| Industrial application of microwave energy in developed countries is known as "next-generation technology in21st Century" and officially defined as new microwave energy and into the new national energy strategy. Microwave heating with an explicitly "quality, efficiency, energy saving, environmental protection" feature has become the important direction of development of green metallurgy. But a stand-alone microwave power is small, difficult to continuous production, low intelligent control. Under the background of this, thermal performance and intelligent control of high-power microwave heating systems is explored, with a view to break through the restrictive industrial application of microwave heating technology bottleneck.First, large-scale multi-physical field coupled numerical simulation software COMSOL Multiphysics is used, and combined with self-programming, simulation and analysis of the thermodynamic properties of high power microwave heating system synthesized by non-coherent wave sources. Second, in this the basis, intelligent control of high power microwave heating system industrialized application is implemented by using the computational intelligence methods of fuzzy logic, neural network which is not strongly dependent on the model of controlled object, and combination of the adaptive, predictive mechanisms. The main carried out work and the made study on results is as follows:(1) Microwave heating with multi-ports is a distributed and time-varying, high-dimensional nonlinear tieself-balancing-absent process with oscillations. Adjusting power of the voltage controlled magnetron is a second-order mode.(2) Intelligent control algorithm of high-power microwave source is proposed based on adaptive Genetic Algorithm. A single microwave power source, microwave power is obtained by indirectly detecting the anode current detection of the microwave source, the use of indirect regulation of anode voltage parameters are the best way to control the microwave power. For non-coherent microwave sources, the power required to meet the size requirements under the premise put forward based on adaptive Genetic Algorithm for intelligent control algorithm for high-power microwave source of power. The algorithm uses the open loop control, the current required microwave power as optimal function, the temperature value of microwave sources and the spent time as the constraint conditions.(3) the absorption wave characteristics of dilute hydrochloric acid, diluted hydrofluoric acid, dilute sulphuric acid, dilute nitric acid and Mixed acid (HF+HNO3) is measured for provided theoretical support on process optimization and numerical simulation of high power microwave loop heating pickling titanium sheet. Simulations and analysis of the thermodynamic properties of high power microwave heating system synthesized by non-coherent wave sources is done by COMSOL Multiphysics, combined with self-programming, large-scale multi-physical field coupled numerical simulation software COMSOL Multiphysics, combined with self-programming, simulation and analysis of the thermodynamic properties of high power microwave heating system synthesized by non-coherent wave sources heating the cycle acid medium inner resonant cavity, simulating different microwave power, the initial entrance to the different temperatures, different velocity and heat pipe radius on the results of the effect of Heating temperature, and polit experimental study on microwave circulating heating acid medium.(4) A dual-quasi cascade fuzzy adaptive PID control algorithm is proposed for controlling the speed of pickling titanium of the microwave heating cycle. To study speed control on microwave cycle heating pickling titanium sheet process, a dual-quasi cascade fuzzy adaptive PID control algorithm is proposed to control the speed of microwave cycle heating pickling sheet. Simulation results show that with the actual production data, speed control system of pickling plate sheet can effectively adapt to change in the production parameters and overcome interference to ensure that the pickling liquid temperature and turbulence intensity matches the plate sheet of strip pickling speed. The results of the practical application show that temperature error came from "hot spots" is reduced to40%.(5) The dynamic neural network based adaptive direct nonlinear model prodictive contorl is designed to control an industrial microwave heating pickling cold-rolled titanium process. The identifier of the direct adaptive nonlinear model identification and the controller of the adaptive nonlinear model predictive control are designed based on series-parallel dynamic neural network training by RLS algorithm with variable incremental factor, gain and forgetting factor. This identifier and controller are used to constitute intelligent controller for adjusting the temperature of microwave heating acid. The correctness of the controller structure the convergence and feasibility of the control algorithms is tested by System simulation. For a given point tracking, model mismatch simulation results show that the controller can be implemented on the system to track and overcome the mismatch system model. The control model can be achieved to track on pickling solution concentration and temperature of a given reference and overcome the disturbance such as "hot spots ".(6) A genetic algorithm-based self-adaptive PID control algorithm by adjusting online is proposed for the industrial microwave drying deeply. Study on drying deeply selenium-enriched slag in the multi-layer rotary microwave drying equipment, a genetic algorithm-based self-adaptive PID control algorithm by adjusting online is put forward. First with five kinds of typical process models are to verify its reliability and validity of the algorithm, and then this control algorithm is applied the temperature of the multi-layer rotary microwave equipment drying deeply selenium-enriched slag. The effect of the practical application shows that the volatile amount of selenium is effectively reduce came from’’hot spots".Industrial application of the high-power microwave heating systems and its intelligent control algorithm is used to heat the acid medium, and to dry depth desiccation of selenium-enriched slag achieved very good results as fellows:(1) The traditional boiler-graphite heater is alternatived from fundamentally put an end to coal-fired bring environmental protection pressure. Also, lectric heating system vulnerable anti-corrosion performance and coal-fired boiler-graphite heat exchanger channel easy crystal plug challenges is avoided, which it is compared to the coal-fired boiler heating mixed acid media, preheat time shortened80%, reduce energy consumption about for75%, and the elimination of coal-fired boiler bring NOX, and SO2such as pollution. The continuity of pickling (continuous pickling titanium coil direct value is120million) and the efficiency of the pickling (compared with in the deep grooves pickling to improve20%) is improved. The under or over pickling of the titanium coil is avoided successfully (the first time of the pickling rate of up to15%).(2) The water content of selenium-enriched slag raw materials dehydration is about30to1%, by shortening the traditional resistance heating time consuming60-70h to2h. Moreover the recovery rate of selenium is improved to2～3%. The continuity of drying and drying efficiency is improved, labor intensity reduced, energy consumption effectively reduced, the rate of received metal improved.
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