【PID优化】基于海鸥算法PID控制器优化设计含Matlab源码(pid参数优化)

1 内容介绍

PID控制器广泛应用于自动控制,电子等领域,其参数的合理性是衡量系统性能指标的关键因素.引入海鸥优化算法优化PID控制器的参数,与传统的寻优方法相比可提高控制器的稳定性和动态特性.

2 部分代码

function[Score,Position,Convergence]=SOA(Search_Agents,Max_iterations,Lower_bound,Upper_bound,dimension,objective)

Position=zeros(1,dimension);

Score=inf;

Positions=init(Search_Agents,dimension,Upper_bound,Lower_bound);

Convergence=zeros(1,Max_iterations);

l=0;

while l<Max_iterations

for i=1:size(Positions,1)

Flag4Upper_bound=Positions(i,:)>Upper_bound;

Flag4Lower_bound=Positions(i,:)<Lower_bound;

Positions(i,:)=(Positions(i,:).*(~(Flag4Upper_bound+Flag4Lower_bound)))+Upper_bound.*Flag4Upper_bound+Lower_bound.*Flag4Lower_bound;

fitness=objective(Positions(i,:));

if fitness<Score

Score=fitness;

Position=Positions(i,:);

end

end

Fc=2-l*((2)/Max_iterations);

for i=1:size(Positions,1)

for j=1:size(Positions,2)

r1=rand();

r2=rand();

A1=2*Fc*r1-Fc;

C1=2*r2;

b=1;

ll=(Fc-1)*rand()+1;

D_alphs=Fc*Positions(i,j)+A1*((Position(j)-Positions(i,j)));

X1=D_alphs*exp(b.*ll).*cos(ll.*2*pi)+Position(j);

Positions(i,j)=X1;

end

end

l=l+1;

Convergence(l)=Score;

end

3 运行结果

4 参考文献

[1]许乐, 莫愿斌, 卢彦越. 基于改进海鸥优化算法的PID控制器参数优化[J]. 机床与液压, 2021, 49(16):7.

部分理论引用网络文献，若有侵权联系博主删除。