## 1 Introduction  
Soft actuators have grown in popularity among researchers and even in the industry over the years [1]. Manufacturing, manipulation, gripping, human-machine interaction, locomotion, and many other applications are covered by soft actuators [2]. This is due to the benefits they have over-rigid actuators. Soft actuators are more compliant, less expensive to produce, can be used in structured and unstructured situations [3], are lightweight, feature an increased power-to-weight ratio, and are easier to access than their counterparts [4]. McKibben muscle, balloon type [5, 6], elastomeric-based [7, 8], and many other approaches have been developed for the construction of soft actuators. McKibben muscle is a standard Pneumic Muscle (PM) with an elastic cylinder tube and a double helical braid draped on the outside that is commonly used in current soft rehabilitation robots [9]. McKibben muscle has gained popularity due to its practical properties, including large contraction strains, high blocked forces, and short response times [10]. Soft actuators can generate a variety of movements, including bending [11], rotary [12], contraction, expansion [13], and have been studied and fabricated. Soft actuators have demonstrated execution tasks such as grasping and gripping objects [14], and generating various crawling and gait movements [15]. [PERSON]'s article focuses on a soft actuator that generates a rotary motion, where the soft actuator's expansion and contraction produce clockwise and anti-clockwise rotary motions that are linked to a joint with an antagonist and agonist pair. [PERSON] et al. used hydraulically amplified self-healing electrostatic (HASEL) actuators in a system, with each foldable HASEL actuator producing an extraction and contraction motion [16]. Despite the benefits, the nonlinearity of soft actuators poses challenges in modelling, controlling, and achieving fast response times [17]. Because of the system's nonlinearity, open-loop systems are not suitable for soft actuator applications. According to [PERSON] et al. pneumatic actuator muscles with open-loop control frequently struggle with high-precision control [18]. To overcome the disadvantages, a closed-loop control system is implemented. A closed-loop control strategy developed by [PERSON] is able to demonstrate a dynamic task while improving accuracy, robustness, and the actuator's conformance to the environment [19]. The system identification technique is one of the ways to realize the idea of implementing closed-loop control through a transfer function that mimics the actual actuator. The consistency of a response system is calculated straight from its transfer feature [20]. Soft robots can collect data throughout their operational range, making them ideal for data-driven system identification techniques [21]. In this study, the system identification was performed using a black box method. The black box method for system identification can be described as a blind approach [22]. This method is gaining popularity because it does not necessitate in-depth knowledge to develop the mathematical model that replicates the actual plant [23]. The system is defined based on observed behaviour in order to build data-driven models that use input and output data from an open-loop experimental setup. Controlling a fiber-reinforced soft bending actuator (FRSBA) employs the black box method [24]. Soft actuators are popular for their nonlinearity properties [25; 26]. To overcome this downside, the implementation of controllers can overcome the nonlinearity of a soft actuator system [27; 28; 29]. A wide selection of controllers have been introduced over the years that implicate nonlinear control, linear control, and artificial intelligence methods, for instance, PID [30; 31], Model Predictive Control (MCP) [32; 33], Sliding Mode Control (SMC) [34; 35], and adaptive control [36; 37]. This study aims to develop a real-time position model for a fiber braided bending actuator (FBBA) developed by [PERSON]. [PERSON] et al.