Researches Of Dual Rate Control For Mixed Separation Thickening Process

The mixed separation thickening process(MSTP)of hematite beneficiation is a strong nonlinear cascade process with the speed of slurry pump as the input,the slurry flow-rate as the inner loop output and the concentration as the outer loop output.During its operation,some large and frequent random disturbances generating from the flotation middling and sewage will cause continuous dynamic of slurry concentration and slurry flow-rate,which will cause failure of controller integration.The influence between the outer and inner loop will deteriorate the dynamic performance of the controlled system and cause resonance.The model parameters,such as settling velocity of slurry particles and slurry height are unknown and nonlinear.Moreover,these model parameters vary in line with flotation middling,sewage and magnetic separation slurry.The main works in the thesis are as follows:(1)The simulation model of mixed separation thickening processIn this thesis,the dynamic characteristics of the mixed separation thickening process are analyzed,and the structure of the simulation model of the controlled object is established.Then the simulation model of the controlled object is obtained by the alternating identification with the least square method and neural network.When there is a large range of frequent interference or the model parameters change randomly,we adopt simulation experiments to verify modeling method used in this paper for the slurry flow-rate and slurry concentration models.The simulation results obtained by the alternating identification method are compared with the simulation results by mechanism principal model with neural network compensator.The feasibility and effectiveness of the proposed method are verified.(2)Dual rate control algorithms for mixed separation thickening processTo deal with the problem of wide range interferences,lifting technique is used to introduce the dynamic characteristics of the inner closed-loop control system into outer dynamic model of slurry concentration.We put forward a double-rate intelligent switching control algorithm for MSTP combined with one-step optimal PI control with unmodeled dynamics compensation,fuzzy switching control and switching control of based on rule reasoning.When the model parameters of the controlled object change randomly,in this paper,a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as the combination of known previous sample unmodeled dynamics and its changing rate.In the proposed controller design,two compensation signals are constructed and added onto the control signal obtained from the linear deterministic model based feedback control design.Such two compensation signals aim at eliminating the effects of the previous sample unmodeled dynamics and tracking error,respectively.And the proposed controller is used to control both loops of the cascade system.The stability and convergence of the proposed method are analyzed as well.(3)Experimental researches on the hardware-in-the-loop systemThe simulated experiment on the hardware-in-the-loop system of MSTP with actual data from industrial area proves the effectiveness of the double-rate intelligent switching control method we proposed.When the model parameters of the process change randomly,it is difficult for the above method to guarantee the control target.With the compensation signal based dual rate adaptive controller,the underflow slurry density,underflow slurry flow-rate and the changing rate of the underflow slurry flow-rate can be controlled well inside their targeted ranges when the system is subj ected to unknown variations of its parameters.