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A major challenge to developing functional electrical stimulation (FES) systems for paraplegic walking and widespread acceptance of these systems is the design of a robust control strategy that provides satisfactory tracking performance. The systems need to be robust against time-varying properties of neuromusculoskeletal dynamics, day-to-day variations, subject-to-subject variations, external disturbances, and must be easily applied without requiring offline identification during different experimental sessions. Another major problem related to walker-assisted FES-activated walking concerns the high metabolic rate and upper body effort that limit the clinical applications of FES systems. In this paper, we present a novel decentralized modular control framework for robust control of walker-assisted FES-activated walking. For each muscle-joint dynamics, an independent module control is designed, and the dynamics of the plant are identified online. This process requires no prior knowledge about the dynamics of the plant to be controlled and no offline learning phase. The module is based on adaptive fuzzy terminal sliding mode control and fuzzy logic control. The module control adjusts both pulse-amplitude and pulsewidth of the stimulation signal in such a way that upper body effort is minimized and the lower extremity walking pattern lies within a defined boundary of the reference trajectory. The proposed control strategy has been evaluated on three paraplegic subjects. The results showed that accurate tracking performance and smooth walking pattern were achieved. This favorable performance was obtained without requiring offline identification, manual adjustments, and predefined ON/OFF timing of the muscles.