Jung-Hua Yang

Nonlinear observer-based adaptive tracking control for induction motors 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.

Nonlinear adaptive control for manipulator system with gear backlash

The backlash, which is caused by a gap between an actuator-side gear tooth and a link-side gear tooth, is a common phenomenon in manipulator systems with gear in their joints. However, if the amount of backlash is greater than the maximum allowed amount which is to ensure satisfactory meshing of gear, the system instability may appear in dynamic situations and cause position errors in the gear chains. Hence, in this paper, a nonlinear adaptive controller is devised to cope with the effects due to backlash as well as parameter variation. A so-called semi-global tracking is achieved, and simulation studies are also provided to demonstrate the validity of the proposed strategy.

Adaptive robust control for flexible manipulators

Because the control DOF (Degree of Freedom) is much less than the motion DOF when a flexible manipulator is commanded to track a desired trajectory, many control strategies that succeed in conventional rigid-robot control cannot be directly applied to solve the flexible robot control problem. In this work, an adaptive variable structure scheme has been proposed to solve such a problem. The full nonlinear dynamics of the whole system are all taken into account for the control design. To alleviate the chattering phenomenon commonly seen in variable structure type of control, a saturation type adaptive scheme has also been proposed. For verification of the effectiveness of the proposed controller, a two-link flexible manipulator is built up and the promise of the controller is experimentally demonstrated.

Adaptive hybrid position/force control for robotic manipulators with compliant links

In this paper, we tackle the problem of nonlinear adaptive hybrid control of constrained robots with flexible links. According to the physical properties of a flexible manipulator, a two time-scale approach, namely singular perturbation approach, is further utilized for thorough analysis and general controller design. It is shown that asymptotic motion tracking can be effectively achieved, whereas the force regulation errors can be made arbitrarily small. For demonstration of the controller performance, experiments of a two-link flexible manipulator were performed for the proposed controller and satisfactory results observed.

Adaptive Robust Neural-Network Based Control for Siso Systems*

Abstract In this paper, an adaptive robust neural-network based control approach which exploits the merits of sliding mode technique is proposed for a class of feedback linearizable nonlinear systems with stable zero dynamics. No prior off-line training phase is needed and only a single feedforward neural network is employed. It is shown that the tracking errors converge to a neighborhood of zero, Stability of the system is proved by Lyapunov theory. All the simulation results have shown the satisfactory performance.

Multi-agent based control kernel for flexible automated production system

An intelligent automated robotic assembly system consists of several subsystems capable of providing dynamic interactions with the environment in order to accomplish a task properly. These subsystems perform various functions like data gathering, decision making, and task execution. Although a great deal of work has been done on individual subsystems, more attention must be given to the way how these subsystems are integrated so as to achieve the high efficiency of automated production. We propose a cooperative multi-agent model of a shop floor control system architecture of robotic assembly automation and extend this model to all automated production system. Based on this model, we develop a control kernel named TOFAK (task oriented flexible automation kernel) to support users to easily implement any shop floor control system. The by-product is to allow system designers to easily expand an existing system or to integrate several automation systems which are all controlled by TOFAK.

Nonlinear Adaptive Control of a Two-Axis Gun-Turret System with Backlash

Abstract This paper considers one of the two-axis gun-turret systems which is subject to some inevitable factors such as the backlash in the gear-chain, that will deteriorate seriously the pointing accuracy. The complete mathematical descriptions of the dynamics including backlash are developed. Thus, by exploiting the characteristics of the model of the gun-turret system, a nonlinear adaptive control scheme is proposed to meet the stringent performance requirements. A so-called semi-global tracking is achieved, and several simulation results are provided to demonstrate the validity of the proposed strategies.

Analysis and control for manipulators with both joint and link flexibility

An analysis of manipulators with both joint and link flexibility is presented. Due to the different order of joint and link stiffness, the full-order nonlinear system can be decomposed into different time-scale subsystems, namely, a slow subsystem, a mid-speed subsystem, and a fast subsystem. It is shown that when the link stiffness is much greater than joint stiffness or when the two kinds of stiffness are comparable, the vibrations due to joint or link flexibility can be suppressed regardless of what control effort is made. A composite control law is proposed in the case where the joint stiffness is much greater than the link stiffness to eliminate the structural vibrations while the tracking objective is achieved.<<ETX>>

The High Performance Adaptive Control of Induction Motors

Abstract In this paper, we propose a nonlinear robust adaptive control of the induction motors for the tasks of position tracking and of speed tracking. All of the system parameters including rotor resistance, rotor inductances, mutual inductance, mechanical load, and system inertia need not be known a priori , except the pole pair numbers. Mechanical load can be either a time-invariant or a time-varying function of rotor speed. A complete proof of the global stability is given without the assumption of persistently exciting condition on the reference input.

Adaptive Robust Neural-Network Based Control for Bank-to-Turn Missile Autopilot

Abstract In this paper, an adaptive robust neural-network based control approach which exploits the merits of sliding mode technique is proposed for For that scheme, a stable adaptive law is determined by Lyapunov theory, and the boundedness of all signals in the closed-loop system are guaranteed. No prior off-line training phase is needed. It is proved that the tracking errors converge to a neighborhood of zero. The simulation results have shown the satisfactory performance.