# Control-Based 4D Printing: Adaptive 4D-Printed Systems
## 2 Controllable 4D-Printed Systems  
One of the early representations of controllable 4D-printed systems was brought about by embedding off-the-shelf flexible sensors into 3D-printed fluidic actuators [7]. Subsequently, conductive hydrogel inks were developed as tactile and force sensors to measure the external load on a 4D-printed pneumatic actuator [33]. The flexible sensors were designed based on the resistive principle and were utilized to measure and control the bending angle of a 4D-printed pneumatic actuator [34]. Ionic polymer-metal composites (IPMCs) have also been utilized as both sensors and actuators in 4D-printed systems [35; 36; 37]. A controllable 4D-printed paper was recently fabricated by a composite polylactic acid (PLA)-graphene filament. The system used a resistive heating element as an actuator and electric potential as a sensor [38]. There have been some advances in the application of controllable 4D-printed systems in the biomedical sector. A 4D-printed system was developed to measure real-time blood pressure and the release of a drug in a controlled manner [39]. A 4D-printed artificial skin was made of thermo-responsive ionic hydrogel which used the capacitive principle for sensing and fiber enlargement as actuation [40]. A combination of poly (D-lactide) (PDLA) and polycaprolactone (PCL) was used to 4D print a biodegradable and biocompatible smart stent [41]. The PCL was used to fabricate an airway stent using the melt streetolithography (SLA) technique. The stent shape was designed according to a patient's tracheebronchial track and delivered in its temporary state. An educated approach for the PCL molecule weight selection was used to control the shape-memory behavior of PCL including the strain fixity rate and the strain recovery rate. Once it was implanted the stent was thermally actuated and recovered to its original shape (set shape memory) providing structural support and preventing the trachea from collapsing. In tissue engineering, the mechanical stimulus of cell-seeded scaffolds plays a key role in cell proliferation and diffraction processes [42], in which a bioreactor is required to apply the mechanical forces. However, by the 4D printing of shape-memory polymers (SMPs) based scaffold, the mechanical forces are applied by the time-controlled deformation of SMPs due to an external stimulus such as thermal radiation. The effectiveness of this concept was investigated using shape-memory polyurethane to fabricate 3D scaffolds [22]. It was shown that such a technique has a clear effect on cell alignment and could be a robust alternative to bioreactors in tissue engineering. The controllable 4D-printed system found a novel application in soft robotics manufacturing through an embedded 3D-printed sensor [43]: a liquid conductor printed as tactile sensor channels to measure the amplitude and location of external forces. Machine-learning (ML)-based control algorithms were developed and applied to enhance the autonomy of 4D-printed soft robots in the assigned tasks [44]. A fusion of different sensors was co-printed in a single step to enable 4D-printed systems with the adaptation to external stimuli. To achieve this, a composite of thermoplastic polyurethane and carbon black was printed by the fused deposition modeling (FDM) as pressure and position sensors operated based on a piezo-resistive principle in a 4D-printed pneumatic actuator [44]. Not all the 4D-printed systems developed thus far have relied on sensory feedback information to function. There have been recent developments of 4D-printed compliant mechanisms, including bi-stable and multi-stable designs, utilizing passive sensing instead of integrated sensors [12; 45; 46; 47]. These prototypes use stimuli-responsive materials, including liquid crystalline elastomers, conductive polymers and hydrogels and shape-memory polymers (SMPs), [3; 6; 48; 49; 50; 51; 52; 53; 54; 55] to react to environmental stimuli changes with a higher sensitivity and response time compared to the integrated sensor systems [34; 56; 57].