Smith Predictor with Inverted Decoupling for stable TITO Processes with Time Delays Juan Garrido Universidad de Cordoba Computer Science Dept. Campus de Rabanales 14071 Cordoba (Spain) juan.garrido@uco.es Francisco Vázquez Universidad de Cordoba Computer Science Dept. Campus de Rabanales 14071 Cordoba (Spain) fvazquez@uco.es Fernando Morilla UNED, Computer Sci. and Automatic Control Dept. Juan del Rosal 16 28040 Madrid (Spain) fmorilla@dia.uned.es Abstract This paper presents a new design methodology of multivariable Smith predictor for stable 2×2 time delay processes based on the centralized inverted decoupling structure. The controller elements are calculated in order to achieve good reference tracking and decoupling response, and the obtained general expressions result very simple. The realizability conditions are stated and the particular case of processes with all of its elements as first order plus time delay systems is discussed in more detail. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response. The methodology is applied to two simulation examples and comparisons with other authors show its effectiveness. 1. Introduction Time delays arise in many industrial processes as a consequence of different phenomena such as transport times of mass, information or energy; accumulation of time lags in processes interconnected in series; or processing time [1]. Time delays affect the performance of traditional control systems because they can lead to very poor system response as they prevent high controller gain from be used in order to avoid instability. The Smith Predictor (SP) was the first compensator specially designed for single-input single output (SISO) systems with time delay [2]. It allows the elimination of the time delay in the characteristic equation. In the last years, different modifications of the SP have been developed to overcome some drawbacks of its initial proposal and to improve its performance [3-5]. On the other hand, most industrial processes are multivariable systems, that are much more difficult to control compared with SISO counterparts because of the existence of interactions between the measurement signals and the control signals. Two-input two-output (TITO) system is one of the most prevalent categories of multivariable systems, because there are real processes of this nature or because a complex process can be decomposed in 2×2 blocks [6] with non negligible interactions between its inputs and outputs. The control system design for multivariable processes with time delays becomes even more difficult because each output is affected by each input with different time delays [7]. As a result, a transfer function matrix representation of the multivariable process is preferred in these cases [8]. Different approaches have been developed in order to design controller for multivariable systems with multiple time delays. Some authors develop directly pure multivariable methodologies: decoupling control [9-13], multivariable PID controllers [14, 15], H • controllers [16], or decentralized controllers [17, 18]. Other authors have extended the SP to the multivariable case [19-21] using a scheme similar or equivalent to that of Fig. 1 where G(s) is the plant, G n (s) is the nominal model of the plant, G o (s) is the fast model of the process and C(s) is the primary controller. Figure 1. Smith Predictor scheme. In order to apply SP to multivariable systems, two approaches can be usually found. The first one consists in designing a decoupling compensator D(s) for the original process G(s) in order to obtain a diagonal or diagonal dominant apparent process, and then, applying the SP to this apparent process H(s)=G(s)·D(s) (Fig. 2) [22]. Then, the SP design can be carried out as that of SISO case. The second one and more common applies 