An evaluation of closed-loop control options for continuum manipulators

Fast inverse kinematics (IK) algorithm is significant for real-time precise motion control for continuum and soft manipulators. In this paper, we studied an explicit expression of a two-segment continuum manipulator based on constant curvature assumptions and discussed the existence of the IK solutions. Utilizing the pseudo-rigid-body method, we contrast this model with the traditional six-axis rigid industrial robot arm, revealing that two-segment extensible continuum manipulators exhibit limited rotation angles around the directional vector of their tips, thereby showcasing reduced dexterity. By pre-constraining five degrees-of-freedom (DOF) and addressing the definition of the remaining DOF, we streamline the IK-solving process, resulting in minimal computational overhead suitable for a wide range of applications. This model promises a robust and real-time approach for controlling two-segment extensible continuum manipulators, enhancing their operational efficiency and effectiveness.

In this paper, model-based precision force and position control of an ionic polymer metal composite (IPMC) is presented. A 23.8 mm × 3.4 mm × 0.16 mm IPMC strip was used as an actuator in a cantilever configuration. Open-loop force and position responses of an IPMC are not repeatable, and hence closed-loop precision control is of critical importance to ensure proper functioning, repeat-ability and reliability. After feedback controllers were designed and implemented with empirically obtained fourth-order plant transfer functions, the overshoot decreased from 460 to 2.8 per cent and the settling time was reduced from 37.5 to 3.22 s in force control. In position control the overshoot decreased from 333 to 20.3 per cent and the settling time was reduced from 21.5 to 2.56 s. Microscale precision force and position control capabilities of the IPMC actuator were also demonstrated experimentally. An 8 μN force resolution was achieved with a force noise of 0.5μN r.m.s., and the position resolution was 6 μm with a position noise of 2.5 μm r.m.s. The maximum force and tip displacement achieved with the IPMC actuator under closed-loop control were 2 mN and 5 mm respectively. The IPMC actuator could follow various commanded force and position trajectories such as sinusoidal and trapezoidal position profiles, and a velocity profile with a 3 mm/s maximum velocity. A novel hybrid force and position control strategy demonstrated its utility in practical micromanipulalion applications where the actuator force must be limited to prevent damaging micro-objects. High-precision control of the IPMC at low force level proved its potential for micromanufacturing and micromanipulation applications such as robotic and biomedical microgrippers.

Perception is an essential component of an intelligent autonomous system. However, the traditional sensors used in robotics and industrial are limited when considering high mobility, wide distribution, and possible wireless operation of the sensors in sensor networks. The self-powered sensing solves the most shackling issue in the current sensing field, thus enabling many previously unattainable application scenarios. In this paper, a novel variable-length continuum manipulator with self-powered sensors is designed, and an adaptive capture control scheme based on deep learning prediction is proposed for the envelope grasp of a fixed cylinder target and the hook grasp of a ring target moving in a small range. First, adaptive capture parameters of the manipulator are generated according to a target’s size and position. Then, deep neural networks are utilized to accurately predict the bending angle of the manipulator with a large displacement motion at the tip of the continuum manipulator. Finally, based on the feedback data from the driving motor’s built-in angular velocity sensor on the continuum manipulator, a set of capture criteria are presented to identify the envelope and capture states of the target. The capture experimental results on a prototype reveal that the generated parameters highly match the targets. The prediction method’s accuracy is higher than that of conventional feedforward neural networks. The capture criteria based on the feedback data from driving motor’s built-in angular velocity sensor can correctly identify the target capture states. In additional, the future research of the adaptive capture control based on self-powered sensors is discussed.

Continuum manipulators coupled with magnetic actuation have great potential as steerable instruments for diverse surgical applications. They can be maneuvered inside the human body to reach difficult-to-access surgical sites with contactless actuation. This paper presents a new design of a compliant continuum manipulator of diameter 3 mm and length 70 mm, capable of spatial bending under magnetic actuation. A quasi-static model is developed to estimate the 3D motion of the manipulator. Experiments report an overall mean error in whole shape estimation of the manipulator between the model and the ground truth of 1.7 mm and 4.8 mm, when suspended vertically and horizontally from its base, respectively. Furthermore, fiber Bragg grating (FBG) sensors are integrated with the manipulator to enable shape sensing. Closed-loop control is demonstrated to trace different trajectories with the tip of the manipulator. A square trajectory and a straight line trajectory are generated with an average error in tip position of 4.1 mm between the desired and estimated positions. The potential of the manipulator as a steerable instrument is validated by maneuvering it inside phantoms of a bifurcating arterial system and a heart with visual guidance from a miniature camera.

A two-wheeled self-balancing robot that works on the principle of inverted pendulum theory is most commonly used in control systems as an exemplar for comparing various control and optimization algorithms. This nonlinear dynamic system has gained much interest among researchers and engineers and the main aim is to stabilize this system with minimum deviation about any desired axis. As this system is affected by external disturbances and measured parametric errors, the need for the implementation of controllers has become crucial. Hardware and software implementation form the basis of the system design. The proposed work aims at the implementation of a PID controller for the successful working of the two-wheeled self-balancing robot driven by stepper motors. The closed-loop controller’s parameters have been optimized by using pole placement method. Besides, the response of the system under the fuzzy controller, created using Mamdani fuzzy interface engine in Simulink, has been illustrated.

This study aims to develop a leveling position control of an active PWM-controlled pneumatic isolation table system. A novel concept using parallel dual-on/off valves with PWM control signals is implemented to realize active control and to improve the conventional pneumatic isolation table that supported by four pneumatic cushion isolators. In this study, the cushion isolators are not only passive vibration isolation devices, but also pneumatic actuators in active position control. Four independent closed-loop position feedback control system are designed and implemented for the four axial isolators. In this study, on/off valves are used, and PWM is realized by software. Therefore, additional hardware circuit is not required to implement PWM and not only cost down but also reach control precision of demand. In the controller design, the Fourier series-based adaptive sliding-mode controller with H∞ tracking performance is used to deal with the uncertainty and time-varying problems of pneumatic system. Finally, the experiments on the pneumatic isolation table system for synchronous position and trajectory tracking control, including no-load and loading conditions, and synchronous position control with master-slave method, are implemented in order to verify that the controller for each cushion isolator can realize good position and trajectory tracking performance.

In this study, an XYθ position sensor is designed/proposed to realize the precise control of the XYθ position of a holonomic inchworm robot in the centimeter to submicrometer range using four optical encoders. The sensor was designed to be sufficiently compact for mounting on a centimeter-sized robot for closed-loop control. To simultaneously measure the XYθ displacements, we designed an integrated two-degrees-of-freedom scale for the four encoders. We also derived a calibration equation to decrease the crosstalk errors among the XYθ axes. To investigate the feasibility of this approach, we placed the scale as a measurement target for a holonomic robot. We demonstrated closed-loop sequence control of a star-shaped trajectory for multiple-step motion in the centimeter to micrometer range. We also demonstrated simultaneous three-axis proportional–integral–derivative control for one-step motion in the micrometer to sub-micrometer range. The close-up trajectories were examined to determine the detailed behavior with sub-micrometer and sub-millidegree resolutions in the MHz measurement cycle. This study is an important step toward wide-range flexible control of precise holonomic robots for various applications in which multiple tools work precisely within the limited space of instruments and microscopes.

The aim of this paper is to investigate the problem of high-precision position control in Switched Reluctance Motor (SRM) drives. Proportional-differential (PD) controller and Advanced gain scheduling proportional-integral (PI) controllers are adopted for position and speed controls, respectively. The control scheme used for the SRM drive operates over a wide speed range and supports the four quadrant operation and also provides low torque ripple at an acceptable level. The proposed four quadrant control scheme is based on the average torque control method. Low torque ripple is achieved by controlling the turn-on and turn-off angles through simple formulas so as to minimize the pulsations of the torque at the commutation intervals. The fine tuned PI controller parameters are online determined according to the load torque and speed of the rotor. In order to provide precise position control, a gain scheduling technique is adopted in the speed control design. A low-pass filter is included in the position controller to improve the set-point tracking and to prevent the impulse of the control signal. The SRM drive is designed and implemented in MATLAB/Simulink environment at different rotor positions and several simulation results are presented to validate the feasibility of the proposed control scheme.

Model-based precision position and force control of SMA actuators with a clamping application

Due to the excessive degree of freedom of the space flexible manipulator, we can hardly obtain its accurate dynamic model for its motion planning. In this work, we formulate the precise motion control of the free-floating space piecewise constant curvature (FSPCC) continuum manipulator (i.e. space flexible manipulator) as a sparse reward problem in reinforcement learning, and use the Soft Actor-Critic (SAC) algorithm along with the Random Network Distillation (RND) method to train the optimal policies. Firstly, we use the RND method to jointly train a predictive network and a fixed network. The discrepancy between the output values of the two networks is served as an internal reward for the environment. Secondly, the SAC algorithm aims to maximize the expected return and the entropy of the policy. Policies with high entropy will successfully complete the task while acting as randomly as possible. Finally, the internal rewards tend to incentivize the agent to explore more widely for faster convergence of the algorithm. We applied this method to the FSPCC continuum manipulator simulation model and the results demonstrate that the SAC algorithm together with RND method can control the FSPCC continuum manipulator to catch the target quickly, even in the presence of sparse reward.

Continuum manipulator compliance enables operation in delicate environments while challenging the actuation and control approaches. In the case of a catheter ablation of atrial fibrillation, the compliance of the continuum backbone lends an inherent safety to the device. This inherent safety frustrates attempts at precise, accurate, and fast control, limiting the continuum devices to simple and static positioning tasks. This paper develops interleaved continuum-rigid manipulation, by which the hysteretic nonlinearities encountered in tendon-actuated continuum manipulators are compensated by the discrete rigid joints located between the continuum sections. The rigid joints introduce an actuation redundancy, which an interleaved controller may use to avoid the continuum nonlinearities and dynamic excitations, or to prefer particular configurations that may improve task accuracy, permit greater end-effector forces, or avoid environment obstacles. Two experimental systems explore the potential of these joints to: 1) increase the manipulator's dexterous workspace, and 2) correct for actuation nonlinearities and enhance manipulator performance. These experiments also expose important design and control observations that were not apparent in the general robotic and continuum literature.

To address the demands for precision and load-bearing capacity in the installation of building panels, a hybrid force-position driven robot with redundant actuation has been developed. The mechanical performance of this robot is primarily governed by its central parallel mechanism, which is equipped with redundant actuators matching the degrees of freedom. Non-redundant and redundant actuators are respectively responsible for position and force control. The inclusion of redundant force-driven joints has increased the internal coupling within the mechanism. To enhance the coordination between position and force control, a hybrid synchronized control method based on cross-coupling has been proposed. Initially, kinematic and dynamic models of the parallel structure were established. Under predefined trajectories, the theoretical inputs for each actuator were calculated using inverse kinematics and dynamics. Subsequently, employing the principle of cross-coupling, the torque output from the position actuators was used as feedback. This feedback was processed by a synchronized coordination controller to adjust the output force of the redundant force-driven joints. By adjusting the output force of the redundant actuators, the torque burden on the position actuators was effectively reduced, thereby enhancing the precision of position control. Additionally, under the same load conditions, smaller power actuators could be utilized for position control, reducing the overall weight of the robot and improving its load-to-weight ratio. To validate the effectiveness of the proposed control strategy, a robotic simulation environment was established. The simulation results demonstrated significant reductions in the average torque required by the position actuators across three different trajectories, with reductions of 91.43%, 54.56%, and 80.6% respectively. Finally, the load-bearing capacity and the load-to-weight ratio of the prototype were assessed. Experimental results confirmed that the prototype achieved a load-to-weight ratio of 15.83%, validating the effectiveness of the hybrid synchronized control method based on cross-coupling.

A 3-PRR flexure based mechanism which is used as a redundant mechanism providing only x-y micro positioning is designed and controlled in this paper. The aim of this work is to eliminate the unpredictable motions due to manufacturing and assembling errors by implementing sliding mode control (SMC) with disturbance observer (DOB) using piezoelectric actuator models. The system is designed to be redundant to enhance the position control. In order to see the effects of the redundant system firstly the closed loop control is implemented for 2 piezoelectric actuators and the remainder piezoelectric actuator is treated as a fixture. Then the position control is implemented for 3 piezoelectric actuators. As a result, our redundant mechanism tracks the desired trajectory accurately and its workspace is bigger. Finally we have compared the proposed position control with the conventional PID control. It is seen that SMC with DOB gives better results. We have achieved to make the position control of our mechanism, which has unpredictable position errors due to rough manufacturing, assembly, piezoelectric actuator hysteresis etc. The designed 3-PRR flexure mechanism can be used as a micro positioner with the available measurement in the laboratory.

This paper investigates the problem of the position control in switched reluctance motor drives. Advanced proportional-integral (PI) and proportional-differential (PD) controllers for the speed and position control, respectively, are adopted. The parameters of the controllers are on-line fine tuned according to the load torque and rotor speed, for providing high dynamic performance and precise position control. In order to improve the set-point tracking of the drive performance, a low-pass filter is included in the position controller. The proposed four-quadrant control scheme is based on the average torque control method. The turn-on and turnoff angles are on-line determined through simple formulas and the proposed fine tuning regulator is capable of maintaining the torque ripple at an acceptable level over a wide speed range. This is important since the position precision is highly influenced from the motor torque ripple. Experimental results of the switched reluctance motor dynamic response are presented to verify the theoretical considerations and to demonstrate the effectiveness of the proposed control scheme.

This paper proposes the use Fuzzy logic controller and a Particle Swarm Optimization (PSO) based Linear Quadratic Regulator (LQR) controller for the balance of an electric unicycle. It also examines dynamics of the electric unicycle's schematic design, which has a backing seat for the passenger and is analogous to the Segway device equipped with a handle shaft for direction. A proportional derivative controller incorporated with a Fuzzy logic controller was designed for the suggested model of the electric unicycle for speed and position control (Fuzzy controller), and a Proportional Derivative (PD) controller was utilized to control the angle rate and angle of the unicycle. Comparison of the Fuzzy logic controller with a Particle Swarm Optimization (PSO) Linear Quadratic Regulator (LQR) controller was carried out based on error deviation and time response simulations. Command tracking or regulation of some initial state condition were examined and demonstrated by time based simulations of the modelled system. The results evidently indicate that the Fuzzy Proportional Derivative (PD) controller can effectively attain attitude equilibrium for the two wheeled unicycle and preventing it from falling down.