— This article reports on the development and implementation of an algorithm for the design of spatially-distributed feedback controllers for the wide variety of physical processes that are included in cross-directional control of industrial paper machines. The spatial and temporal structure of this class of process models is exploited in the use of the two-dimensional frequency domain for anal...

Abstract: This paper describes DB(n) control algorithm extended on Antiwindup and state space version of algorithm. Author derived extended version of algorithm. This version of algorithm in conjunction with on-line identification has the adaptive self-tuning performance. The synthesis was derived for control loop with proportional third order behaviour of controlled plant. However, the algorit...

Active Noise Control (ANC) systems are developing rapidly because of their improvements in environmental noise reduction. ANC is based on either feedforward or feedback control. Feedback structures are employed in applications that the reference signal is not available. The step size of filters used in ANC systems plays an essential role in performance of the system. Any variation from the appr...

This contribution demonstrates possibility of delta models for identification and process control of higher order plants by the help of self-tuning delta controllers. Simulation will show behaviour of second order delta controllers used for control of higher order plants. It is used pole placement method and method Ziegler-Nichols for syntheses of controller, comparison is done for different st...

The paper presents the identification issues of the self-tuning nonlinear controller ASPECT (Advanced control algorithmS for ProgrammablE logiC conTrollers). The controller is implemented on a simple PLC platform with an extra mathematical coprocessor, but is intended for the advanced control of complex processes. The model of the controlled plant is obtained by means of experimental modelling....

Decentralized control has been popular very much because of its very good results in several tasks of control of multidimensional systems. Adaptation enlarges the area of the usage especially in the case that standard controllers with fixed parameters are unsatisfactory. Last year we have introduced a new approach based on a modified tuning method based on a combination of one-dimensional self-...

Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a quadratic cost function is minimised, without ignoring the variance of the model predictions. This leads to implicit regularisation of the control signal (caution) in areas of high uncertainty. As a consequence, the c...

This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous multivariable nonlinear stochastic hybrid systems with input saturation. Here, the continuous nonlinear stochastic system is assumed to have unknown system parameters, system and measurement noises, and inaccessible system states. The proposed method enables the development of a digitally...

In the paper, a new multivariable self-tuning PID controller design scheme is proposed which has a static matrix precompensator to reduce the interaction terms of the process transfer function matrix adjusted by an online estimator. The p £ p precompensated multivariate system is then controlled via ‘p’ univariate self-tuning PID controllers whose parameters are adjusted by a second identifier ...

Most Active Queue Management (AQM) algorithms based on control theory have difficulty in obtaining desirable performance once the network conditions or the traffic patterns change out of the presumed ones they are designed for. To address these problems, a new self-tuning AQM algorithm called STR is proposed in this paper. STR has the ability of keeping minimum variance between the instantaneou...