The paper presents aspects related to the design and implementation of a cascade control solution (CCS), which is tested on laboratory equipment meant for the position control of a ferromagnetic sphere in a Magnetic Levitation System with Two Electromagnets (MLS2EM). The nonlinear mathematical model (MM) of the MLS2EM is derived on the basis of the first principles equations with experimentally identified parameters. This MM is next linearized at two operating points. The CCS includes a state feedback controller in the inner loop and a model predictive controller in the outer loop. Experimental results are given in order to validate the proposed CCS and to illustrate the performance of the position control system expressed as very good dynamics and zero steady-state control error.

This paper treats the design and implementation of a low-cost neuro-fuzzy control solution for a class of servo systems with an integral component and variable parameters. A hybrid Takagi-Sugeno PI-neuro-fuzzy controller (T-S PI-N-FC) is proposed and presented along with its relatively simple design approach. The solution carries out the on-line adaptation of a single parameter of the input membership functions of a TakagiSugeno PI-fuzzy controller with input integration (T-S PI-FC-II) by a single neuron trained by back propagation with momentumfactor in the framework of a model reference adaptive controller structure. The second parameter of the input membership functions is tuned by the modal equivalence principle. Linear matrix inequalities are proposed as sufficient stability conditions to be fulfilled by the parameters of the rule consequents of the T-S PI-FC-II in order to guarantee the stable design of the hybrid T-S PI-N-FC. The solution is validated by a case study using a set of three process parameters that correspond to a strip winding system laboratory equipment. Digital simulation results and experimental results are given.

No abstract

No abstract

No abstract