Dynamic Economic Performance Optimization and Control Integrated Design Method for Non-Gaussian Systems
A design method and performance technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem that real-time optimization does not consider dynamic characteristics, cannot guarantee the accessibility of set values, and cannot predict control action trends And other issues
Active Publication Date: 2020-10-30
TAIYUAN UNIV OF TECH
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But in fact, the set value / reference trajectory needs to be set according to the actual economic performance index, which is a movement trajectory that changes at any time, so this solution needs further consideration;
[0006] (2) Similarly, in terms of non-Gaussian stochastic control, the existing literature mainly constructs instantaneous performance indicators based on statistical information to obtain a single-step control law, which cannot predict the future control action trend, and has a certain degree of conservatism;
[0007] (3) In the traditional two-level economic process optimization of real-time optimization and model predictive control, real-time optimization does not consider the dynamic characteristics of the process, so the accessibility of the obtained set values cannot be guaranteed
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[0051] Step 1, a non-isothermal continuous stirred tankreactor (CSTR), a basic reaction from A to B, the feed to the reactor is pure A, the volume flow rate of A is F, and the temperature is T 0 +ΔT 0 , the molar concentration is C A0 +ΔC A0 . The reactor jacket is used to remove heat from the reactor. According to the law of conservation of energy, the dynamic equation of the above system is:
[0052]
[0053]
[0054] Among them, C A is the concentration of feed A, T is the reactor temperature, Q is the fluid heat, V R is the reactor volume, ΔH is the heat of reaction, k 0 and E are the exponential factors and the activation energy of the reaction. C p and q refer to the specific heat capacity and the fluid density in the reactor, respectively. y=[T,C A ],y 1 =T,y 2 =C A is the system output, u 1 =q and u 2 = F operation input, ΔC A0 and ΔT 0 is a non-Gaussian random perturbation of feed concentration and temperature.
[0055] Define the actual output...
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The invention discloses a dynamic economic performance optimization and control integrated design method for a non-Gaussian system, and belongs to the field of random system optimization control. Themethod comprises the steps: 1, building a nonlinear random system model under the non-Gaussian disturbance; 2, building a two-layer dynamic optimization control framework structure; 3, carrying out the performance index selection based on the statistical information; 4, carrying out the dynamic economic performance optimization and the design of a model prediction controller. Compared with a conventional two-layer RTO-MPC employing a steady-state model at an upper layer, the method gives full consideration to the dynamic characteristics of a process, highlights the reachability of the obtainedoptimal set track, and has greater practical engineering significance.
Description
technical field [0001] The invention specifically relates to an integrated design method of economic performance optimization and control of a system under the influence of non-Gaussian random noise, belonging to the field of random system optimization control. Background technique [0002] In practical systems, random disturbances exist widely, especially in industrial processes, such as the random factors of the temperature concentration of reactors in chemical processes. Therefore, the optimal control of stochastic systems has always been a hot issue in the field of system control. Based on the assumption of Gaussian nature of system variables, a large number of research results have been obtained by optimizing and controlling the mean and variance, and have been widely used in engineering practice. However, the actual industrial process variables are often non-Gaussian, which makes the study of non-Gaussian distributed control systems more necessary. Inspired by classi...
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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 任密蜂成婷程兰续欣莹阎高伟
Owner TAIYUAN UNIV OF TECH