Continuum robots (CRs) show great potential in complex environments due to their excellent deformability. For practical applications, the position control of the CRs is an important research field. The common drives of the CRs are rigid motors with mature control schemes. However, the driving force of the rigid motors is often impactive, which may cause safety concerns during interaction. Soft drives based on pneumatic soft actuators (PSAs) can provide compliant driving force for the CRs robot bodies to solve this problem, but it is necessary to comprehensively consider the control of the soft drives and the robot bodies. This article takes a CR with soft drives as the research objective, and proposes a double closed-loop adaptive position control method to achieve the endpoint position control of the CR. This CR includes a length-variable robot body with millimeter-scale diameter and pneumatic soft drives. The kinematic model of the robot body is built based on the piecewise constant curvature (PCC) method, and the static models of the soft drives are derived from the three-element model. Based on these models, we propose a double closed-loop adaptive position control method. The inner loop is used to control the displacements of the soft drives, and the outer loop combines the endpoint position control with the nonsingular fast terminal sliding mode function to adaptively control the endpoint position based on the inner loop. By Lyapunov method, we prove the convergence of the endpoint position error. The effectiveness of the proposed control method is verified through experiments.

This paper proposes efficient modeling and control methods for a continuum robot (CR) composed of a three-segment robot body (two proximal segments and a distal segment with an endpoint) and soft drives. Each segment incorporates multiple mutually exclusive magnetic spacer disks for a flexible structure, and the soft drives are designed based on pneumatic soft actuators (PSAs) to ensure operational safety. For both computational efficiency and tracking performance, an open-loop control method based on the kinematic model of the robot body is adopted to operate the two proximal segments, and a feedforward-feedback control method based on the dynamic model of the distal segment derived from the Euler-Lagrange method is proposed to control the endpoint trajectory. During the dynamic modeling process of the distal segment, the magnetic potential energy is considered additionally by simplifying the magnetic spacer disks to multiple magnetic dipoles. Moreover, the relationship between the input pressures of the soft drives and the generalized force of the dynamic model is derived from the three-element model and the principle of virtual power. Experiments demonstrate the effectiveness of the proposed modeling and control method.

Severe drill-string vibration is a significant source of drilling problems. Most existing methods for vibration recognition rely on downhole data, facing great limitations in practice. In addition, complex and changeable formations result in limited ability of single-scale features to characterize the vibration. To resolve these issues, an end-to-end vibration recognition model using only surface drilling data is proposed based on multiscale features extraction. A multiscale temporal convolutional network is developed to extract multiscale temporal features of multisensor data, enhancing the vibration representation capability to adapt to complex formations. To further improve recognition capability, the bidirectional long short-term memory network is utilized to obtain contextual linkage of multiscale features. Experiments conducted with field data have verified the efficiency of proposed method. It has achieved 97% accuracy, and outperforms existing methods. Furthermore, compared with the recognition result based on single-scale features, it has improved by 6% in accuracy. The proposed method provides automated diagnostics of drill-string vibration.

Due to the complex nonlinear behavior and external sensitivity of pneumatic soft actuators (PSAs), it is difficult to design control methods to achieve their control objectives by establishing their precise specific models. This article takes a PSA with bellow-type folds, called pneumatic bellow actuator (PBA), as the object, and proposes an adaptive nonsingular fast terminal sliding mode (NFTSM) control method with time-delay estimation (TDE) to achieve the trajectory tracking control of the PBA without relying on its specific model. The model framework of the PBA is first discussed, but the specific model is unknown, and all the unknown model information is defined as the lumped unknown dynamics. The TDE is applied to obtain the estimation of the lumped unknown dynamics using only the measured system states. Based on the estimation information, an adaptive NFTSM control method is proposed. This control method is nonsingular, continuous, adaptive, and accurate. Since the step of establishing the specific model of the PBA is omitted, and the model framework used in this article is universal for many PSAs, this control method exhibits universal applicability for controlling other PSAs that have difficulty obtaining specific models. The effectiveness is validated through stability analysis and PBA tracking experiments under different loads.

Soft manipulators have been widely developed due to their manipulation safety, design versatility, and motion dexterity. However, accurate kinematic modeling and control of soft manipulators are still challenging due to the complex nonlinear hysteresis in their motion characteristics. This article presents the fabrication of an elephant-trunk-inspired soft manipulator (ESM) using pneumatic bellows actuators (PBAs) and proposes a kinematic modeling and control method considering hysteresis. The ESM contains three soft arms and a pneumatic claw, while each soft arm consists of four PBAs connected in parallel. The forward kinematics of the ESM are modeled using the piecewise constant curvature (PCC) method. The kinematic model of the ESM consists of three parts: actuator space, configuration space, and task space. To address the inability of the PCC method to characterize the nonlinearity of soft materials, the hysteresis of the PBA in the actuator space is modeled using the Prandtl–Ishlinskii model. The inverse kinematic model of the ESM is derived from its forward kinematic model, and on this basis, a feedforward controller is developed to achieve position control of the ESM. The positional workspace of the ESM is analyzed using the Monte Carlo method. The validity of the kinematic model is verified experimentally. Position control and application experiments are conducted to demonstrate the practical application of the ESM.

For a three-link vertical underactuated manipulator (TVUM) with only one active joint, the control target is to swing up its endpoint from the straight-down equilibrium point (SDEP) and to stabilize the endpoint at the straight-up equilibrium point (SUEP) eventually. Up to now, there are few effective control strategies to achieve the above control target. In this article, we propose an effective control method based on the trajectory optimization to realize the system control target, and the main steps of this article are: 1) a continuous trajectory that consists of two segments with design parameters is planned for the actuated link, along which the actuated link can be swung up from the initial states to the final states; 2) the design parameters are optimized by using the intelligent optimization algorithm to guarantee that the states of the underactuated links are continuous at the junction. In this way, the underactuated links are also moved to their final states with the actuated link simultaneously; 3) a tracking controller is designed by using the sliding-mode method to track the trajectory with optimized design parameters, so the endpoint is swung up from the SDEP to the SUEP directly; and 4) a stabilizing controller is further devised through the LQR method to keep the endpoint being stable at the SUEP. Finally, simulation results show that the proposed control method achieves the swing-up and stable control target of the system, and the control performance of the proposed method is superior than that of the existing control methods through the comparisons.

Complicated geological environments lead to a high risk of drilling incidents. Early warning of loss and kick for the drilling process is essential to ensure process safety. On account of the nonlinear and temporal correlation of drilling parameters, an early warning method for loss and kick based on sparse autoencoder with multivariate time series is proposed. The sparse autoencoder is utilized for multivariate time series abnormality detection of the drilling process. Abnormal drilling parameter isolation is performed through contribution analysis. Reconstruction analysis and time series segmentation approaches are integrated for abnormal time series trend evaluation. The characteristic of drilling parameters under normal operation learned by the sparse autoencoder and the property of the original time series are taken into account. The final early warning result can be obtained through expert rules based on the trend evaluation result. Case studies are presented based on the data from an actual drilling project. The experiment result shows the effectiveness of the proposed method.

When a flexible link manipulator lacks a joint motor, how to use the remaining motors to achieve the control objective is a challenge, and the research in this direction is limited. This article presents a tip position control and vibration suppression approach for a planar two-link rigid-flexible (TLRF) underactuated manipulator with a passive first joint. First, we establish a dynamic model of the system by using the assumed mode method (AMM) and the Lagrangian modeling method. Then, we obtain the dynamic coupling relationship of the two links based on the dynamic model. According to this dynamic coupling relationship, we find that the passive rigid link can be controlled indirectly by controlling the active flexible link. Thus, we calculate the target angles of the two links by using the inverse kinematic method and design a controller for the active flexible link to stabilize it at its target angle and to suppress its vibration. Next, we optimize the parameters of this controller by using the genetic algorithm (GA). GA helps us simultaneously stabilize the passive rigid link at its target angle while realizing the control objective of the active flexible link. The simulation results demonstrate the effectiveness of the proposed control approach.

This article deals with an uncertain two-link rigid-flexible manipulator with vibration amplitude constraint, intending to achieve its position control via motion planning and adaptive tracking approach. In motion planning, the motion trajectories for the two links of the manipulator are planned based on virtual damping and online trajectories correction techniques. The planned trajectories can not only guarantee that the two links can reach their desired angles, but also have the ability to suppress vibration, which can be adjusted to meet the vibration amplitude constraint by limiting the parameters of the planned trajectories. Then, the adaptive tracking controller is designed using the radial basis function neural network and the sliding mode control technique. The developed controller makes the two links of the manipulator track the planned trajectories under the uncertainties including unmodeled dynamics, parameter perturbations, and persistent external disturbances acting on the joint motors. The simulation results verify the effectiveness of the proposed control strategy and also demonstrate the superior performance of the motion planning and the tracking controller.

The control objective of the vertical plane underactuated manipulator (VPUM) is generally to swing up the end point (EP) from the vertical down equilibrium point (VDEP) to the vertical up equilibrium point (VUEP), and finally, to stabilize it at the VUEP. The zone control methods are usually used to achieve this control objective, but the problem of these methods is that they cannot find a unified zone range, and it is easy to appear singularity in the motion process. In this article, for two-link VPUMs, we propose a control strategy based on trajectory planning and optimization, which does not need to divide the zone range, avoids the singularity problem, and can achieve the control objective quickly and smoothly. We design the trajectory by using the time scale method for the active link according to the initial and target states. Then, we obtain the trajectory parameters by employing differential evolution algorithm to ensure that the passive link can also move from the initial states to the target states simultaneously. We design a sliding mode tracking controller to make the active link move along the designed trajectory, so the EP is moved to VUEP. Meantime, we design a sliding mode stabilization controller to ensure that the system is stable at VUEP. Finally, the universality and robustness of the proposed method are proved by simulations.

The safe and efficient operation of geological drilling systems is critically dependent on proper process monitoring. A monitoring model based on probabilistic principal component analysis is presented to deeply exploit performance feature information hidden among the process data in this paper. First, the offline monitoring model is established with historical process data collected from different sources to reveal different characteristics, and the monitoring statistics as a benchmark are obtained. Then, actual operating data are introduced to the established model to realize online monitoring. Finally, the monitoring effect is discussed, and the causes of inefficient drilling are tracked. The experimental results indicate that the proposed method can effectively monitor the operating performance of the drilling process.

Complicated geological environments lead to a high risk of drilling incidents. Incident early warning for drilling process is in demand for industry field. An incident early warning method for loss and kick based on sparse autoencoder and decision fusion is proposed in this paper. Sparse autoencoder is employed to detect the abnormality of the drilling parameter time series. Mann-Kendall trend test approach is performed to extract the trend of the time series that is detected as abnormal. The abnormality detection and trend extraction results of each drilling parameter are fused to get the final incident early warning result. Experiments are executed with the actual data collected from a practical drilling process. The experiment results indicate the effectiveness of the proposed method.

Single-link flexible-joint manipulator (FJM) is a kind of time-varying nonlinear system with underactuated characteristics. This paper takes the uncertain single-link FJM (USLFJM) as the object, and presents a novel robust control approach based on equivalent input disturbance (EID) method for motion control (i.e., position control and trajectory tracking control) of the USLFJM. Based on the uncertain dynamic model and desired target of this system, an error system is constructed. The error system is considered as a linear system with a nonlinear virtual disturbance. The motion control objective of the USLFJM can be realized by globally asymptotically stabilizing this linear system and compensating the influence of the nonlinear virtual disturbance. Then, an EID-based control system is designed to realize this control objective. Only position measurements are utilized in this paper, and the stability of the control system is proved. The simulation results are presented to illustrate the validity and the robustness of the proposed control method.

This paper develops a quick and effective continuous state feedback control strategy based on intelligent optimization for a planar three-link passive–active–active (PAA) underactuated system with first-order nonholonomic characteristic. We analyze the integral characteristic of the system and find the passive link will be stabilized at different angle when the two active links of the system are controlled to different angles. Therefore, we design a set of continuous state feedback controllers based on the control targets of the two active links, and then we optimize the target angles of all links and the design parameters of the above controllers by employing intelligent optimization algorithm. In this way, the system can be stabilized at the target point by using these controllers with optimized parameters. Finally, the simulation results demonstrate that the continuous control strategy based on intelligent optimization may make the planar PAA underactuated system be stabilized at any target point from any initial point.

This paper presents a control strategy based on model reduction and online intelligent calculation for a planar n-link underactuated manipulator with a passive first joint (PAn-1 for short) to realize its control objective, which is to move its end-point from an initial position to a target position. First, two active links of the planar PAn-1 manipulator are chosen to be the active links of a planar virtual passive-active-active (PAA) manipulator, which guarantees that the geometric reachable range of the planar virtual PAA manipulator is the same as that of the planar PAn-1 manipulator. The planar PAn-1 manipulator is reduced to the planar virtual PAA manipulator by keeping the states of two active links in their initial values and controlling the states of the remaining n - 3 active links to zero. Then, the planar virtual PAA manipulator is equivalent to two planar virtual Acrobots by adopting two-stage control method. Based on two sets of angle constraint relationships corresponding to two planar virtual Acrobots, an online differential evolution algorithm is employed to obtain all link target angles of the planar virtual PAA manipulator. Next, two Lyapunov functions, each of which is constructed based on the active link angle of one planar virtual Acrobot, are used to design controllers to realize the system control objective. Finally, Simulation results of a planar PAA-active manipulator demonstrate the effectiveness of the proposed control strategy.

This paper presents a trajectory tracking control strategy based on the finite element method for a planar three-link underactuated manipulator with a passive third joint. From the mechanical structure, the manipulator can be thought of as composed of two parts. The first part is the first link of the manipulator, which is a single link manipulator system. The second part consists of the remaining two links, which can be seen as a plananr Pendubot. First, a finite element model of the planar Pendubot is built by using COMSOL, and the coupling relationship between its active link and its passive link is analyzed. Then, two servo controllers (A and B) with the same structure are designed for two active links of the manipulator, respectively. The servo controller A is directly applied to control the angular velocity of the first link of the manipulator rotating with a constant speed, which makes the end-point of the manipulator move along the trajectory direction. Next, a fuzzy system is designed based on the coupling relationship of the planar Pendubot to calculate the target angular velocity of the second link of the manipulator according to the tracking error and its change rate. The servo controller B is applied to control the angular velocity of the second link of the manipulator, which makes the tracking error converge to zero. Finally, Simulation results demonstrate the effectiveness and the robustness of the proposed control strategy.

This paper presents a unified treatment of the motion control of underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control laws are designed for each. First, a control law based on a weak-control Lyapunov function (WCLF) is employed to increase the energy of and control the posture of the actuated link in the swing-up area. Next, one parameter of the WCLF is chosen to be a nonlinear function of the state to avoid singularities. Then, another parameter of the control law is adjusted based on the state to improve the control performance. Finally, an optimal control law is designed for the attractive area. Stability is guaranteed in the swing-up area by the use of a WCLF based on LaSalle's invariance principle. Moreover, the global stability of the control system is guaranteed by integrating the WCLF and a nonsmooth Lyapunov function.

This paper presents a novel control strategy based on a non-smooth Lyapunov function to guarantee the stability of the system in the whole motion space. Three control laws that are derived based on three Lyapunov functions are applied successively in three stages of motion control to achieve a suitable posture and increase the energy so as to make the acrobot move into the area around the unstable inverted equilibrium position, and to stabilize it at that position. These three Lyapunov functions are combined into one non-smooth function, which theoretically guarantees the stability of the acrobot in the whole motion space. Simulation results have demonstrated the validity of this strategy

This paper presents a comprehensive unified control strategy for underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control laws are designed for each. First, a control law based on a weak control Lyapunov function (WCLF) is employed to increase the energy and control the posture of the actuated link in the swing-up area. Next, one of the parameters of the WCLF is chosen to be a nonlinear function of the state so as to avoid any singularities. Then, another parameter in the control law is adjusted based on the state to improve the control performance. Stability is guaranteed in the swing-up area by the use of a WCLF based on the LaSalle invariant theorem. Finally, the global stability of the control system is guaranteed by the use of a non-smooth Lyapunov function integrated with a minimum-switching strategy. Simulation results for a pendubot and an acrobot show this control scheme to be very effective