Željko Ban

Adaptive control of peak current mode controlled boost converter supplied by fuel cell

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm’s weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm’s weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.

State Variables Estimation of Fuel Cell - Boost Converter System Using Fast Output Sampling Method

Estimation of state variables of a peak current mode (PCM) controlled DC-DC boost converter supplied by a PEM fuel cell is described in this paper. Since this system is highly nonlinear and non-minimum phase, its state variables are estimated by using fast output sampling method. Estimated state variables are the converter output voltage and its first derivative, and they are suitable for model reference adaptive control or sliding mode based control techniques. The estimator has been designed in a way that it gives a good estimate of the state variables in the continuous and in the discontinuous conduction mode of the converter, and in the presence of measurement and process noise caused by converter switching-mode operation. Experimental results of estimating the state variables on a 450 W boost converter supplied by the emulator of the PEM fuel cell BCS 64–32 show good results of the estimation, regardless of the conduction mode of the converter, i.e. the operating point determined by its output current.

Optimization of a Servo System With a Referent Model and Inner Parameter Adaptation Loop

Abstract A rather slow adaptation to parameter variations is achieved in those servosystems which contain a PI controlled inner control loop and the outer control loop with a referent model and parameter adaptation. This paper is concerned with involvement of the referent model and parameter adaptation in the inner control loop of the servo system, while keeping the PI controller in an outer control loop. A very fast adaptation was achieved by optimization of parameter adaptation algorithm coefficients for a given range of variations of a drive moment of inertia An impact of a sampling interval and state variable estimator on the maximum value of a referent model tracking error during transient response has investigated.