Optimal Fuzzy PID Controller Based On Ant Colony System Algorithm And Its Application To CIP-I Intelligent Artifical Leg

Intelligent bionic artificial leg (IBAL) is a kind of electromechanicaldevice, which is used for leg-amputees. It has many excellent featurescompared with the conventional mechanical legs. It can imitate themovement way of human healthy leg and its walking speed can changenaturally with the change of leg-amputee's walking speed. The IBALobtains the gait information of the leg-amputee using a sensor systeminstalled in the artificial leg, and the information is sent to amicroprocessor. Then, the microprocessor adjusts a needle valve in thecylinder according to the gait information. Through changing the openingof the valve, the speed of the artificial leg can be adjusted to implementaccurately tracking the other healthy leg in real-time. Currently, manydeveloped countries are focusing on this research in medical field.The intelligent artificial legs developed several years ago in someforeign countries have following shortages. The first is that the controlstrategy in the controllers is too simple, which can't give attention to boththe high-speed and the accuracy in the system respond. Additionally, themicroprocessors used in these legs mainly are C51 single chip, which hasworse function extendability and higher power consumption, and whoserunning speed cannot satisfy the requirement of many advanced controlalgorithms. We developed an innovative intelligent bionic artificial leg,named CIP-I Leg. Aimed at the above shortages, in the design of CIP-ILeg's control system, the following improvements were made. First, anovel design method for optimal fuzzy PID controller, based on the antcolony system (ACS) algorithm and fuzzy logic control, is proposedwhich is suitable to various kinds of control objects. The core of thismethod is generating the optimal fuzzy control rules for a given controlobject by taking the ITAE criterion as the system performance index andusing the ACS algorithm to optimize the input scaling factors and outputscaling factors of the fuzzy controller. The simulation experimentsdemonstrated that the optimal fuzzy PID controller had the minimumITAE value, compared with other three optimal PID controllers, which indicates that the optimal fuzzy PID controller has better transient-stateand steady-state performance. These improvements of control strategyeffectively raised the respond speed and accuracy of walking speedadjustment. Secondly, in the design of the hardware circuits,MSP430F149 microprocessor produced by Texas Instruments (TI) wasadopted as the CPU of the controller. MSP430F149 is a kind ofmicroprocessor with ultra-low-power and highly integrated degree, andits running speed is faster than C51 single chip. MSP430F149 cancomplete many advanced control algorithms on line. Furthermore, usingthe abundant chip resources on MSP430F149, we designed everymodules of the intelligent bionic artificial leg control system.After the hardware circuits designed and made, of the intelligentcontroller software written debugged, and the control algorithm simulate,debugged and ran, it was concluded that the controller of intelligentartificial leg designed in this research has better intelligent behavior,response speed, and accuracy.