Adaptive Swarm Fuzzy Logic Controller of Multi-Joint Lower Limb Assistive Robot

The idea of developing a multi-joint rehabilitation robot is to satisfy the demands for recovery lower limb functionality in hemiplegic impairments and assist physiotherapists with their therapy plans. This work aims at implement Lyapunov Adaptive Swarm-Fuzzy Logic Control (LASFC) strategy 4-degree freedom (4-DoF) Lower Limb Assistive Robot (LLAR) application, which control law an integration swarm-fuzzy logic (SFLC) adaptive (LAC) particle swarm optimization (PSO). controller established based on sliding filtered steady-state error SFLC. Its parameters are tuned by using PSO mathematical model LLAR. fuzzy defuzzification membership set real-time system. LAC determined stability analysis system choose controller’s observation system’s output reference. implemented LLAR SFLC adjust input voltage joints. compared genetic algorithm (GA) statistically. In addition, trajectory tracking proposed each joint separately. experiment revealed that LASFC has superior performance other two methods tracking. For example, average left hip 53.57% 68% than LAC, respectively. By statistical analysis, it can be ascertained performed efficiently