant LPTN‐based method. Experimental results based on a PMSM are presented to validate the proposed method.

Practical Tracking of Permanent Magnet Linear Motor Via Logarithmic Sliding Mode Control

This article focuses on the fast position tracking problem for the permanent magnet linear motor (PMLM) system under a chattering-reduced sliding mode control signal. To this end, a class of globally nonsingular sliding mode control (SMC) laws, called logarithmic sliding mode (LnSM) control, is proposed in this article. Using the natural logarithm function, a high gain is established at the equilibrium of the sliding mode reduced-order system, which leads to a higher tracking precision and a faster local convergence rate than those of some classical SMCs. In addition, a super-twisting algorithm-based LnSM (ST-LnSM) control is constructed to reduce the chattering typical for first-order SMC, while stabilizing the position tracking system rapidly. Since only a few parameters need to be adjusted, and the employed natural logarithm function is conventionally integrated into most PMLM drivers, the proposed control law is easy to implement in PMLM systems or other industrial servo systems.

Efficient autonomous feedback controller parameter design considering robust stability for galvanometer scanner

AbstractRobust stable feedback (FB) controller design against plant perturbation is crucial for industrial servo systems. However, since the controller parameter design generally requires expert skills and/or considerable labor by engineers, an autonomous controller design technology would be promising. This paper presents an efficient autonomous design method that optimizes the parameters of a cascade structure FB controller to achieve robust stabilization. Conventionally, robust stabilization is realized by imposing stability constraints on all the perturbed plant model sets in a parameter optimization problem. As a result, the design time would be much longer owing to the complicated optimization problem. The proposed method makes the parameter optimization considering robust stability more efficient than the conventional method, by simplifying the stability constraint definition and optimizing the specified circle radius for the stability constraint based on a bisection method. The effectiveness of the proposed method is evaluated through an example FB controller design for a laboratory galvanometer scanner.

An Intelligent Machine Condition Monitoring Model for Servo Systems

The installation of industrial servo systems and the determination of control parameters are limited to the skills and knowledge of the commissioner. In addition, commissioned systems are often not re-optimized if environmental influences or loads change. The goal of this research is to create an artificial neural network (ANN) model for servo systems that will keep the servo system's proportional, integral, and derivative (PID) parameters working optimally. For this process, a machine condition monitoring algorithm developed with the ANN technique, which uses the data such as actual current, torque, power, position to be obtained from the servo system on an industrial controller, for the control and rearrangement of the parameters.

A large-stroke rapid motion controller for servo applications with speed and control constraints

Large-stroke rapid motion is required in many industrial servo systems (e.g. pick-and-place applications), on which constraints of control input and motion speed are usually imposed. This paper presents a hybrid control scheme for large-stroke rapid motion in such systems. The controller resorts to the time-optimal control (TOC) for maximum acceleration initially and then switches into a linear control law to achieve smooth settling. A speed regulation stage is inserted in the tracking process to prevent violating the speed constraint. To tackle the unmeasured speed and unknown disturbance, an extended state observer (ESO) can be included in the controller. The controller is applied to a permanent magnet synchronous motor (PMSM) servo system for large-stroke position regulation. Digital simulation via MATLAB is conducted first, followed by an experimental verification using a TMS320F28335 board. The results confirm that the proposed controller can track a wide range of target references with desirable performance under speed constraint and load disturbance and has a competitive advantage over the popular active disturbance-rejection control (ADRC) scheme.

Decoupled error dynamics design for discrete-time sliding mode control in industrial servo systems under control input saturation and disturbance

This paper presents a design framework for the discrete-time Sliding mode control with Decoupled disturbance compensator and Auxiliary state (SDA) method in industrial servo applications. In particular, the discrete-time SDA method is formulated to provide an excellent tracking performance even in the presence of control input saturation and disturbance. Moreover, it preserves the separation principle of the sliding mode dynamics and the disturbance estimation error dynamics of the original discrete-time Sliding Mode Control (SMC) with Decoupled Disturbance Compensator (DDC) method. However, it can be problematic due to the unpredictable transients in the error states under control input saturation. This paper investigates the error dynamics of discrete-time SDA after a transition from a saturated region to an unsaturated region, which is called the decoupled error dynamics. The decoupled error dynamics can be designed by shaping a “hidden” sliding manifold which is activated only after the transition. Based on the analysis, a systematical design methodology for the decoupled error dynamics is proposed, which prevents the recurrence of the control input saturation and provides fast convergence of the error states. The effectiveness of the proposed design methodology is shown experimentally using an industrial linear motor system.

Switching position-torque control system for increasing servo PMDC positioning precision in presence of intense external disturbance loading

The overall performance of servo Permanent Magnet DC (PMDC) machines can be gravely undermined when the machine is prone to strong external disturbances and uncertainty in modeling parameters. Additionally, this effect will be compounded if the PMDC machine is expected to track a low-frequency desired trajectory. The main cause of this phenomenon lies in the third-order differential relationship between control voltage and position and this will inevitably result in a slow convergence of the tracking error to zero. On the other hand, the relationship between PMDC torque and control voltage is of first-order which, from a control point of view, can bear the meaning of the presence of the possibility of a faster response for a torque tracking process. In this study, primarily, a discussion is held on the position control algorithms of DC motors that illustrate robustness against external disturbance. The studied controllers have been compared based on their structure (single loop or cascade structures) and consequently, with respect to their shortcomings and advantages, a Discrete-Time Sliding Mode Control (DTSMC)-based tracking control algorithm named as Position-Braking Tracking Control (PBTC) is introduced in which the servo PMDC is controlled in position tracking mode when motoring/reverse motoring property is expected. Similarly, the PMDC is controlled in torque tracking mode when braking/reverse braking property is announced to be required. Activation and the necessity of position or torque tracking is determined by the execution of a simple analysis on the position and torque tracking errors. The proposed DTSMC-based PBTC system is applied to an industrial servo application and the performance improvements are demonstrated. Obtained results indicate that for low-frequency desired position trajectories, transient response of PBTC is more precise relative to single mode DTSMC-based position tracking control.

On the interplay of friction and stress relaxation to improve stretch-flangeability of dual phase (DP600) steel

Industrial servo presses have been used to successfully demonstrate improved formability when deforming sheet metals. While the time dependent viscoplastic behavior of material is attributed to the observed formability improvement, much less effort has been devoted to understand and quantify the underlying mechanisms. In this context, the hole expansion test (HET) of a dual phase steel was interrupted at pre-defined punch travel heights to understand the time-dependent effects on stretch-flangeability. The effect of pre-strain, hold time and edge quality on hole expansion ratio (HER) improvement was studied. The present study shows that the HER improves significantly in interrupted HET. This improved HER is due to the combined effects of stress relaxation and friction on deformation behavior. The ductility improvement estimated from uniaxial stress relaxation tests was used to estimate the contribution of stress relaxation and friction, respectively, in HET. This study shows that friction plays a significant role in improving HER at high pre-strain. It was also demonstrated that frictional effects are largely influenced by edge quality.

Integral Design and Manufacturing Methodology of a Reduced-Scale Servo Press

In a context where industrial production boosts both the society and the economy of a country, improvements in industrial processes are key factors for efficient and reliable development of goods and products. New industrial processes and machines must be evaluated before deployment at large production scales. This article proposes a new optimized design and manufacturing methodology to develop scaled test benches under predefined design requirements and constraints. The main contribution of this article is the integral scaling methodology based on an optimized dimensional analysis and a similitude metric that eases the design of a test bench. Thus, the search for the optimal physical magnitudes of the test bench is accelerated, and the inability to design nonproportional components is solved avoiding distortion. The first step of the methodology is definition of scaling laws through the Buckingham's <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pi$</tex-math></inline-formula> theorem. The second step is to employ a constrained optimization to determine the physical magnitudes of the test bench, based on the scaling laws defined earlier. The third step is to calculate the parameter activities and to set the design tolerances of the scaled components, so that the components are designed more freely while dealing with nonproportional ratios obtained due to arbitrary constraints. The methodology was used to construct a test bench of a servo press that retains the kinematics and dynamics of an industrial servo press. Experimental assessment of the dynamic and kinematic similitudes showed a less than 5% deviation from the industrial servo press's force/angular position ratio.

A Test Procedure Optimization Method for an Industrial Robot Servo System on an Integrated Testing Platform

A test procedure optimization method was proposed in this paper to improve the test efficiency of the industrial robot servo system (IRSS) to be tested on the IRSS integrated testing platform (IITP). First, an ordered sequence was used to define the IRSS test project when tested on the IITP. The ordered sequence consisted of execution subelements, which were a combination of control variable parameters of the IITP. Second, the optimization relationships among the IRSS test projects were dug out according to the IRSS test project sequences. Finally, by using the traveling salesmen problem (TSP), an optimization model was established based on the optimization relationships of the IRSS test projects, and the optimal test order of the IRSS test projects to be tested on the IITP was obtained by solving the model. A case analysis showed that the proposed method optimized the test procedure on the IITP effectively, and the test time when implementing the test on the IITP according to the optimized order was nearly 50% shorter than before optimization. The optimization effect was thus found to be significant.

Deep RL Based Notch Filter Design Method for Complex Industrial Servo Systems

This paper proposes a deep reinforcement learning (deep RL) method for simultaneously designing several notch filters in complex industrial servo systems. Notch filters are highly effective for suppressing resonances in motion control systems and are widely utilized in industry. However, severe limitations exist in complex servo systems because there are many vibration modes that are difficult to identify. In such cases, several notch filters must be used, but the task of tuning these filters involves lengthy empirical procedures by well-experienced engineers. To automate this tuning process, this paper proposes a novel design method that can design several notch filters simultaneously for the first time. In this method, a deep deterministic policy gradient (DDPG) algorithm with a vector stability margin as the reward function is utilized to find filter parameters in the frequency domain. The proposed method simultaneously finds a set of many parameters for several notch filters that are optimal with respect to stability. Using a real industrial servo system that has multiple resonances, it is demonstrated that the proposed method effectively finds the optimal parameters for several notch filters and successfully suppresses multiple resonances to provide desired performances.

Observer-Based Fault Detection With Fuzzy Variable Gains and Its Application to Industrial Servo System

In this paper, an adaptive high-accurate observer-based fault detection approach for industrial applications is proposed. The proposed fault detection algorithm employs a fuzzy logic-based approach with the objective of finding the appropriate observer gains that could cope with the different working conditions. The flexibility and adaptability represent the main objectives of the proposed observer. This work is interested in proposing an observer with fuzzy variable gains for a general nonlinear system. Furthermore, a linear model has been built to facilitate the accomplishment of the fault detection of the industrial servo system by using the proposed observer. In order to evaluate the proposed approach, eleven realistic sensor fault scenarios are created under varying conditions: fault parameters (e.g., multiple fault profiles, location, and magnitudes), unknown inputs (e.g., disturbers and sensor noises) for performance testing. Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. The experimental results demonstrate the effectiveness of the proposed observer approach in detecting sensor faults in the industrial servo systems, with 88.8% classification accuracy. Furthermore, the obtained results confirm the proposed algorithm superiority when compared to classical Luenberger observer with constant gains.

Performance Optimization Methodology for Discrete-Time Sliding Mode Control in Industrial Servo Systems Under Control Input Saturation and Disturbance

Abstract This paper presents a performance optimization methodology for the discrete-time sliding mode control (SMC) with the decoupled disturbance compensator (DDC) and the auxiliary state (AS) for an industrial position control system under control input saturation and disturbance. The discrete-time SMC with DDC and AS (SDA) method prevents windup phenomena in the switching function and the disturbance estimation error. Therefore, it provides robust performance under control input saturation, disturbances, as well as parametric uncertainties. However, it is difficult to relate several design parameters to the desired performance. In this paper, a systematical design framework for the discrete-time SDA method is developed. Based on the phase portrait of the error state, the error can be made to converge to zero with a fast speed and less oscillation under control input saturation by an offline tuning process. An optimization process is performed in terms of the peak value of the control input. Both numerical simulations and experimental results show the effectiveness of the developed tuning methodology for the discrete-time SDA method.

High-precision magnetic encoder module design based on real-time error compensation algorithm

The continuous development of industrial automation requires more and more control precision for automated control systems. As a key component of the servo motor control system, the encoder has a great influence on the accuracy of the control system. Although the common photoelectric encoder has relatively high precision, its control structure is limited by these unfavorable external environments due to its complicated structure, difficulty in integration, and vulnerability to external environments such as dust, oil, water vapor, and vibration. A high-precision magnetic encoder design based on error compensation algorithm proposed in this paper can not only effectively overcomes the influence of these unfavorable conditions, but also introduces an error compensation algorithm based on ordinary magnetic encoder, which can be compared with ordinary magnetic encoder. The encoder has higher position feedback accuracy and greater stability. it can provide position information with real-time error not exceeding 0.2° within general industrial servo motor speed range. The high-precision magnetic encoder module has low cost, simple structure and easy integration, and also has considerable practical value in the field of industrial automation.

Effective Disturbance Compensation Method Under Control Saturation in Discrete-Time Sliding Mode Control

This article presents a novel method of dealing with disturbances and control saturation in the framework of discrete-time sliding mode control (DSMC). A DSMC with decoupled disturbance compensator (DDC) was developed for SMC to recover the loss of stability in the discrete-time domain. However, windup phenomena occur in both the switching function and the disturbance estimate when control saturation occurs, and the method cannot guarantee stability. The article develops a new method for maintaining stability under both disturbances and control saturation by incorporating a novel auxiliary state into the DSMC with DDC method. The auxiliary state prevents the windup phenomena, and the developed new method preserves the asymptotic convergence property of the disturbance estimation error dynamics and the stability of the sliding mode dynamics. Also, the error states are stable under bounded disturbances and control saturation. Simulations and experiments are performed on a commonly used industrial servo system to demonstrate the effectiveness of the proposed method.