Design of Decoupled Pi Controllers for Two-Input Two-Output Networked Control Systems with Intrinsic and Network-Induced Time Delays

Proportional integral controller design for two-input two-output (TITO) networked control systems (NCSs) with intrinsic and network-induced time delays is studied in this paper. The TITO NCS consists of two delayed sub-systems coupled in a 1-1/2-2 pairing mode. In order to simplify the controller design, a decoupling method is first applied to obtain a decoupled system. Then, the controllers are designed based on the transfer function matrix of the obtained decoupled system and using the boundary locus method for determining the stability region and the well-known Mikhailov criterion for the stability test. A comparative analysis of the designed controllers and other controllers proposed in previous literature works is thereafter carried out. To demonstrate the validity and efficacy of the proposed method and to show that it achieves better results than other methods proposed in earlier literature works, the implementation in simulation of Wood–Berry distillation column model (methanol–water separation), a well-known benchmark for TITO systems, is carried out.

Decentralized robust evolving cloud-based controller for two input two output systems

The fuzzy logic controller (FLC) makes it possible to control a system using IF-THEN rules through human intellect. It tackles parameter uncertainty using imprecise reasoning. The fuzzy logic controller is usually tuned using offline methods. An online evolving adaptation of fuzzy controller design is a recent trend in fuzzy rule-based systems. The robust evolving cloud-based controller (RECCo) is one such controller implemented for single-input-single-output (SISO) systems. The membership functions and consequent rules are automatically updated in real time based on the input data. In this paper, a decentralized robust evolving cloud-based controller (DRECCo) is proposed for two-input-two-output (TITO) systems. It consists of two independent loops with RECCos having a nonparametric premise facet and an adaptive proportional-integral-derivative (PID) model consequent facet. The effectiveness of the proposed method is validated for the benchmark interacting two-tank process (ITTP) and quadruple-tank process (QTP) by simulation and in real time. The results indicate that with the information of loop pairing and the forward-acting/reverse-acting nature of the process, the proposed controller can adapt itself to ensure set-point tracking and disturbance rejection.

Methods of Pre-Identification of TITO Systems

The content of this article is the presentation of methods used to identify systems before actual control, namely decentralized control of systems with Two Inputs, Two Outputs (TITO) and with two interactions. First, theoretical assumptions and reasons for using these methods are given. Subsequently, two methods for systems identification are described. At the end of this article, these specific methods are presented as the pre-identification of the chosen example. The Introduction part of the paper deals with the description of decentralized control, adaptive control, decentralized control in robotics and problem formulation (fixing the identification time at the existing decentralized self-tuning controller at the beginning of control and at the beginning of any set-point change) with the goal of a new method of identification. The Materials and methods section describes the used decentralized control method, recursive identification using approximation polynomials and least-squares with directional forgetting, recursive instrumental variable, self-tuning controller and suboptimal quadratic tracking controller, so all methods described in the section are those ones that already exist. Another section, named Assumptions, newly formulates the necessary background information, such as decentralized controllability and the system model, for the new identification method formulated in Pre-identification section. This section is followed by a section showing the results obtained by simulations and in real-time on a Coupled Drives model in the laboratory.