Research Article
Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton
Algorithm 1
Optimize SMC with GA. (Notation:
and
represent desired trajectory of hip joint and knee joint, resp.)
, Size = 30, , parameters definition | input vector , the length of optimized parameters Len = 8 | initialize population | for do | for do | for do | ; will be used for fitness | end for | end for | Selection and reproduction | sort the fitness value and obtain the sequence number index | for do | | end for | Crossover and select the probability | for do | temp = rand | If do | for do | | | end for | end if | end for | Mutation and select the probability | , temp = rand | for do | for do | if do | if do | | else | | end if | end if | end for | end for | replace old generation with new one | end for | Obtain optimal parameters |
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