Linear Motor Servo Research Articles

Modified complementary sliding mode control with disturbance compensation for permanent magnet linear synchronous motor servo system

In this study, a modified complementary sliding mode control (MCSMC) method based on a disturbance force observer with mass identification (DFOB-MI) applicable to the permanent magnet linear synchronous motor is proposed to achieve high-performance servo control fields. MCSMC is an improvement on the complementary sliding mode control (CSMC) method, which incorporates an approach angle into the saturation function. MCSMC allows for asymptotic convergence of the position tracking errors and guarantees the global robustness of the system. In addition, compared to hybrid control strategies combining neural networks with CSMC, the MCSMC method has a simpler structure and faster response. However, in practical applications, the mass variation of the mover has a significant impact on system performance. To achieve better dynamic and static characteristics, a disturbance force observer capable of identifying the mass variation based on model reference adaptive identification theory is proposed. DFOB-MI can identify the mass of the mover and provide information on the disturbance caused by the change of the load. Thus, the compensation current is calculated to reduce the disturbance and realise compensation. The more accurate tracking performance and stronger robustness of the proposed control scheme compared to conventional approaches have been confirmed through comparative experimental studies.

Intelligent second‐order sliding mode control for permanent magnet linear synchronous motor servo systems with robust compensator

In this study, an intelligent second-order sliding mode control (SMC) method combining second-order SMC (SOSMC) and recurrent radial basis function neural network (RRBFNN) applicable to the permanent magnet linear synchronous motor (PMLSM) is proposed to achieve high-performance servo control fields. On the basis of a dynamic model of PMLSM and the SMC theory, the chattering problem in SMC is weakened and the tracking accuracy is improved by the design of SOSMC. As for the boundary of the uncertainty factors is difficult to obtain, the optimal performance of SOSMC is hard to achieve, the RRBFNN uncertainty observer is introduced for estimating the value of the uncertainty factors. Owing to the strong learning ability, the network parameters can be trained online. Besides, a robust compensator is developed to suppress the uncertainties such as approximation error, optimal parameter vector and higher Taylor series for further improving the robustness. Moreover, the adaptive learning algorithms are obtained by using the Lyapunov theorem to guarantee the asymptotical stability of the system. The experiments demonstrate that the proposed scheme provides high performance dynamic characteristics and strong robustness to uncertainties.

Active disturbance rejection position servo control of PMSLM based on reduced-order extended state observer

To enhance the control accuracy of permanent magnet synchronous linear motor (PMSLM) servo systems affected by disturbances, such as time-varying parameters and abrupt load changes, an active disturbance rejection control (ADRC) algorithm based on a reduced-order extended state observer (ESO) is adopted to suppress the disturbances on the control system. First, the system's ability to estimate disturbances is enhanced by linearizing the ESO. Second, the pole placement method is used for the construction of a reduced-order ESO that can reduce the influence of the number of adjustment parameters and the phase lag. The parameters of the reduced-order ADRC are adjusted, the optimal control parameters are selected, and the stability of controller is proved. Finally, practical experiments prove that the proposed method can improve control accuracy under multiple working conditions and features strong anti-interference ability. There is a smaller steady-state error, and no overshoot is observed.

Model Predictive Control-Based Smart Linear Servo-Motor Driver for a Resonance Frequency Tuner of Azimuth Variable Field Cyclotrons

The most important thing in the startup procedure or the long-term operation of radio frequency (RF) cyclotrons especially azimuth variable field (AVF) cyclotrons, is the resonance frequency stability of the cavities. Generally, servo-motors or stepper motors are used to adjust the tuners of cavities. Actually, proportional-integral-derivative (PID) controller-based servo-motor drivers have many problems for long-term operation, such as the tuner’s temperature dependence, shot noise, and so on. Our model predictive controller (MPC) or MPC-based smart linear servo-motor driver in a multi-input and single-output state, with artificial intelligence (AI), can solve usual and unusual problems in order to control the speed and/or position. In other words, the MPC is a progressive strategy of process control to control the process and provides satisfaction limitations. Additionally, this real-time controller can reduces the time needed for the startup procedure and minimizes the number of failures during long-term operation.

A Novel Tension Control System of Square Lithium Battery Laminated Machine

Background: To the problem that the traditional square laminated machine with passive unwinding control strategy makes the tape speed periodical changing in reciprocating motion and not achieve a good tension control, a novel unwinding system and control algorithm are presented to improve the efficiency and quality of such equipment. Methods: Compared with the traditional passive unwinding control system, the novel tension control system adds an active compliance mechanism. After obtaining the motion relationship between the compliance device and the laminated motion platform through building the complex system mathematical model, the laminated machine tension control is equivalent to a spatial trajectory tracking control, and multi-axis synchronous coordinated control algorithm is used to control their relative motions, and a cross-coupling control in multi-axis coordinated motion is presented to decrease the synchronous error of the two linear servo motors, which are the compliance device driving motor and the laminated motion platform driving one. Without tension sensor, however, good tension control is obtained only by position tracking control. Results: Based on the proposed approaches and novel unwinding mechanism, the tension control was examined on an experimental square lithium battery laminated machine and results of the experiments performed with the experimental setup demonstrated the effectiveness of the proposed approach. Conclusion: Without a tension sensor, good tension control is obtained only by position tracking control in the novel unwinding system, and the production quality and efficiency of the lithium battery laminated machine are improved.

Nonlinear Robust Optimal Control via Adaptive Dynamic Programming of Permanent-Magnet Linear Synchronous Motor Drive for Uncertain Two-Axis Motion Control System

In this article, a nonlinear robust optimal control (NROC) scheme for uncertain two-axis motion control system via adaptive dynamic programming (ADP) and neural networks (NNs) is proposed. The two-axis motion control system is an X-Y table actuated by permanent-magnet linear synchronous motor servo drives. First, the motions of the tracking contour in X-axis and Y-axis of the X-Y table are stabilized through feedback linearization control (FLC) laws. However, the control performance may be destroyed due to parameter uncertainties and compounded disturbances. Therefore, to improve the robustness of the control system, an NROC is designed to achieve this purpose. The tracking control problem of the X-Y table with uncertainties is transformed to a regulation problem. Then, it is solved by an infinite horizon optimal control using a critic NN. Consequently, the NN is developed via ADP learning algorithm to facilitate the online solution of the Hamilton-Jacobi-Bellman equation corresponding to the nominal system for approximating the optimal control law. The uniform ultimate boundedness of the closed-loop system is proved utilizing the Lyapunov approach and the tracking error asymptotically converges to a residual set. The validation of the proposed control schemes are carried out through experimental analysis. The control algorithms have been implemented using a DSP control board. A comparison of control performances using FLC, adaptive FLC, and FLC-based NROC is investigated. From the experimental results, the dynamic behaviors of the two-axis control system using the proposed FLC-based NROC can achieve robust optimal control performance against parameter uncertainties and compounded disturbances.

A novel high-precision motion control for permanent magnet linear synchronous motor servo system

In this paper, a novel high-precision motion control is proposed for a permanent magnet linear synchronous motor (PMLSM) servo system, which is vulnerable to the influence of uncertainties. First, the dynamics of the PMLSM with uncertainties are derived. To cater for the parametric uncertainties, the model-based feedforward control is constructed so that the transient response of the system is improved. Moreover, the adaptive jerk control (AJC) scheme based on a robust integral of the sign of the error (RISE) feedback is adapted to restrain the uncertainties such as external disturbance and nonlinear friction in the system. To alleviate the chattering phenomenon, a novel exponential adaptive law is designed to bound the feedback gain of the jerk, under the condition of the initial term of control efforts considered. Then, the jerk signal is integrated to form the feedback control law, which generates continuous control input and ensures the stability of the system. Compared with sliding mode control (SMC), the experimental results indicate that both the robustness and tracking performance of the system are significantly improved without adding more control efforts. The position tracking error is reduced and high-frequency oscillation is effectively attenuated.

Simultaneous Stiffness Measurement Device for a Human Forearm

The paper proposes a stiffness measurement device composed of a measurement part that includes four indenters and an arm anchorage part that includes four linear servomotors. The device is able to make simultaneous stiffnesses measurements of the human forearm. An indenter using parallelogram mechanisms has two degrees-of-freedom and is designed to measure the stiffness at various locations. The kinematics of the parallelogram mechanism is computed to control the position of the indenters. Additionally, the admittance compensator for force control is designed so that the indenter can press the skin surface of the human forearm. According to the force level measured at loadcell installed on the indenter, the control is switched between pure position control and admittance control. Further, this device includes a two-axis potentiometer at the indenter endpoint. This potentiometer acts like a passive two degrees-of-freedom universal joint, allowing the indenter to press perpendicular to the measurement skin area. For this purpose, the mapping between the voltage output and the potentiometer angle was obtained by fitting for each axis. The proposed measurement device was tested for accuracy and repeatability. Ultimately, the measurement device was able to measure the stiffnesses of four regions of the human limb simultaneously.

Tracking Accuracy Improvement Based on Adaptive Nonlinear Sliding Mode Control

Oftentimes, due to mechanical wear and ambient environment variations, friction-related parameters may vary with respect to the position of the iron-core linear servomotor. In addition, cogging force is also a function of the iron-core linear servomotor's position. In order to cope with the adverse effects caused by friction and cogging force, this article proposes a disturbance compensation approach based on nonuniform rational B-spline (NURBS), in which the parameters of the proposed NURBS-based disturbance compensation approach are represented as a function of the linear servomotor's position. The parameters of the proposed NURBS-based friction model are updated using online adaptive laws designed based on the Lyapunov stability theory. Moreover, in order to attain excellent tracking performance for a motion stage actuated by iron-core linear servomotors, this article combines the proposed NURBS-based friction model and cogging force model with fast nonsingular terminal sliding mode control (FNTSMC) to develop adaptive nonlinear sliding mode control (ADNSMC). The proposed ADNSMC inherits the advantages of both FNTSMC and the proposed NURBS-based disturbance compensation approach. Experimental results indicate that the proposed ADNSMC exhibits satisfactory performance on tracking control and disturbance compensation.

Intelligent Adaptive Jerk Control With Dynamic Compensation Gain for Permanent Magnet Linear Synchronous Motor Servo System

In this paper, an intelligent adaptive jerk control (IAJC) with dynamic compensation gain for the permanent magnet linear synchronous motor (PMLSM) servo system was proposed to improve robustness and tracking performance against nonlinear and time-varying uncertainties. First, the dynamic model of the PMLSM servo system was investigated. Subsequently, the model-based feedforward control was designed for parametric uncertainties. Then, an adaptive jerk control (AJC) was adopted to restrain external load disturbance, nonlinear friction and unmodeled dynamics of the servo system. The adaptive feedback gain of jerk was updated by an exponential function. However, the uncertainties of the PMLSM servo system were unavailable in advance, it was difficult to design the adaptive feedback gain in practice. Thus, in the following part, the IAJC was further developed in which a dynamic compensation gain was designed using a double-loop recurrent feature selection fuzzy neural network (RFSFNN) to compensate for approximation deviation and suppress the chattering phenomenon. The learning algorithms of the double-loop RFSFNN were derived and the stability of the closed-loop system was proved by the Lyapunov approach. Finally, the experimental results demonstrate that the proposed IAC scheme can achieve robust precise tracking performance.

Dual stage control of a servo system consisting of a piezoelectric actuator and a linear motor for electrical discharge machining

Gap width is the most important factor that affects the stability of the electrical discharge machining (EDM) process, material removal rate and surface finish of the workpiece. This research is to develop a new hybrid positioning system which consists of a linear servo motor and a piezoelectric actuator (PZT) for high efficiency EDM processes. In this new system, the servo motor provides the macro feeding for the workpiece while the PZT feeds the workpiece in micro scale at high frequency. To reduce the delay caused by separate movements of the linear motor and PZT, a new control algorithm was developed to synchronize the movements of both the motor and PZT. Cutting experiment shows that an increase in MRR of 1.5 times was achieved by using the proposed algorithm.

Extended Kalman filter-based disturbance feed-forward compensation considering varying mass in high-speed permanent magnet linear synchronous motor

A disturbance feed-forward compensation method based on 7th-order extended Kalman filter (EKF) is proposed for permanent magnet linear synchronous motor (PMLSM) servo system which is vulnerable to the influence of external disturbances, such as friction force, force ripple and so on. Firstly, a disturbance model which consists of position-dependent functions was developed and utilized as a disturbance feed-forward compensator. Then, the initial position and the varying mass information of plant were estimated by the 7th-order EKF and reflected to the disturbance feed-forward compensator. In addition, the coefficients of the disturbance model were adjusted adaptively to create synchronization between the model and real disturbance and achieve the purpose of varying mass estimation and disturbance compensation. Finally, the system simulation and experiment results confirm that the proposed method is effective and feasible. The PMLSM servo system based on 7th-order EKF has superior performance in disturbance compensation, and it is not affected by the varying mass of PMLSM.

Force ripple compensation in a PMLSM position servo system using periodic adaptive learning control

Force ripple deteriorates the performance of permanent magnet linear synchronous motor (PMLSM) servo systems. Using a model reference adaptive control and periodic adaptive learning control (MRAC–PALC) algorithm, this paper presents a novel compensation method to eliminate the influence of force ripple on the system performance of a position servo system under repetitive motion tasks. The key idea of the proposed method is to utilize the periodic characteristics of both force ripple and system motion. The controller consists of four components: a PD component, a feedforward component, a velocity feedback component and an MRAC–PALC compensator. The first three components are designed in a conventional way. The compensator is divided into two parts: in the 0th-iteration, an MRAC algorithm is employed to obtain the initial information, and in the ith-iteration (i≥ 1), a PALC algorithm is used to learn from the information obtained in the previous period and update the controller parameters for estimating force ripple. Moreover, a theoretical stability analysis is given via Lyapunov stability theorem, and some comparative results are provided through simulations and experiments.

Linear Active Disturbance Rejection Control for Nonaffine Strict-Feedback Nonlinear Systems

This paper presents a linear active disturbance rejection controller (LADRC) for nonaffine nonlinear systems with strict-feedback form. The proposed LADRC results in a closed-loop system with a three-time-scale structure, in which a reduced-order linear extended state observer estimates unmeasured states and total disturbance in the fastest time scale and dynamic inversion based on sector conditions is used to deal with nonaffine inputs in the intermediate time scale while the system dynamics evolves in the slowest time scale. The singular perturbation method is used to analyze the stability and performance of the system. The effectiveness of the proposed LADRC is demonstrated through simulation studies and experimental validation on a linear motor servo system with nonaffine uncertainties.

Adaptive Neural Network Nonsingular Fast Terminal Sliding Mode Control for Permanent Magnet Linear Synchronous Motor

For the problem that the position tracking accuracy of permanent magnet linear synchronous motor (PMLSM) servo system is easily affected by uncertain factors such as parameters change, load disturbance and friction and so on, an adaptive neural network nonsingular fast terminal sliding mode control (ANNNFTSMC) method is proposed. Firstly, the PMLSM dynamic mathematical model with uncertainty is established. Then, the nonsingular fast terminal sliding mode control (NFTSMC) can avoid the singularity problem and make the state of the system converge to the equilibrium point quickly, so as to improve the response speed of the system. Secondly, in order to minimize the influence of disturbance and dynamic uncertainty, the dynamic model of PMLSM servo system is estimated by RBF neural network, and the uncertain upper bound of PMLSM servo system is estimated in real time combined with adaptive control, which weakens the chattering phenomenon and enhances the robustness of the system. It is proved theoretically that the control scheme can make the system achieve fast convergence and good tracking. Finally, the system experiments show that the proposed control scheme has the advantages of high tracking accuracy, good robustness, fast response speed and small position error.

Approach Angle-Based Saturation Function of Modified Complementary Sliding Mode Control for PMLSM

In this paper, an approach angle-based saturation function of modified complementary sliding mode control (MCMSC) method was proposed to overcome the influence of uncertainties such as parameter variations and external disturbances on permanent magnet linear synchronous motor (PMLSM) servo system. On the foundation of the mathematical model considering uncertainties of PMLSM and the theory of sliding mode control (SMC), complementary sliding mode control (CSMC) method was designed by combining the integral sliding surface with the complementary sliding surface. By using the continuous saturation function, CSMC can efficiently eliminate the system chattering phenomenon caused by the discontinuous function in SMC and further improve the position tracking accuracy. However, the saturation function makes the boundary layer in CSMC constant, so the asymptotic stability of the system cannot be guaranteed. Hence, an approach angle-based saturation function of MCSMC was designed to realize the dynamic change of the boundary layer, which can diminish the boundary layer with the change of state trajectory until it converges to the sliding surface, thereby further improving the robustness of the system. Additionally, the hybrid SMC methods, such as fuzzy-SMC and neural network-SMC (NN-SMC), are avoided. A precise test platform based on digital signal processor (DSP) was implemented, and experimental results are shown to demonstrate the effectiveness and correctness of the proposed method.

Research on Multi-Loop Nonlinear Control Structure and Optimization Method of PMLSM

Recently, the permanent magnet linear synchronous motor (PMLSM) servo control technology has become a research hotspot. However, the control performance under the traditional PID control is not ideal, which usually has the problems of slow response speed, large overshoot and poor anti-interference performance. In addition, adding nonlinear links with certain characteristics purposefully can greatly improve the performance of the system and achieve the expected effect that the traditional linear controllers cannot achieve. Based on this, this paper introduces the nonlinear PID control strategy into the field of servo control, and proposes a nonlinear control strategy of the three-loop of the servo system to improve the above problems. Firstly, the proposed structure is explained and the rule of nonlinear parameters selection is discussed. Secondly, the conditions for the structural stability of the proposed nonlinear control strategy are analyzed. Finally, experiments on the servo system platform are carried out and the results verify the fast dynamic response, precise positioning and good anti-disturbance performance.

Re-Design of a Packaging Machine Employing Linear Servomotors: a Description of Modelling Methods and Engineering Tools

Position-controlled servo-systems mostly make use of electric rotary motors and gearboxes and, if necessary, a transmission mechanism to convert rotary into linear motion. Even so, especially in the field of automatic machines for packaging, it should be highlighted that most of the required movements are usually linear, so that Linear Electric Motors (LEM) should somehow represent a more convenient solution for designers. LEM can directly generate the required trajectory avoiding any intermediate mechanism, thus potentially minimizing the number of linkages/mechanical parts and, therefore, the undesired backlash and compliance that come along. On the other hand, particularly within small-medium enterprises, LEM may be rarely employed despite obvious advantages, mostly due to their high-cost as compared to rotary actuators and the lack of knowledge of the achievable performance. In light of these considerations, the present paper reports an industrial case study where an automatic machine for packaging, comprising distributed actuation and several tasks requiring a linear motion, has been completely redesigned employing different kind of LEM (i.e. iron-core and iron-less). Such machine architecture is compared to a “traditional” design where brushless gear-motors are coupled to linkage systems. The paper mainly focuses on the selection criteria for the LEM system and on the engineering tools employed during the different design stages. Qualitative and quantitative conclusions are finally drawn, which may provide useful hints for designers that are willing to actually employ LEM-based solutions in an industrial scenario

Designing multi-input multi-output modal-space negative acceleration feedback control for vibration suppression of structures using active mass dampers

The objective of this study was to design multi-input and multi-output feedback control for vibration suppression of structures using multiple active mass dampers driven by linear servo motors. The linear servo motor was used to enhance control effectiveness and decrease noise. The multi-input and multi-output modal-space negative acceleration feedback control was developed to fully utilize multiple accelerometers and multiple active mass dampers. Control spillover problem due to mistuning of the negative acceleration feedback control was also investigated in detail. To determine the efficacy of the proposed multi-input and multi-output modal-space negative acceleration feedback control, a two-story building-like structure was built and tested. A dynamic model was derived by using energy approach and beam modeling. The proposed multi-input multi-output modal-space negative acceleration feedback controller was validated both theoretically and experimentally for the test structure. Both numerical and experimental results showed that the proposed controller could effectively suppress vibrations.

Design of L1 Adaptive Controller for Position Control of Permanent Magnet Linear Synchronous Motor (PMLSM)

In the present work, the design of an L1 adaptive controller for position control of a linear servo motor for X-Y table application has been developed. The AC Permanent Magnet Linear Synchronous Servo Motor (PMLSM) is considered. A comparative study between L1 adaptive control and Model Reference Adaptive Control (MRAC) has been made. The effectiveness of the L1 adaptive controller against uncertain parameters is analyzed based on simulated results. Robustness characteristics of both L1 adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty have been evaluated. The L1-adaptive controller could ensure uniformly bounded transient and asymptotic tracking for input and output signals. Simulations based on MATLAB of an x-y table based on PMLSM with time-varying friction and disturbance are presented to verify the theoretical findings. The simulation results within the environment of MATLAB/SIMULINK showed that L1-adaptive controller could give better tracking performance, dynamic and steady-state characteristics, than that obtained from MRAC for considered types of input and for various structures of uncertainties.