摘要:

The problem of controlling a robot with end effector rigidly gripping an inertial load is studied using the generalised command-matching technique via proportional state feedback. In particular, the necessary and sufficient conditions for the problem to have a solution are established and the general analytical expressions of the controller matrices are derived. Structural properties of the resulting closed-loop system are also investigated.

DOI:10.1049/ip-d.1993.0049

出版商:IEE    

年代:1993

数据来源: IET

摘要:

A state space based self-tuning controller is proposed that incorporates a closed loop pole restriction principle. The plant matrices, Kalman gain and the states are estimated using a bootstrap method. The state feedback control design is based upon a modified LQ infinite-time control that restricts the closed loop poles within a user-specified disk in thez-plane to meet the maximum overshoot and the maximum settling time specifications. The control design is called only when the estimated closed loop poles with the fixed existing control rule move out of the specified disk. This approach reduces the computational requirement significantly and also increases the stability robustness by providing a piecewise time-invariant control.

DOI:10.1049/ip-d.1993.0050

出版商:IEE    

年代:1993

数据来源: IET

摘要:

Multilayered neural networks are used to construct nonlinear learning control systems for a class of unknown nonlinear systems in a canonical form. An adaptive output tracking architecture is proposed using the outputs of the two three-layered neutral networks which are trained to approximate the unknown nonlinear plant to any desired degree of accuracy by using the modified back-propagation technique. A weight-learning algorithm is presented using the gradient descent method with a dead-zone function, and the descent and convergence of the error index during weight learning are shown. The closed-loop system is proved to be stable, with the output tracking error converging to the neighbourhood of the origin. The effectiveness of the proposed control scheme is illustrated through simulations.

DOI:10.1049/ip-d.1993.0051

出版商:IEE    

年代:1993

数据来源: IET

摘要:

An algorithm for self-tuning control of discrete-time linear plant is proposed. The algorithm uses a stochastic right-matrix-fraction innovation description as the system representation, a recursive-prediction-error algorithm for online estimation of the system parameters and the costates, and pole placement plus moving-average control via costate and innovation feedback.

DOI:10.1049/ip-d.1993.0052

出版商:IEE    

年代:1993

数据来源: IET

摘要:

In this paper two types of intelligence supervised controllers are proposed with the aim to achieve an overall performance beyond the limit of linear controllers. In each case, the overall controller has a hierarchical structure with two conventional linear controllers in the bottom layer to perform accurate control action under the supervision of a reasoning process in the top layer. The reasoning process consists of heuristic rules drawn from our physical insight, and can easily be implemented either by fuzzy logics or by IF … THEN statements. Both intelligence supervised controllers achieve a performance beyond the limit of linear control laws, and are superior to both a fuzzy controller and a neural controller at least in the sense that their performances are independent of the type of command.

DOI:10.1049/ip-d.1993.0053

出版商:IEE    

年代:1993

数据来源: IET

摘要:

Consideration of control limits in the design of discrete control system and their impact on system performance is discussed in this paper. The mechanism of how the control limits influence the closed loop system behaviour is investigated using an approach different from that commonly adopted in the literature. Theoretical analysis in this paper reveals the effect of control limits in the form of a short-term behaviour of the controlled system. This phenomenon is investigated by introducing a concept of ‘short-term behaviour index’. With the introduction of ‘dynamic control limits’, an effective discrete control system design method is proposed to handle this problem.

DOI:10.1049/ip-d.1993.0054

出版商:IEE    

年代:1993

数据来源: IET

摘要:

This paper addresses the problem of obtaining stabilising controllers for a class of uncertain discrete time systems containing delayed controls. A generalisation of the so-called ‘matching condition’ is formulated and two kinds of robust stabilising feedback controllers are proposed. An illustrative example is presented to show validity of the approach.

DOI:10.1049/ip-d.1993.0055

出版商:IEE    

年代:1993

数据来源: IET

摘要:

This paper presents a method for the design of decentralised controllers for interconnected dynamic systems with structured uncertainties. The design problem is formulated as a constrained linear quadratic optimal regulator problem, where the cost function is designed to incorporate the system uncertainties. Conditions are then derived for choosing the state and control weighting matrices that guarantee closed-loop stability in the presence of the uncertainties. Once these matrices are appropriately chosen, a generalised Riccati equation is solved and a robust decentralised controller is obtained. Two numerical examples are given to illustrate the controller design method.

DOI:10.1049/ip-d.1993.0056

出版商:IEE    

年代:1993

数据来源: IET

摘要:

Computer programs, based on the polynomial approach, have been used to design fixed, linear, optimal roll loop controllers using typical plant and disturbance models. Design parameters may be adjusted to produce systems which satisfy a hard limit on aileron angle and which have a range of step responses. The controller complexity may be reduced as part of the design process. The performance of the resulting single-loop system is examined and compared with that of the corresponding double loop design in which roll rate as well as roll angle is fed back. In cases where weathercock oscillation is a problem, it is demonstrated how the system attenuation at the weathercock frequency might be increased. The details of a worked example are given in Appendix 8 to illustrate the design method.

DOI:10.1049/ip-d.1993.0057

出版商:IEE    

年代:1993

数据来源: IET

摘要:

A new hybrid learning algorithm is proposed for use in the parametric estimation of Gaussian potential function networks (GPFNs). In the new algorithm, the number of network inputs is augmented by using target output values in the learning centres of Gaussian nodes in the network's hidden layer. This augmentation of input leads to a more reasonable distribution of centres in the hidden layer of a GPFN. A critical angle technique is then used to determine those nodes in which the shape factors will need further tuning by optimisation techniques. Two numerical examples are supplied to show the superior performance of this new algorithm as compared to that achieved through a traditional hybrid learning method, or to the optimised-only method of Lee and Kil. The capability of the GPFN as a dynamical model for continually tracking dynamics of non-stationary and time-varying systems is also illustrated.

DOI:10.1049/ip-d.1993.0058

出版商:IEE    

年代:1993

数据来源: IET