Adaptive robust motion control of linear motors for precision manufacturing

Linear motors offer several advantages over their rotary counterparts in many precision manufacturing applications requiring linear motion; linear motors can achieve a much higher speed and have the potential of gaining a higher load positioning accuracy due to the elimination of mechanical transmission mechanisms. However, these advantages are obtained at the expense of added difficulties in controlling such a system. Specifically, linear motors are more sensitive to disturbances and parameter variations. Furthermore, certain types of linear motors such as the iron core are subject to significant nonlinear effects due to periodic cogging force and force ripple. To address all these issues, the recently proposed adaptive robust control (ARC) strategy is applied and a discontinuous projection-based ARC controller is constructed. In particular, based on the special structures of various periodic nonlinear forces, design models consisting of known basis functions with unknown weights are used to approximate those unknown nonlinear forces. On-line parameter adaptation is then utilized to reduce the effect of various parametric uncertainties such as unknown weights, inertia, and motor parameters while certain robust control laws are used to handle the uncompensated uncertain nonlinearities effectively for high performance. The resulting ARC controller achieves a guaranteed transient performance and a guaranteed final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. In addition, in the presence of parametric uncertainties, the controller achieves asymptotic output tracking. Extensive simulation results are shown to illustrate the effectiveness of the proposed algorithm.     

A Novel Digital Control Technique for Brushless DC Motor Drives

Brushless DC (BLDC) motor drives are continually gaining popularity in motion control applications. Therefore, it is necessary to have a low cost, but effective BLDC motor speed/torque regulator. This paper introduces a novel concept for digital control of trapezoidal BLDC motors. The digital controller was implemented via two different methods, namely conduction-angle control and current-mode control. Motor operation is allowed only at two operating points or states. Alternating between the two operating points results in an average operating point that produces an average operating speed. The controller design equations are derived from Newton's second law. The novel controller is verified via computer simulations and an experimental demonstration is carried out with the rapid prototyping and real-time interface system dSPACE.     

A Globally Stable High-Performance Adaptive Robust Control Algorithm With Input Saturation for Precision Motion Control of Linear Motor Drive Systems

This paper focuses on the synthesis of nonlinear adaptive robust controller with saturated actuator authority for a linear motor drive system, which is subject to parametric uncertainties and uncertain nonlinearities such as input disturbances as well. Global stability with limited control efforts is achieved by breaking down the overall uncertainties to state-linearly-dependent uncertainties (such as viscous friction) and bounded nonlinearities (such as Coulomb friction, cogging force, etc.), and dealing with them via different strategies. Furthermore, a guaranteed transient performance and final tracking accuracy can be obtained by incorporating the well-developed adaptive robust control strategy and effective parameter identifier. Asymptotic output tracking is also achieved in the presence of parametric uncertainties only. Meanwhile, in contrast to the existing saturated control structures that are designed based on a set of transformed coordinates, the proposed saturated controller is carried out in the actual system states, which have clear physical meanings. This makes it much easier and less conservative to select the design parameters to meet the dual objective of achieving global stability with limited control efforts for rare emergency cases and the local high-bandwidth control for high performance under normal running conditions. Real-time experimental results are obtained to illustrate the effectiveness of the proposed saturated adaptive robust control strategy     

A robust digital position control of brushless DC motor with deadbeat load torque observer

A method for the robust position control of brushless DC (BLDC) motors is presented. The linear quadratic controller plus load torque observer is used to obtain an approximately linearized robust BLDC motor system for an AC servo, using the field-orientation method. The gains are obtained systematically from a discrete state space analysis. The robustness is obtained without affecting the overall system response. The load disturbance is detected by a zero-observer of the unknown and inaccessible input, and is feedforward compensated without requiring noisy current information. The overall system is controlled using a microprocessor, and the performance of each control algorithm is compared with both the simulation and the experimental results for two types of machines, a BLDC motor and a brushless direct drive (BLDD) motor     

Adaptive Approach to Motion Controller of Linear Induction Motor with Friction Compensation

In this paper, we propose a nonlinear adaptive controller and an adaptive backstepping controller for linear induction motors to achieve position tracking. A nonlinear transformation is proposed to facilitate controller design. In addition, the very unique end effect of the linear induction motor is also considered and is well taken care of in our controller design. We also consider the effect of friction dynamics and employ observer-based compensation to cope with the friction force. A stability analysis based on Lyapunov theory is also performed to guarantee that the controller design here can stabilize the system. Also, the computer simulations and experiments are conducted to demonstrate the performance of our various controller design.     

Robust adaptive control of sawyer motors without current measurements

We address nonlinear robust adaptive dynamic output feedback of voltage-fed dual-axis linear stepper (Sawyer) motors using a detailed motor model with electrical dynamics and significant uncertainties and disturbances. A coordinate transformation is proposed to decouple the model into three third-order subsystems along with an appended fifth-order subsystem. The controller utilizes only position and velocity measurements in each axis and achieves practical stabilization of position tracking errors. Adaptations are utilized so as not to require any knowledge of electromechanical system parameters. The controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. The controller corrects for the yaw rotation to achieve synchrony of motor and platen teeth.     

Modeling and control strategies for a variable reluctancedirect-drive motor

A high-performance ripple-free dynamic torque controller for a variable-reluctance (VR) motor intended for trajectory tracking in robotic applications is designed. A modeling approach that simplifies the design of the controller is investigated. Model structure and parameter estimation techniques are presented. Different approaches to the overall torque controller design problem are discussed, and the solution adopted is illustrated. A cascade controller structure consisting of a feedforward nonlinear torque compensator, cascaded to a nonlinear flux or current closed-loop controller is considered, and optimization techniques are used for its design. Although developed for a specific commercial motor, the proposed modeling and optimization strategies can be used for other VR motors with magnetically decoupled phases, both rotating and linear. Laboratory experiments for model validation and preliminary simulation results of the overall torque control system are presented     

Robust control of permanent magnet motors: VSS techniques lead tosimple hardware implementations

It is shown how very simple velocity-tracking robust controllers for permanent magnet motors driving nonlinear loads can be designed based on variable structure systems techniques. Very fast dynamics, accurate and robust velocity-tracking are achieved with very simple hardware components without resorting to powerful digital signal processors and related interface hardware. A cascade control structure is used to ensure maximum flexibility. The controller for a DC motor is considered in great detail. Extension to AC synchronous PM motors is also presented. At the different control levels robustness is addressed with specific algorithms and the simplest solution is always selected. The controller architecture for both DC and AC synchronous motor are presented and discussed in the paper. Experimental results related to the control of a DC motor driving a nonlinear load are also shown. They demonstrate feasibility and excellent performances of the proposed approach     

控制增益符号已知的MIMO非线性时滞系统自适应控制

针对一类具有死区模型并且控制增益符号已知的不确定多输入多输出非线性时滞系统,基于滑模控制原理提出了一种稳定的自适应神经网络控制方案。该方案通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性。通过利用积分型李亚普诺夫函数,并且构造逼近连续函数,闭环系统证明是半全局一致终结有界。仿真结果表明了该方法的有效性。     

Adaptive robust motion control of SISO nonlinear systems with implementation on linear motors

For the purpose of controlling an X–Y table driven by linear motors with a high precision, an adaptive robust motion tracking control method is first introduced. The controller is developed based upon a class of SISO nonlinear systems whose nonlinear part can be linearly parameterized. The advantage of such a controller is that parametric uncertainties and unknown disturbances can be dealt with, which is essential for a high precision of the control of linear-motor-driven X–Y table. With the prior knowledge of the bounds of the system parameters, a discontinuous projection is utilized in the adaptive law to ensure the boundedness of the parameters estimates. The algorithm is then implemented on a real X–Y table driven by the linear motors. In the modeling of such a system, fiction effects are also considered, which is useful for the derivation of the adaptive law. Experiments on the X–Y table are carried out and the results show excellent tracking performance of the system.     

一种基于神经网络的超稳定自适应控制算法

提出了一种用于控制复杂非线性系统的超稳定自适应控制算法。使用波波夫超稳定性原理设计控制器。用神经网络在线辨识系统的建模误差及不确定性因素，辨识结果作为补偿信号以实现系统的鲁棒控制。对一双输入双输出非线性系统的仿真结果表明，所提出的超稳定自适应控制算法具有较好的性能。     

Torque and current control of high-speed motion control systems with sinusoidal-PMAC motors

Describes a torque- and current-control application to a commercial motion-control system with sinusoidal permanent magnet ac (PMAC) motors. The control approach is based on maximization of torque-per-amp ratio. The proposed torque controller, in the form of torque feedforward plus proportional-integral (PI)-type torque feedback, utilizes the feedback of nominal torque signal only, a signal that can be readily calculated, online. No torque sensor is required. Through proper design of the desired nominal torque with adaptive control, the proposed torque controller can overcome disturbances due to torque estimation error and model uncertainties. A discrete-time approach is developed for inner-current loop control design. The inner-loop control gains, which are hard to obtain through manual tuning in practice, are determined by a dynamic model-based calculation methodology. Experimental evaluation on a commercial motion control system demonstrates the validity of the proposed approach in high-speed motions.     

Nonlinear adaptive speed and torque control of induction motorswith unknown rotor resistance

In this paper, we propose a nonlinear adaptive speed and torque controller of induction motors with unknown rotor resistance. All the system parameters except rotor resistance are assumed to be known, and only the stator currents and rotor speed are assumed to be available. The desired speed and torque should be a smooth bounded function. A complete proof of the global stability without singularity is given, and the output error will converge to zero asymptotically. Finally, the simulation and experimental results are given to demonstrate the effectiveness of the proposed controller     

Design of an Adaptive Controller for Microcomputer Implementation

A design procedure for an adaptive controller is described and applied to the design of a velocity controller for small dc motors. The basic concept has been to determine a small set of controllers each of which is capable of maintaining stability and acceptable performance over a specific region of motor load parameters. Optimal control theory is used to define the control coefficients while cluster analysis and decision function techniques from pattern recognition theory are used to determine each controller's region of applicability. Simulation results are presented to verify performance improvements using the design procedure. The design procedure produces an adaptive controller which is computationally feasible for implementation in small microcomputer systems.     

Nonlinear observer-based adaptive tracking control for inductionmotors with unknown load

In this paper, we propose a nonlinear observer-based adaptive controller for induction motors with unknown load. With the use of the skew-symmetric property of induction motors, a two-stage design technique is applied to construct an observer-based controller for velocity tracking control. To demonstrate the effectiveness of the proposed scheme, a voltage-control type of drive system is set up to perform the task of velocity tracking. The main computing facility consists of two personal computers, PC 486 and PC 286, of which one is to perform the calculation of the control law and the other is to provide the function of pulse width modulation (PWM) and to generate the gating pulses. Satisfactory experimental results are shown in the paper     

An adaptive fuzzy sliding-mode controller for servomechanismdisturbance rejection

A two-level spring-lumped mass servomechanism system was constructed for disturbance rejection control investigation. This dynamic absorber is similar to a model of the serial-type vehicle suspension system. The lower level is actuated by two DC servo motors, to provide the specified internal and external disturbances to the vibration control system. The upper level has another DC servo motor to control the main body balancing position. In order to tackle the system's nonlinear and time-varying characteristics, an adaptive fuzzy sliding-mode controller is proposed to suppress the main mass position variation due to external disturbance. This intelligent control strategy combines an adaptive rule with fuzzy and sliding-mode control technologies. It has online learning ability for responding to the system's time-varying and nonlinear uncertainty behaviors, and for adjusting the control rules and parameters. Only seven rules are required for this control system, and its control rules can be established and modified continuously by online learning. The experimental results show that this intelligent control approach effectively suppresses the vibration amplitude of the body, with respect to the external disturbance     

Nonlinear sliding-mode torque control with adaptive backsteppingapproach for induction motor drive

In this paper, the nonlinear sliding-mode torque and flux control combined with the adaptive backstepping approach for an induction motor drive is proposed. Based on the state-coordinates transformed model representing the torque and flux magnitude dynamics, the nonlinear sliding-mode control is designed to track a linear reference model. Furthermore, the adaptive backstepping control approach is utilized to obtain the robustness for mismatched parameter uncertainties. With the proposed control of torque and flux amplitude, the controlled induction motor drive possesses the advantages of good transient performance and robustness to parametric uncertainties, and the transient dynamics of the induction motor drive can be regulated through the design of a linear reference model which has the desired dynamic behaviors for the drive system. Finally, some experimental results are demonstrated to validate the proposed controllers     

Tracking control of biomathematical model of muscular vessel

Based on the backstepping design and Nussbaum-type gain function methods, the tracking control problem of chaotic muscular vessel systems with parameter uncertainties and external disturbances is addressed. The derived adaptive robust tracking controller guarantees that the closed-loop system is globally and uniformly bounded, and the tracking error is convergent to a small neighbourhood of zero. In addition, the singular problem of the controller can be avoided. Simulation results demonstrate the validity of this developed controller.     

Advanced simulation model for IPM motor drive with considering phase voltage and stator inductance

This paper proposes an advanced simulation model of driving system for Interior Permanent Magnet (IPM) BrushLess Direct Current (BLDC) motors driven by 120-degree conduction method (two-phase conduction method, TPCM) that is widely used for sensorless control of BLDC motors. BLDC motors can be classified as SPM (Surface mounted Permanent Magnet) and IPM motors. Simulation model of driving system with SPM motors is simple due to the constant stator inductance regardless of the rotor position. Simulation models of SPM motor driving system have been proposed in many researches. On the other hand, simulation models for IPM driving system by graphic-based simulation tool such as Matlab/Simulink have not been proposed. Simulation study about driving system of IPMs with TPCM is complex because stator inductances of IPM vary with the rotor position, as permanent magnets are embedded in the rotor. To develop sensorless scheme or improve control performance, development of control algorithm through simulation study is essential, and the simulation model that accurately reflects the characteristic of IPM is required. Therefore, this paper presents the advanced simulation model of IPM driving system, which takes into account the unique characteristic of IPM due to the position-dependent inductances. The validity of the proposed simulation model is validated by comparison to experimental and simulation results using IPM with TPCM control scheme.     

FPGA-Based Adaptive Backstepping Sliding-Mode Control for Linear Induction Motor Drive

A field-programmable gate array (FPGA)-based adaptive backstepping sliding-mode controller is proposed to control the mover position of a linear induction motor (LIM) drive to compensate for the uncertainties including the friction force. First, the dynamic model of an indirect field-oriented LIM drive is derived. Next, a backstepping sliding-mode approach is designed to compensate the uncertainties occurring in the motion control system. Moreover, the uncertainties are lumped and the upper bound of the lumped uncertainty is necessary in the design of the backstepping sliding-mode controller. However, the upper bound of the lumped uncertainty is difficult to obtain in advance of practical applications. Therefore, an adaptive law is derived to adapt the value of the lumped uncertainty in real time, and an adaptive backstepping sliding-mode control law is the result. Then, an FPGA chip is adopted to implement the indirect field-oriented mechanism and the developed control algorithms for possible low-cost and high-performance industrial applications. The effectiveness of the proposed control scheme is verified by some experimental results. With the adaptive backstepping sliding-mode controller, the mover position of the FPGA-based LIM drive possesses the advantages of good transient control performance and robustness to uncertainties in the tracking of periodic reference trajectories.