A Gravity Search Algorithm and a Sewage Treatment Control Method Based on the Algorithm
A search algorithm and universal gravitational technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problems of water quality parameter detection lag, difficult control, large blast and aeration cost consumption, etc., to achieve optimal cost , the effect of controlling the convergence speed and speeding up the convergence speed
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Embodiment 1
[0067] A differential adaptive gravitational search algorithm, comprising the following steps:
[0068] S1. Initialize the population;
[0069] S2. Calculate the population fitness value;
[0070] S3. Calculate the inertial mass M and acceleration a of the population;
[0071] S4. Updating the individual position;
[0072] S5. Check whether the number of iterations is reached, and output the optimal value when the number of iterations is reached; if the number of iterations is not reached, repeat the steps S2, S3 and S4.
[0073] The step S4 includes bringing the formula of the gravitational search algorithm into the update formula;
[0074] The formula of the gravitational search algorithm includes:
[0075] The gravitational force between particles is:
[0076]
[0077] In the formula, G represents the gravitational constant, M 1 , M 2 Respectively represent the inertial mass of the two particles, R represents the Euclidean distance between the two particles, F rep...
Embodiment 2
[0107] A control method for sewage treatment, comprising the steps of:
[0108] S100. Set the dimension of the search space of the problem to be 2, and set the upper and lower limits of the space as follows:
[0109]
[0110] in, is the ammonia nitrogen content; COD is the chemical oxygen demand; ρ DO Dissolved oxygen; Q w is the sludge discharge
[0111] Heavy volume;
[0112] S200, population initialization;
[0113] S300. Initialize the global optimal value gbest;
[0114] S400, calculating the adaptation value and the acceleration;
[0115] S500, update speed and position;
[0116] S600. Update the global optimal particle and the individual optimal particle to obtain the global optimal solution pbest i and gbest;
[0117] S700, comparing whether the number of iterations is reached, when the number of iterations is reached, output the optimal solution, when the number of iterations is not reached, repeat the steps S300, S400, S500 and S600;
[0118] S800. Thro...
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