Chih-Lyang Hwang

Trajectory tracking of large-displacement piezoelectric actuators using a nonlinear observer-based variable structure control

The trajectory tracking of a large-displacement piezoelectric actuator (LDPA) using a nonlinear observer-based variable structure control (VSC) was developed. A mechanism of amplification using a double lever was first designed, fabricated, and tested. Subsequently, a nonlinear model for the LDPA was verified by sinusoidal response and system knowledge. Because not all of the states of the nonlinear model were available, a nonlinear state observer was employed to estimate the state (e.g., velocity, hysteresis, excitation force, and its derivative). For tracking the trajectory dominant by a specific frequency, the reference model with desired amplitude and phase features was designed. The proposed control scheme contained a feedback linearization with variable structure controller, a reference model to assign the desired dynamics, and a nonlinear state observer to estimate the unavailable state. The VSC included the following two parts: equivalent control and switching control. The equivalent control using the signals from observer and reference model was constructed to obtain the desired control behavior. Due to the existence of hysteresis, disturbance, and estimation error, the tracking performance was often deprived. In this situation, the switching control was employed to ameliorate the robust performance. The stability of the overall system was then verified by Lyapunov stability theory so that the ultimately bounded tracking was accomplished. Experiments of the LDPA were carried out to verify the usefulness of the proposed control.

A Network-Based Fuzzy Decentralized Sliding-Mode Control for Car-Like Mobile Robots

In this paper, the trajectory tracking of a car-like mobile robot (CLMR) using network-based fuzzy decentralized sliding-mode control (NBFDSMC) is developed. The scaling factors and the coefficients of the sliding surface for the control of the steering angle and forward-backward velocity of a CLMR are adopted by that for the control of two motors. Due to the delay transmission of a signal through an Internet and wireless module, a revision of fuzzy decentralized sliding-mode control (FDSMC) with suitable sampling time (i.e., NBFDSMC) is accomplished by the quality-of-service (QoS). The proposed control can track a reference trajectory without the requirement of a mathematical model. Only the information of the upper bound of system knowledge (including the dynamics of the CLMR, the delay feature of Internet network, and wireless module) is required to select the suitable scaling factors and coefficients of sliding surface such that an excellent performance is obtained. In addition, the stability of the closed-loop system in the presence of time-varying delay is addressed. Finally, a sequence of experiments including the control of unloaded CLMR and the trajectory tracking of CLMR is carried out to consolidate the usefulness of the proposed control system

A DSP-based fuzzy robust tracking control for piezoelectric servosystems

In this paper, a DSP-based fuzzy-linear-model robust tracking control (DFRTC) is developed for the piezoelectric servosystem (PS) with dominant hysteresis. The PS is approximated by the weighted combination of N fuzzy linear pulse transfer functions. The DFRTC contains equivalent control and switching control. Based on the fuzzy model, the equivalent control is designed by the dead-beat to the switching surface for every ideal subsystem. Then the H/sup /spl infin//-norm of the sensitivity function between the switching surface and the output disturbance is minimized. Although the effect of the output disturbance is attenuated, the control accuracy may not be good enough. The switching control based on the Lyapunov redesign is applied to improve the control performance. The stability of the overall system can be verified by Lyapunov stability theory. The experiments of the PS are given to confirm the usefulness of the proposed control.

Trajectory tracking of frictional direct-drive motors using fuzzy-linear-model-based robust variable structure control

First, a one-degree-of-freedom of the frictional direct-drive motor is approximated by nine linear state-space dynamic subsystems obtained by the local linearization about the operating point. Then the same fuzzy sets of the system rule are applied to design the fuzzy-linear-model-based robust variable structure control, including a fuzzy equivalent control and fuzzy switching control. The fuzzy equivalent control is designed to obtain the desired control behavior. The fuzzy switching control is applied to tackle the uncertainty caused by the approximation error of fuzzy-model and the interaction dynamics resulting from the other subsystems. The proposed control does not require the solution of linear matrix inequalities for obtaining a common positive definite matrix to ensure the stability of the closed-loop system. The simulations are also presented to confirm the usefulness of the proposed control.

Fuzzy Model Reference Adaptive Control Design for Uncertain Nonlinear Time-delay Systems

In this paper, the problem of fuzzy model ref- erence adaptive control (FMRAC) for a class of continuous- time multiple-input-multiple-output (MIMO) nonlinear uncer- tain systems with state delays and external disturbances is investigated. A reference model with the desired amplitude and phase properties is given to construct an error model. A fuzzy system is used to approximate an unknown optimal control law from the strategic manipulation of the model following tracking errors. The proposed FMRAC scheme uses on-line estimations for the control gains. Based on the Lyapunov stability theorem, a fuzzy adaptive control strategy using Takagi-Seguno (TS) fuzzy system with proportional-integral (PI) type can guarantee parameter estimation convergence and stability robustness of the closed-loop system. The performance of the proposed scheme is evaluated through the simulation results. A 2 DOF parallel robot control problem is simulated to demonstrate the validity of the proposed scheme.

Internet-Based Fuzzy Decentralized Microprocessor Control for a Two-Dimensional Piezo-Driven System

In this paper, the trajectory tracking of a two-dimensional piezo-driven system (2DPDS) using Internet-based fuzzy decentralized microprocessor control (IBFDMC) was developed. It was known that the piezoelectric actuator contained hysteresis, which was not one-to-one mapping and memory nonlinearity. Due to this nonlinearity and the coupling characteristic of 2DPDS, an effective decentralized control was difficult to design. From the very beginning, suitable coefficients of switching surface were assigned to stabilize the switching surface and to shape the response of tracking error. Based on the data of input-output, two scaling factors are employed to normalize the switching surface and its derivative. According to the concept of if-then rule, an appropriate rule table for the ith subsystem was then achieved. Finally, a sequence of experiments was carried out to confirm the usefulness of the proposed control.

Path Tracking and Obstacle Avoidance of Car-Like Mobile Robots in an Intelligent Space Using Mixed H/sub 2//H/spl infin/ Decentralized Control

In this paper, the trajectory tracking and obstacle avoidance of a car-like mobile robot (CLMR) within an intelligent space via mixed H2 / Hinfin decentralized control was developed. For implementing (dynamic) obstacle avoidance and trajectory tracking, two distributed CCD (charge-coupled device) cameras were established to realize the pose of the CLMR and the position of the obstacle. Based on the authority of these two CCD cameras, a suitable reference command for the proposed controller of the CLMR is planned by the information of the CCD camera with higher authority and then transmitted to the CLMR by a wireless device. The features of the proposed control included smaller energy consumption with bounded tracking error, attenuation of output disturbance, and improvement of control performance. The suggested control system contained two processors with multiple sampling rates. One personal computer (PC) was employed to capture the image of CLMR and obstacle, to plan a reference command for the CLMR, and then to transmit the reference command to the CLMR. The other was a DSP (digital signal processor) implementing in the CLMR to control two DC motors. A sequence of experiments was carried out to confirm the effectiveness of the proposed control system.

A Fuzzy-Neural Variable Structure Control for Nonlinear Time-Varying Delay Systems

In this paper, a partially known nonlinear dynamic system with input and state time-varying delay was approximated by N fuzzy-based linear subsystems described by state-space model with average-delay. For tracking the trajectory with a primary frequency, the fuzzy reference models with desired amplitude and phase features were established. Similarly, the same fuzzy sets of the system rule were employed to design a fuzzy-neural variable structure control (FNVSC). The proposed control contained a radial basis neural network to learn the uncertainties caused by the fuzzy-model error and the interactions resulting from the other subsystems. As the norm of the switching surface was inside of a defined set (e.g., ||sigma(t)|| < nsigma2) the learning law started; the proposed method was an adaptive control possessing a compensation of uncertainties. As it was outside of the other set (e.g., ||sigma(t)|| > nsigma1 , where nsigma1 > nsigma2) the learning law stopped; the proposed method became a robust control. A transition between robust control and adaptive control was also assigned to smooth the possible discontinuity of control input. In addition, no assumption about the upper bound of the time-varying delay for the state and the input is required; however, a time-average delay is needed for the controller design. The stability of the overall system was verified by Lyapunov stability theory

Fuzzy linear-model-based robust control for a class of nonlinear stochastic systems

In this paper, a nonlinear stochastic system (NSS) is approximated by weighted combination of N subsystems, which are described by ARMAX model (autoregressive moving-average model with exogenous input). The approximation error between the NSS and the stochastic fuzzy-model system (SFMS) is represented by nonlinear time-varying uncertainties (NTVU) in every subsystem. In the beginning, a dead-beat to the switching surface for every nominal subsystem is designed. The total disturbance of the ith subsystem is caused by the white noise, the approximation error of SFMS, and the interaction dynamics resulting from the other subsystems. In general, it is not small. Then the H/sup /spl infin// -norm of the weighted sensitivity function between the switching surface and the total disturbance is minimized. For obtaining a better performance, a fuzzy switching control is also designed. Finally, the simulations are carried out to confirm the validity of the proposed control.

The trajectory tracking of robots via a fuzzy linear pulse transfer function matrix based variable structure control

Due to the complexity of robot, its exact description is difficult. On the contrary, a linear model about a specific operating point for a nominal robot is easy Then, a nominal robot can be approximated by the weighted combination of N subsystems described by the pulse transfer function matrices. The approximation error between the robot and the fuzzy linear pulse transfer function matrix system (FLPTFMS) includes two categories: the structural one caused by parameter variations and the unstructural one caused by measurement noise and external disturbance. The approximation error is represented by the weighted combination of the output disturbance in every subsystem. In addition, the output response of the ith closed-loop subsystem is subjected to the uncertainties caused by the output disturbance and the interaction dynamics resulting from the other subsystems. Due to the existence of the (remaining) uncertainties, a disadvantageous response often occurs. Under the circumstances, a switching control in every subsystem is designed to reinforce the system performance. The experiments of two-joint robot in the horizontal plane with (or without) payload confirm the practicality of the proposed control.