Enhanced control strategies for lower limb rehabilitation robots: a comparative study of MRAC, PID‐ZN, and MRAC‐PSO controllers

<jats:p>Wearable robots for rehabilitation have dramatically advanced the medical field regarding helping patients suffering from lower limb impairments to regain mobility and ameliorate their range of motion (ROM). However, to further optimize control mechanisms within these robots, conventional methods cannot adapt to the different needs of patients in their walking, and the complex patterns of human gait. As a result of such limitations, the functionality of ROM training is constricted. To cope with these problems, the present article will design and validate an adaptive control system for the lower limbs with Particle Swarm Optimization (PSO): Model Reference Adaptive Control (MRAC)‐PSO. By introducing the adaptation mechanism of MRAC‐PSO, as well as its capabilities in optimization, this research aims to further improve the adaptability and effectiveness in ROM training to provide a better rehabilitation process for the patient. Moreover, the performance of the MRAC‐PSO controller is compared with that of a traditional MRAC system and a classical Proportional‐Integral‐Derivative controller optimized via the Ziegler–Nichols (Z–N) method. This comparison is performed to underline the benefits and possible improvements brought by the adaptive and optimized control approach. The novelty of this article lies in the first systematic integration of PSO optimization with MRAC for wearable lower limb rehabilitation (WLLR) ROM training, achieving significant performance improvements over conventional methods: 89% faster risetime and 98.9% lower steady‐state error (SSE) compared to PID‐ZN control. This research advances wearable robotics by demonstrating that the synergy between adaptive control and bioinspired optimization can substantially improve rehabilitation robot performance, safety, and clinical viability. The synthesis and overcoming analysis of MRAC‐PSO, conventional MRAC, and PID‐ZN controllers are carried out with the aim to overcome existing ROM training deficiencies, making the rehabilitation strategy more adaptable and effective. In this regard, this research outcome would likely open ways for further development in rehabilitation technology to improve the living standard of people suffering from lower limb disabilities.</jats:p>