Prediction-Based Control of Linear Systems by Compensating Input-Dependent Input Delay of Integral-Type

International audienceThis study addresses the problem of delay compensation via a predictor-based output feedback for a class of linear systems subject to input delay which itself depends on the input. The equation defining the delay is implicit and involves past values of the input through an integral relation, the kernel of which is a polynomial function of the input. This modeling represents systems where transport phenomena take place at the inlet of a system involving a nonlinearity, which frequently occurs in the processing industry. The conditions of asymptotic stabilization require the magnitude of the feedback gain to comply with the initial conditions. Arguments for the proof of this novel result include general Halanay inequalities for delay differential equations and take advantage of recent advances in backstepping techniques for uncertain or varying delay systems

Control-oriented input-delay model of the distributed temperature of a SI engine exhaust catalyst

International audienceThis chapter aims at showing how a particular class of input delay ordinary differential equations, in which the time- and input-dependent delay is defined through an implicit integral equation, can be used to model accurately the internal temperature of a Spark-Ignited engine catalyst. The modeling approach is grounded on a one-dimensional distributed parameter model, which is approximated by a time-varying first-order delay system whose dynamics parameters (time constant, delay, gains) are obtained through a simple analytic reduction procedure. Following recent works, the distributed heat generation resulting from pollutant conversion is shown here to be equivalent to an inlet temperature entering the system at a virtual front inside the catalyst. The gain of this new input introduces a coupling to ac- count for the conversion efficiency. Relevance of this real-time compliant model is qualitatively supported by experimental data