【PID优化】基于头脑风暴算法PID控制器优化设计含Matlab源码

本文链接：https://blog.youkuaiyun.com/matlab_dingdang/article/details/126218919

本文探讨了使用头脑风暴算法优化PID控制器参数，以实现更快的响应时间、更高的控制精度和更强的鲁棒性。通过MATLAB仿真，展示了算法在不同条件下的性能，并提供了最佳和最差性能的比较，为PID控制系统的设计提供了参考。

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1 内容介绍

PID参数优化对PID控制性能起着决定性作用,针对PID参数寻优问题,提出运用一种头脑风暴算法.头脑风暴算法优化参数使系统具备更短的响应时间,更高的系统控制精度以及更好的鲁棒性,为PID控制系统的参数整定提供了参考.

2 仿真代码

clc

clear

%bso test

tic

funStr = 'sphere10D5C'; %output worksheet name

funName = @sphere; % fitness function name

rang_l = -100; % left of dynamic range sphere

rang_r = 100; % right of dynamic range

%n_p = 500; % population size

%n_d = 2; % dimension

%n_c = 5; % number of clusters

%rang_l = -100; % left of dynamic range

%rang_r = 100; % right of dynamic range

%max_iteration = 50; % maximal number of iterations

warning off all

n_p = 100; % population size

n_d = 300; % dimension

% n_c = 2; % number of clusters

% funStr = 'sphere10D5C'; %output worksheet name

% funName = @sphere; % fitness function name

% rang_l = -100; % left of dynamic range sphere

% rang_r = 100; % right of dynamic range

% funStr = 'Minima10D5C'; %output worksheet name

% funName = @Minima; % fitness function name

% rang_l = -5; % left of dynamic range rastrigin

% rang_r = 5; % right of dynamic range

% funStr = 'Griewangk10D5C'; %output worksheet name

% funName = @Griewangk; % fitness function name

% rang_l = -50; % left of dynamic range rastrigin

% rang_r = 50; % right of dynamic range

% funName = @ackley_path; % fitness function name

% rang_l = -5; % left of dynamic range rastrigin

% rang_r = 5; % right of dynamic range

% minpts = 10;

max_iteration = 2000; % maximal number of iterations

XX=1;

%P = 0;

n_c = 2;

% P = 0.6;

% for P = 0:0.1:1

for idx = 1:30 % run times

fit = bso2(funName,n_p,n_d,n_c,rang_l,rang_r,max_iteration);

%run BSO one time

if idx <27

str = native2unicode(idx + 64);

else % assume idx <53

str =['A',native2unicode(idx + 38)];

end

xlswrite('bso.xls',fit,funStr, [str,'1']);

% output best fitness over generation to EXCEL worksheet for each BSO run

['run', num2str(idx)]

opt(idx,:)=fit; %可以把列换成行 fit为一列数据

% plot(x,opt(1,:)

end

opt;

format short g

best_value = min(opt(:,max_iteration))

worst_value = max(opt(:,max_iteration))

[ln col]=size(opt);

out_put(XX,:)=sum(opt)/ln; %每一列的均值

format short g

m_value = min(out_put(XX,:))

z = 0;

for idx = 1:30

z = z+(opt(idx,max_iteration)-m_value)^2;

end

SD = z/29

XX=XX+1

% end

% save UUB out_put(n_c,:);

% plot(out_put);

% end

% save UUB out_put(n_c,:);

% plot(opt);

figure(1)

save UUB out_put;

x=1:max_iteration;

% plot(x,out_put(1,:),'b',x,out_put(2,:),'g',x,out_put(3,:),'r',x,out_put(4,:),'c',x,out_put(5,:),'m',x,out_put(6,:),'y',x,out_put(7,:),'k',x,out_put(8,:),'b--',x,out_put(9,:),'g-.',);

% legend('k=2：蓝色','k=3：绿色','k=4：红色','k=5：青色','k=6：品红色','k=7：黄色','k=8：黑色','k=9','k=10');

plot(x,out_put(1,:))%,'b',x,out_put(2,:),'g',x,out_put(3,:),'r',x,out_put(4,:),'c',x,out_put(5,:),'m',x,out_put(6,:),'y',x,out_put(7,:),'k',x,out_put(8,:),'b--',x,out_put(9,:),'g-.',x,out_put(10,:),'r:',x,out_put(11,:),'c-.');

% legend('P=0','P=0.1','P=0.2','P=0.3','P=0.4','P=0.5','P=0.6','P=0.7','P=0.8','P=0.9','P=1');

toc

img =gcf; %获取当前画图的句柄

print(img, '-dpng', '-r600', './运行结果.png') %即可得到对应格式和期望dpi的图像