Y.A. Jiang

Controller design for hot strip finishing mills

The results to date of a collaborative research project with BHP Steel in Port Kembla, Australia, are described. The project is concerned with control of strip tension and looper angle in BHPs hot strip steel rolling mill (the finishing mill). The new controllers have been successfully implemented on the process and now handle all the production at the mill. The paper describes a model of the process, similar to that reported in the work of others. The development of a full nonlinear controller is traced, based on a recursive nonlinear method (cf., backstepping). Insights are drawn into possible system structures, particularly in the output feedback case when tension measurements may not be available. Alternative controller schemes are examined, including a speculative design which contains filters, similar to those obtained from output feedback designs of linear systems, together with nonlinear operators which invite comparisons with variable structure designs. Simulation results, which provided the justification for the final implementation, together with results from actual production records are presented.

Adaptive learning control of robot manipulators in task space

Adaptive sliding mode control is considered, together with an iterative learning control scheme for tracking control of robot manipulators in Cartesian space coordinates. It is shown that the algorithm is globally convergent in the presence of external disturbances and modelling uncertainties. Owing to the robustness of the algorithm, a large gain for learning control can be used to achieve fast convergence of tracking errors. Moreover, the control scheme is rather simple and the inverse of the Jacobian matrix is not required.

Variable structure based decentralized adaptive control

This paper proposes a model free scheme for the design of a decentralised adaptive control scheme for large scale systems with higher order interconnections. The basic idea is to use a variable structure adaptive controller to guarantee the system stability and to account for the uncertain higher order interactions. The global stability of the overall system is established based on the Lyapunov theory.

Trajectory control of manipulators using adaptive sliding mode control

Considers an adaptive control algorithm for robot manipulators. The presented algorithm uses an adaptive sliding mode control law to ensure robustness. The proposed algorithms eliminate the requirement for inversion of the inertia matrix, the requirement for measurement of joint acceleration, and the requirement for calculation of a regressor. Computer simulation results show good properties of the proposed algorithm under large manipulator parameter uncertainties and disturbances.<<ETX>>

High Order Sliding-mode Control of Uncertain Linear Systems

Abstract High order sliding control of linear systems with unmatched perturbations is considered. A closed-loop system matrix assignment design procedure is proposed. The method is a modification of back-stepping design to take the advantage of scaling. A new high order sliding mode controller is presented, in which a nonlinear scaling function is used to achieve sliding mode.

Output feedback sliding-mode control of linear systems

The paper considers output feedback sliding-mode control of uncertain linear (nonminimum-phase) SISO systems. A new observer-free method is proposed, based on the transformation of the output feedback control problem to a state-feedback (scaled H/sub /spl infin//) control problem.

Betterment learning control of nonlinear systems

This paper considers betterment learning control of a class of uncertain nonlinear systems. We present a simple learning algorithm that exhibits uniform boundedness and ultimate uniform boundedness of the trajectories of the states. Moreover, if the initial condition errors are zero, the trajectories converge to zero.

Non-minimal state-space realisation in H/sub /spl infin// control design

A non-minimal state-space realisation is used in this paper to represent linear uncertain systems described with input-output relationships. By this method, a dynamic output feedback control problem can be transformed to a state-feedback control problem. This will simplify the optimal I/O scaled H/sub /spl infin// output control problem.

Rejection of Unmatched Disturbances in Sliding Mode Control

Abstract Sliding mode control of linear systems with unmatched input disturbances is considered in this paper. Matched uncertainties and disturbances, which lie in the range space of the input signals, can be easily handled with sliding mode control associated with a fixed sliding surface. To deal with unmatched disturbances, a dynamical sliding surface is necessary. The possibility of driving the state of the controlled system to a dynamical sliding surface is exploited which may result in an asymptotically stable output in the presence of the unmatched input distul bances.

Adaptive control of robot manipulators in task space

This paper considers adaptive control of robot manipulators in task space. An adaptive sliding-mode control scheme is combined with nonlinear integral control to derive a globally stable adaptive control algorithm. With this algorithm, the robustness is guaranteed by the sliding-mode control law and the chattering associated with sliding mode control is eliminated by the integral control law. With the proposed algorithm, model uncertainties and external disturbances can be easily handled. The algorithm has the advantages that the inverse of the Jacobian matrix is not required, that a detailed description of the dynamic model is not required and that only some PID operations are required for its implementation.<<ETX>>