Design of a general purpose 6-DOF haptic interface

A general purpose six degree-of-freedom haptic device is newly designed, which can be used as a general motion commander as well as a force reflector. The structure features the large workspace and easy analysis of a serial structure and the compactness and durability of a parallel structure at the same time. The study analyzed kinematics of the proposed device to obtain the optimal device parameters in terms of kinematics and derived dynamics to form a linear control system through the feedback. In calculating the optimal design factors of the haptic device in terms of kinematics, this study employed the global isotropy index. The proposed structure has high manipulability within the workspace, which is an essential factor for a motion generator. Also the study proposed a force controller featuring an inner nonlinear loop designed to compensate the nonlinear dynamics of the device and an outer linear control loop aimed to compensate un-modeled dynamics and disturbance. For an outer linear controller, the study adopted an LQG/LTR controller that can systematically take into account stability, robustness and frequency characteristics in the design process. The performance of the proposed device was verified with its efficiency through simulation and experiments.     

Intelligent optimal control of single-link flexible robot arm

This paper addresses the design and properties of an intelligent optimal control for a nonlinear flexible robot arm that is driven by a permanent-magnet synchronous servo motor. First, the dynamic model of a flexible robot arm system with a tip mass is introduced. When the tip mass of the flexible robot arm is a rigid body, not only bending vibration but also torsional vibration are occurred. In this paper, the vibration states of the nonlinear system are assumed to he unmeasurable, i.e., only the actuator position can be acquired to feed into a suitable control system for stabilizing the vibration states indirectly. Then, an intelligent optimal control system is proposed to control the motor-mechanism coupling system for periodic motion. In the intelligent optimal control system a fuzzy neural network controller is used to learn a nonlinear function in the optimal control law, and a robust controller is designed to compensate the approximation error. Moreover, a simple adaptive algorithm is proposed to adjust the uncertain bound in the robust controller avoiding the chattering phenomena. The control laws of the intelligent optimal control system are derived in the sense of optimal control technique and Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. In addition, numerical simulation and experimental results are given to verify the effectiveness of the proposed control scheme.     

Nonlinear control of mechatronic systems with permanent-magnet DC motors

The current trends in development and deployment of advanced electromechanical systems have facilitated the unified activities in the analysis and design of state-of-the-art motion devices, electric motors, power electronics, and digital controllers. This paper attacks the motion control problem (stabilization, tracking, and disturbance attenuation) for mechatronic systems which include permanent-magnet DC motors, power circuity, and motion controllers. By using an explicit representation of nonlinear dynamics of motors and switching converters, we approach and solve analysis and control problems to ensure a spectrum of performance objectives imposed on advanced mechatronic systems. The maximum allowable magnitude of the applied armature voltage is rated, the currents are limited, and there exist the lower and upper limits of the duty ratio of converters. To approach design tradeoffs and analyze performance (accuracy, settling time, overshoot, stability margins, and other quantities), the imposed constraints, model nonlinearities, and parameter variations are thoroughly studied in this paper. Our goal is to attain the specified characteristics and avoid deficiencies associated with linear formulation. To solve these problems, an innovative controller is synthesized to ensure performance improvements, robust tracking, and disturbance rejection. One cannot neglect constraints, and a bounded control law is designed to improve performance and guarantee robust stability. The offered approach uses a complete nonlinear mechatronic system dynamics with parameter variations, and this avenue allows one to avoid the conservative results associated with linear concept when mechatronic system dynamics is mapped by a linear constant-coefficient differential equation. To illustrate the reported framework and to validate the controller, analytical and experimental results are presented and discussed. In particular, comprehensive analysis and design with experimental verification are performed for an electric drive. A nonlinear bounded controller is designed, implemented, and experimentally tested.     

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.     

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.     

H∞ control of a flexible gantry robot arm using smart actuators

This paper presents new feedback actuators to achieve an accurate position control of a flexible gantry robot arm. The translational motion in the plane is generated by two d.c. motors and controlled by electro-rheological (ER) clutch actuators. The generated motion can be continuously controlled by controlling the intensity of electric fields imposed to the ER fluid domains of bi-directional rotating ER clutches. On the other hand, during control action of the translational motion, a flexible arm attached to the moving part produces undesirable oscillations due to its inherent flexibility. The oscillations are actively suppressed by employing feedback voltage to the piezoceramic actuator bonded on the surface of the flexible arm. Consequently, an accurate position control at the end-point of the flexible arm can be achieved. In order to accomplish this control target, the governing equations of the proposed system are derived and rewritten as transfer functions to design a robust H_∞ controller. The control electric fields to be applied to the ER clutch and the control voltage for the piezoceramic actuator are determined via the loop shaping design procedures (LSDP) in the H_∞ control technique. Control results of position regulating and tracking are provided to evaluate the effectiveness of the proposed methodology.     

Modular integrated longitudinal and lateral vehicle stability control for electric vehicles

In this paper, the problem of integrated longitudinal and lateral vehicle stability control is addressed using a modular optimal control structure. The optimization process of the high level model predictive control (MPC) controller determines required longitudinal force and yaw moment adjustments to minimize the error between vehicle longitudinal and lateral vehicle stability dynamic states with respect to the target courses. The low level controller is designed to optimally regulate torque at each wheel based on the control inputs of the high level controller, and distribute required torque between the wheels via actuation system. The actuation system that is utilized to implement the proposed control structure functions based on all-wheel drive technology that can provide active control of both traction and yaw moment control with differential torque. The multi-layered structure of the control system allows modularity in design. The performance of the control structure is investigated by conducting experimental tests. The experimental tests have been performed on an electric Chevrolet Equinox vehicle equipped with four independent motors. The results show that the integration of the vehicle longitudinal and lateral dynamics preserves vehicle stability in a planar motion and improves the vehicle dynamic response, especially in challenging driving maneuvers.     

Safe operation of scaling bilateral control system under application of excessive force by operator

Physical interaction between humans and robots in a remote environment can be realized safely with bilateral teleoperation. The acceleration-based scaling bilateral controller and the reaction force estimator implemented with the disturbance observer facilitate robust control and vivid touch sensation between different structures. This paper introduces a replica-side security enhancement method when the operator applies excessive force on the master during scaling bilateral motion. Initially, the system follows four-channel acceleration-based scaling bilateral control. It switches to the master side virtual impedance controller and replica side force controller as the bearable force limit is reached on the replica. As a result, the operator-applied excessive force is not transmitted to the remote end, and the master maneuvers freely following the operator's intention. This method supports the operator's freedom while protecting the replica object. This study derives the value of virtual impedance aiming at high reproducibility. As a result, the operator receives replica side object impedance throughout the operation even when controllers are switched. This study analyzes the stability considering pole placement with system parameter variations. Experiments verified the proposed method. The results demonstrate that the proposed method ensures the safety of remote objects while the operator freely applies excessive force. The operator was able to successfully sense object impedance irrespective of whether the system followed scaling bilateral control or constrained scaling motion control.     

Control of linear motor machine tool feed drives for end milling: Robust MIMO approach

Linear motors are getting promising for use as high speed, high accuracy machine tool feed drives. The cutting force in the machining process are directly reflected to the linear motor due to no gearing mechanism. To achieve high accuracy machining, the controller for the linear motor system should be designed to compensate for the cutting force.

In this work, a MIMO H_∞ controller for the linear motor machine tool feed drives has been designed to reduce tracking errors induced by cutting forces for end milling. The controller is designed using normalized coprime factorization method for the dynamic model of the linear motor system. The model includes constant in-line and cross coupling force gain, since the feedback cutting force can be considered as the product of the constant gain and the moving velocity of each axis.

Analysis of the structured singular value shows that the designed controller has good robust performance despite wide variations of the cutting force and physical parameters. It is directly implemented on a linear motor X–Y table which is mounted on a milling machine to have cutting experiments via a DSP board. Experimental results verified effectiveness of the proposed scheme to suppress the effects of the cutting force in the high feed rate.     

Lateral stabilization of a four wheel independent drive electric vehicle on slippery roads

In this paper, a new controller is proposed for lateral stabilization of four wheel independent drive electric vehicles without mechanical differential. The proposed controller has three levels including high, medium and low control levels. Desired vehicle dynamics such as reference longitudinal speed and reference yaw rate are determined by higher level of controller. Moreover, using a neural network observer and a fuzzy logic controller, a novel reference longitudinal speed generator system is presented. This system guarantees the vehicle’s stable motion on the slippery roads. In this paper, a new sliding mode controller is proposed and its stability is proved by Lyapunov stability theorem. This sliding mode control structure is faster, more accurate, more robust, and with smaller chattering than classic sliding mode controller. Based on the proposed sliding mode controller, the medium control level is designed to determine the desired traction force and yaw moment. Therefore, suitable wheel forces are calculated. Finally, the effectiveness of the introduced controller is investigated through conducted simulations in CARSIM and MATLAB software environments.     

The use of GPS for vehicle stability control systems

This paper presents a method for using global positioning system (GPS) velocity measurements to improve vehicle lateral stability control systems. GPS can be used to calculate the sideslip angle of a vehicle without knowing the vehicle model. This measurement is combined with other traditional measurements to control the lateral motion of the vehicle. Noise estimates are provided for all measurement systems to allow the sensors to be accurately represented. Additionally, a method to calculate the lateral forces at the tires is presented. It is shown that the tire estimation algorithm performs well outside the linear region of the tire. Results for the controller and force calculations are shown using a nonlinear model to simulate the vehicle and the force calculations are validated with experimental measurements on a test vehicle.     

Nonlinear adaptive control of direct-drive brushless DC motors andapplications to robotic manipulators

Robust adaptive nonlinear control of brushless DC (BLDC) motors is considered. A controller is designed for the plant that is robust to parametric and dynamic uncertainties in the entire electromechanical system. These uncertainties are shown to be bounded by polynomials in the states. In addition, the controller can reject any bounded unmeasurable disturbances entering the system. A model for the motor incorporating magnetic saturation is used to design voltage-level control inputs for the motor. The design methodology is based on our earlier work on adaptive control of nonlinear systems. The overall stability of the system is shown using Lyapunov techniques. The tracking error is shown to be globally uniformly bounded. The design procedure is shown to be also applicable to multilink manipulators actuated by BLDC motors. The performance of the controller is verified through simulations and comparisons with a proportional-integral-derivative-type controller are made     

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.     

Adaptive Control of Two-Axis Motion Control System Using Interval Type-2 Fuzzy Neural Network

An interval type-2 fuzzy neural network (IT2FNN) control system is proposed for the precision control of a two-axis motion control system in this paper. The adopted two-axis motion control system is composed of two permanent-magnet linear synchronous motors. In the proposed IT2FNN control system, an IT2FNN, which combines the merits of an interval type-2 fuzzy logic system and a neural network, is developed to approximate an unknown dynamic function. Moreover, adaptive learning algorithms that can train the parameters of the IT2FNN online are derived using the Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties, including a minimum reconstructed error, optimal parameter vectors, and higher order terms in Taylor series. To relax the requirement for the value of the lumped uncertainty in the robust controller, an adaptive lumped uncertainty estimation law is also investigated. Last, the proposed control algorithms are implemented in a TMS320C32 digital-signal-processor-based control computer. From the simulated and experimental results, the contour tracking performance of the two-axis motion control system is significantly improved, and the robustness can be obtained as well using the proposed IT2FNN control system.     

Contact-free planar stage using linear induction principle

The feasibility of using a linear induction motor as a driving actuator for a contact-free planar stage is investigated for various situations. In this stage, the features of an induction motor such as no cogging force, ease of workspace enlargement, and a simple metrology process may be advantageous. The induction principle has inherently limited performance. So, a novel control method and a structural modification are suggested to compensate for the poor characteristics of the induction system. First, a modified vector controller, in which the normal force is controlled with direct current (dc) current biased to three-phase current under settled d-axis flux, replaces the general dq-based controller. Secondly, a pair of linear induction motors, in which the traveling direction of the moving part changes not by a phase change of three-phase current but by a difference of thrust forces from each linear induction motor, substitutes for a single linear induction motor to compensate for discontinuity due to the phase shift of alternating current (ac). Therefore, the stage with a dynamic characteristic, such as a double integrator in the planar direction, is preloaded in the planar direction. Finally, the influence of air stiffness on the ripple of normal force due to the ac drive is analyzed for two types of air-supporting mechanisms. All the aforementioned methods are verified experimentally.     

Performance tuning of robust motion controllers for high-accuracy positioning systems

This paper presents a structural design method of robust motion controllers for high-accuracy positioning systems, which makes it possible to tune the performance of the whole closed-loop system systematically. First, a stabilizing control input is designed based on Lyapunov redesign for the system in the presence of uncertainty and disturbance. And adopting the internal model following control, robust internal-loop compensator (RIC) is proposed. By using the structural characteristics of the RIC, disturbance attenuation properties and the performance of the closed-loop system determined by the variation of controller gains are analyzed. Next, in order to design a robust motion controller for a high performance positioning system, dual RIC structure is proposed and it is shown that if the synthesis of the robust motion control law is performed in the RIC framework, the robust property of RIC can be naturally implanted in the feedback controller. The proposed structural design of robust motion controller provides a systematic approach to the problem of robust stability and performance requirement in the face of uncertainty. Furthermore, by allowing the tradeoffs between robust stability and performance to be quantified in a simple fashion, it can illuminate systematic design procedure of the robust motion controllers. Finally, the proposed method is verified through simulation and the performance is evaluated by experiments using a high-accuracy positioning system.     

四轮驱动四轮转向的汽车电子差速转向控制

通过汽车转向时稳定性分析阐明了四轮转向的优点。而鉴于轮毂电机在电动汽车上应用的诸多优点,及其功率受结构体积的限制,轮毂电机的应用将使汽车由性能更好的四轮驱动替代两轮驱动,它不但充分利用了地面对车轮的附着力和驱动力,而且结合用直线步进电机控制转向力的汽车转向系统,能更容易地实现全面改善转向性能的四轮转向系统。由于四轮驱动...     

Feedback-linearizing control of IPM motors considering magnetic saturation effect

This paper describes feedback-linearizing control of interior permanent magnet (IPM) motors which operate in magnetic saturation. First, we propose a current tracking controller for direct control of stator currents. Then, we explicitly characterize all torque controllers that can make the motor torque of an IPM motor exactly linear with respect to torque command even if magnetic saturation occurs. In particular, our torque controller contains a free function that can be used to achieve other control objectives as well as linear dynamic characteristics. Finally, the free function is chosen so optimal as to maximize power efficiency. The practical use of our control method is demonstrated through various simulation and experimental results.     

Motion and Internal Force Control for Omnidirectional Wheeled Mobile Robots

This paper presents an integrated scheme for motion control and internal force control for a redundantly actuated omnidirectional wheeled mobile robot. The interactive forces between a robot body and its wheels can be reduced into two orthogonal parts: motion-induced forces and internal forces. First, it is shown that the internal forces reside in the null space of the coefficient matrix of the interactive forces and do not affect robotic motion. However, these forces caused by motor torques should be minimized as much as possible to increase the energy efficiency and life span of joint components. With different goals, the control for motion and the control for internal forces can be designed separately. Here, both kinematic and dynamic models of the forces are proposed. A proportional differential plus controller regulates the motion and an inverse dynamic controller tracks it. Then, to minimize the internal forces, an integral feedback internal force controller is used. The motion controller guarantees the robotic motion while the internal force controller minimizes the internal force occurring during robot motion. Simulation results verify the effectiveness of the proposed schemes.     

Stabilization system on an office-based ear surgical device by force and vision feedback

An “office-based surgical device” is a kind of device which aims to shift the conventional surgical procedures from the operating room to the confines of the doctor’s/surgeon’s office as well as to assist the surgeons to carry out the surgeries on the patients automatically or semi-automatically. In this paper, an office-based surgical device suitable for patients with Otitis Media with Effusion (OME) is introduced. Due to the office-based design, it is not possible to subject the patient to general anesthesia, i.e., the patient is awake during the surgical treatment with the device. To ensure a high success rate and safety, it is very important that the relative motion and the contact force between the tool set of the device and the tympanic membrane (TM) can be stabilized. To this end, a control scheme using force and vision feedback is proposed. The force feedback controller is a PID-based (proportional-integral-derivative) controller, which is designed for force tracking. The vision feedback controller is a vision-based motion compensator, which is designed to measure and compensate the head motion since it is equivalent to TM motion. Furthermore, the control scheme is implemented and tested in a mock-up system. The experimental results show that the proposed composite controller can achieve much better performance in force tracking than a pure force feedback controller. The performance can at least improve by 20% after augmenting the motion compensator, which helps the system to stabilize the relative motion indirectly and maintain the contact force precisely.