43 research outputs found
Applicability of Asymptotic Tracking in Case of Type 1 Diabetes
No full textThe alarming increasing tendency of diabetes population attracts technological interest too. From an engineering point of view, the treatment of diabetes mellitus can be represented by an outer control loop, to replace the partially or totally deficient blood glucose control system of the human body. To acquire this “artificial pancreas” a reliable glucose sensor and an insulin pump is needed as hardware, and a control algorithm to ensure the proper blood glucose regulation is needed as software. The latter is a key point of the diabetes “closing the loop” problem and its primary prerequisite is a valid model able to describe the blood glucose system. In the current chapter one of the most widely used and complex nonlinear model will be investigated with a dual purpose. Specific control aspects are discussed in the literature only on linearized versions; however, differential geometric approaches give more general formalization. As a result our first aim is to hide the nonlinearity of the physiological model by transforming the control input provided by a linear controller so that the response of the model would mimic the behavior of a linear system. Hence, the validity of linear controllers can be extended from the neighborhood of a working point to a larger subset of the state-space bounded by specific constraints. On the other hand, applicability of the nonlinear methodology is tested on a simple PID control based algorithm compared with LQG optimal method. Simulations are done under MATLAB on realistic input scenarios. Since the values of the state variables are needed Kalman filtering is used for state estimation
System Identification by Statistical Methods — Spectral Analysis — from Disturbed Measurements
No full textExperimental results of model-based fuzzy control solutions for a laboratory antilock braking system
No full textThis chapter presents aspects concerning the design of model-based fuzzy control solutions dedicated to the longitudinal slip control of an Antilock Braking System laboratory equipment. Continuous-time and discrete-time Takagi-Sugeno (T-S) fuzzy models of the controlled process are first derived on the basis of the modal equivalence principle. The consequents of the T-S models of the T-S fuzzy controllers are local state feedback controllers which are solutions to several linear quadratic regulator (LQR) problems and the parallel distributed compensation is next applied. Linear matrix inequalities are solved to guarantee the global stability of the discrete-time fuzzy control systems and to give the optimal state feedback gain matrices of the LQR problems. A set of real-time experimental results is included to validate the new fuzzy control solutions
Development methods of fuzzy controllers with dynamics for low order benchmarks (electrical drives)
No full textDevelopment of some fuzzy controllers with non-homogenous dynamics with respect to the input channels meant for a class of systems
No full textFuzzy Control Algorithms Implementation for a Synchronous Generator Connected to a Power System
No full textFUZZY CONTROL ALGORITHMS IMPLEMENTATION FOR A SYNCHRONOUS GENERATOR CONNECTED TO A POWER SYSTEM
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