Wen-Fang Xie

Brief paper: Adaptive tracking of nonlinear systems with non-symmetric dead-zone input

Quite successfully adaptive control strategies have been applied to uncertain dynamical systems subject to dead-zone nonlinearities. However, adaptive tracking of systems with non-symmetric dead-zone characteristics has not been fully discussed with minimal knowledge of the dead-zone parameters. It is shown that the controlled system preceded by a non-symmetric dead-zone input can be represented as an uncertain nonlinear system subject to a linear input with time-varying input coefficient. To cope with this problem, a new adaptive compensation algorithm is employed without constructing the dead-zone inverse. The proposed adaptive scheme requires only the information of bounds of the dead-zone slopes and treats the time-varying input coefficient as a system uncertainty. The new control scheme ensures bounded-error trajectory tracking and assures the boundedness of all the signals in the adaptive closed loop. By appropriate selections of the controller parameters, we show that the smoothness of the controller does not affect the accuracy of trajectory tracking control. A numerical example is included to show the effectiveness of the theoretical results.

Sliding-Mode-Observer-Based Adaptive Control for Servo Actuator With Friction

In this paper, a novel sliding-mode observer based adaptive controller is developed for the servo actuators with friction. The LuGre dynamic friction model is adopted for adaptive friction compensation. A sliding-mode observer is proposed to estimate the internal friction state of LuGre model. Based on the estimated friction state, adaptation laws are designed to compensate the unknown friction and load torque. The stability of the adaptive controller with sliding-mode observer is analyzed. The position tracking performance has been verified through experimental results.

Pattern recognition with SVM and dual-tree complex wavelets

A novel descriptor for pattern recognition is proposed by using dual-tree complex wavelet features and SVM. The approximate shift-invariant property of the dual-tree complex wavelet and its good directional selectivity in 2D make it a very appealing choice for pattern recognition. Recently, SVM has been shown to be very successful in pattern recognition. By combining these two tools we find that better recognition results are obtained. We achieve the highest rates when we use the dual-tree complex wavelet features with the Gaussian radial basis function kernel and the wavelet kernel for recognizing similar handwritten numerals, and when we use the Gaussian radial basis function for palmprint classification. Our findings are that the dual-tree complex wavelets are always better than the scalar wavelet for pattern recognition when SVM is used. Also, among many frequently used SVM kernels, the Gaussian radial basis function kernel and the wavelet kernel are the best for pattern recognition applications.

Observer-based control of discrete-time Lipschitzian non-linear systems: application to one-link flexible joint robot

The problem of designing asymptotic observers along with observer-based feedbacks for a class of discrete-time non-linear systems is considered. We assume that the system non-linearity is globally Lipschitz and the system is supposed to be stabilizable by a linear controller. Sufficient linear matrix inequality condition is derived to ensure the stability of the considered system under the action of feedback control based on the reconstructed states. A numerical example of a single-link flexible joint robot is presented to illustrate the efficacy of the theoretical developments.

Fuzzy adaptive internal model control

In this paper, a fuzzy adaptive internal model controller (FAIMC) for open-loop stable plants is presented. The control scheme consists of two parts: a fuzzy dynamic model and a model-based fuzzy controller. A fuzzy dynamic model, which serves as the internal model of the FAIMC is identified online by using the input and output measurement of the plant. Based on the identified fuzzy model, the fuzzy controller is designed to minimize an H/sub 2/ performance objective. This FAIMC scheme has been successfully applied to control the flow rate in a laboratory-scale process control unit from Bytronic. The experimental results demonstrate that this class of control scheme is appropriate for control of time-varying stable plants with time delay. The control system is also shown to possess satisfactory robust performance.

New model and simulation of Macpherson suspension system for ride control applications

The main purpose of this paper is to propose a new nonlinear model of the Macpherson strut suspension system for ride control applications. The model includes the vertical acceleration of the sprung mass and incorporates the suspension linkage kinematics. This two-degree-of-freedom (DOF) model not only provides a more accurate representation of the Macpherson suspension system for control applications in order to improve the ride quality, but also facilitates evaluation of the suspension kinematic parameters, such as camber, caster and king-pin angles as well as track alterations on the ride vibrations. The performances of the nonlinear and linearised models are investigated and compared with those of the conventional model. Besides, it is shown that the semi-active force improves the ride quality better than active force, while the opposite is true in terms of improving the performance of the kinematic parameters. The results of variations of the kinematic parameters based on the linear model subject to road disturbances are compared with those of a virtual prototype of Macpherson suspension in ADAMS software. The analytical results in both cases are shown to agree with each other.

Switching Control of Image-Based Visual Servoing With Laser Pointer in Robotic Manufacturing Systems

In this paper, an Eye-in-Hand robotic system with laser pointer is developed to detect, grasp, and assemble a planar object on a main body in robotic manufacturing systems. This paper is focused on detecting the object and moving the end effector to a position where a pump can perfectly suck up the object. A switching control of image-based visual servoing (IBVS) is designed to control the pose of the end effector with respect to the stationary object so that the image features of the planar object observed by the camera converge to the target image features for the further assembly. A simple off-the-shelf laser pointer is adopted to realize the depth estimation for obtaining the image Jacobian matrices. By using a laser spot as an image feature and the separate degree-of-freedom method, the proposed switch-control algorithm decouples the rotational and translational motions of the camera to avoid the inherent drawbacks of traditional IBVS. The experiments on a robotic assembly system are given to verify the effectiveness of the proposed method.

Sliding mode fault tolerant control dealing with modeling uncertainties and actuator faults.

In this paper, two sliding mode control algorithms are developed for nonlinear systems with both modeling uncertainties and actuator faults. The first algorithm is developed under an assumption that the uncertainty bounds are known. Different design parameters are utilized to deal with modeling uncertainties and actuator faults, respectively. The second algorithm is an adaptive version of the first one, which is developed to accommodate uncertainties and faults without utilizing exact bounds information. The stability of the overall control systems is proved by using a Lyapunov function. The effectiveness of the developed algorithms have been verified on a nonlinear longitudinal model of Boeing 747-100/200.

Optimized Control of Semiactive Suspension Systems Using H

In this paper, an optimized modified skyhook control for the semiactive Macpherson suspension system, equipped with a magnetorheological (MR) damper, is investigated. Using H∞ robust control theory and a 2-D dynamic model, including the kinematics of the suspension system, a robust output feedback controller is developed. The combination of a linear matrix inequality (LMI) solver and genetic algorithm (GA) is adopted to optimize the control gains. Further a 3-D kinematic model is introduced to evaluate the kinematic performance of the controlled suspension system. An inverse dynamic model of the MR damper is obtained based on the experimental results for tuning the input current signal. The effectiveness of the control system is discussed and validated through the simulations and experiment.

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Smart actuators such as magneto-restrictive actuators, shape memory alloy (SMA) actuators, and piezoceramic actuators exhibit different hysteresis loops. In this paper, a generalized Prandtl-Ishlinskii model is utilized for modeling and compensation of hysteresis nonlinearities in smart actuators. In the formulated model, a generalized play operator together with a density is integrated to form the generalized Prandtl-Ishlinskii model. The capability of the formulated model to characterize hysteresis in smart actuators is demonstrated by comparing its outputs with experimental results obtained from different smart actuators. As an example, hysteresis nonlinearities of the magnetostrictive and SMA actuators are characterized by the generalized Prandtl-Ishlinskii model. Furthermore, an analytical inverse of the generalized Prandtl-Ishlinskii model is derived for compensations in different smart actuators. In other words, exact inverse of the generalized Prandtl-Ishlinskii model is achievable and it can be implemented as a feedforward compensator to migrate the effects of the hysteresis in different types of smart actuators. Such compensation is experimentally illustrated by piezoceramic actuator.