In order to meet the requirements of accurate and fast leg joint control of hydraulic footed robots in complex environments,the advantage of single neural network PID of being able to adjust parameters in real time was applied to the control of hydraulic legs of footed robots.On the basis of single neural network PID,the position and speed control algorithms of mechanical leg joints were 〖JP2〗added,and an improved single neural network PID was formed,then the self-〖JP〗adjustment of neuron proportional parameters and the self-tuning of PID parameters were realized,which could better adapt to the changes of internal and external parameters.So the speed and precision of the leg joints were enhanced.The experimental results show that the improved single neural network PID has a fast response speed in the leg joint control of the foot hydraulic robot.It has the advantages of small overshoot,high control precision and strong robustness.