Computed Torque Method Research Articles

Neural Network Robust Control Based on Computed Torque for Lower Limb Exoskeleton

The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings. Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm. The Radial Basis Function (RBF) neural network is used widely to compensate for modeling errors. In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability, a neural network robust control algorithm based on computed torque method is proposed in this paper, focusing on trajectory tracking. It innovatively incorporates the robust adaptive term while introducing the RBF neural network term, improving the compensation ability for modeling errors. The stability of the algorithm is proved by Lyapunov method, and the effectiveness of the robust adaptive term is verified by the simulation. Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out, and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°, respectively. The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.

LIMIT OF USING COMPUTED TORQUE CONTROL OF AUTONOMOUS AIRSHIPS IN WIND ENVIRONMENT

The studies of the swarm of UAVs (Unmanned Aerial Vehicles) have increased, and they are part of many daily tasks. There are several proposals for aircraft that operate autonomously, each with its advantages and disadvantages. An interesting proposal, with a reasonable cost-benefit ratio, is the use of autonomous dirigibles. One of the disadvantages of the airship is its sensitivity to strong wind environments. The proposed work studies the limit of using autonomous airships controlled by computed torque method in a strong winds’ environment. The study established a threshold of wind speed to an autonomous airship be controlled by computed torque method. The use of simulations with wind conditions will showed the limit of computed torque control by data like error to reach the path, variation on absolute speed, effort to control the UAV, and others. These data will help to improve the control system proposed.

Robust Control of a MIMO Laboratory Motion System Using Variable Structure Control and the Computed Torque Method With the Velocity Limitation

Robust Control of a MIMO Laboratory Motion System Using Variable Structure Control and the Computed Torque Method With the Velocity Limitation

Hybrid control of attitude maneuver and structural vibration for a large phased array antenna satellite

This paper focuses on the study about hybrid control strategy of attitude maneuver and structural vibration for a large phased array antenna satellite. The satellite system is equipped with cable actuators in the antenna structure and control moment gyros on the central satellite. Firstly, the rigid-flexible coupling dynamic model of the entire satellite system is established based on the hybrid coordinate method. Then a control strategy is presented which could realize the ideal attitude maneuver of satellite while suppressing the structural vibration simultaneously. The proposed strategy is contained of two parts: the attitude controller is designed based on the computed torque method, and the vibration controller is achieved by using a piecewise cost function which could ensure the unidirectional and saturated constraints of cable actuators. Finally, numerical simulations of a large antenna satellite model demonstrate that the structural vibration during the attitude maneuver process can be suppressed effectively by applying the proposed control strategy.

Nonlinear optimal control for a 4-DOF SCARA robotic manipulator

AbstractSelective compliance articulated robot arms (SCARA) robotic manipulators find wide use in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-degrees of freedom (DOF) SCARA robotic manipulator. The dynamic model of the SCARA robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system, a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control method is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, it is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs and (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators. The nonlinear optimal controller for the 4-DOF SCARA robot is finally compared against a flatness-based controller implemented in successive loops.

Rapid Robust Control of a Marine-Vehicle Manipulator with Series Elastic Actuators Based on Variable Power Log Reaching Law

Marine-vehicle manipulators, which represent a kind of mechanical systems installed on marine surface or underwater vehicles, are mostly suffering from the problem of waves (or ocean currents)-caused base oscillations. The oscillations have a significant impact on system stability. Numerous control strategies have been investigated, but the majority of them are concentrated on the control’s robust performance. This study focuses on an innovative marine-vehicle manipulator (ammunition transfer manipulator on warships) with novel compliant actuators (series elastic actuators), for which the control performance of convergence speed and flexible-vibration suppression should also be considered. To address these issues, this paper proposes a unique hybrid control based on the singular perturbation method, by which the control problem is decomposed into two time scales. In the slow time-scale, it is given a rapid trajectory tracking controller that integrates the computed torque method and the terminal sliding mode control law with a novel reaching law (variable power log reaching law). For the fast time-scale control, a derivative-type controller is used to achieve the suppression of the flexible vibrations. To demonstrate the effectiveness of the proposed control method, theoretical proofs and numerical simulations are both presented. According to our knowledge, this study presents the first control strategy for rapid robust control of marine-vehicle manipulators that are subject to base-oscillation-caused disturbance and compliant-actuator-induced flexible vibrations.

Nonlinear optimal control for the 4-DOF underactuated robotic tower crane

Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum.

Adaptive passivity-based control of an autonomous underwater vehicle

An Autonomous Underwater Vehicle (AUV) is a nonlinear nonholonomic dynamical system. Tracking control of AUVs in the presence of disturbances and uncertainties is a challenging problem. In this paper, an adaptive passivity-based algorithm is proposed for tracking control of an AUV. Also, a disturbance estimator has been used to attenuate the effects of unknown disturbances. A proper adaptive rule is designed to estimate unknown parameters and disturbances. The stability of the proposed method is analyzed using passivity properties and the Lyapunov theory. Obtained comparative results show the advantages of the proposed Adaptive Computed Torque Method ACTM plus disturbance estimator.

Soft Artificial Muscle With Proprioceptive Feedback: Design, Modeling and Control

Twisted-coiled polymer actuators (TCAs) have been known for many interesting properties such as inherent compliance, high stroke, high power density. However, the current TCAs normally come along with traditional sensing methods such as encoders attached to the link, which limits the application of the soft actuator. This letter presents a biologically inspired soft robotic muscle from TCAs with embedded proprioceptive position feedback. The embedded elongation sensor fabricated from EcoFlex and liquid metal has little hysteresis and is soft, which can help detect the muscle’s displacement. Moreover, the position of the muscle module is controlled by applying an adaptive backstepping sliding mode control algorithm which can provide finite-time convergence, high tracking performance with no singularity, and less chattering. It is verified from the experimental results that the muscle can be controlled with an average steady state error of 0.15 mm and follow a sinusoidal waveform with composite frequencies of 0.01 Hz and 0.03 Hz using natural cooling. The proposed controller has better performance over computed torque method control and adaptive sliding mode control in terms of maximum error, mean steady state error, rising time, peak time, and overshoot. A robotic hand application driven by the proposed artificial module was also demonstrated.

Nonlinear optimal control for a five-link parallel robotic manipulator

Control and stabilization of parallel robotic manipulators is a non-trivial problem because of nonlinearities and the multi-variable structure. In this article, a nonlinear optimal control approach is proposed for the dynamic model of such robotic systems, using as a case-study the model of a five-link parallel robot. The dynamic model of the parallel robotic manipulator undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system, a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands as a solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller’s feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control without the need to measure the entire state vector of the parallel robotic manipulator, the H-infinity Kalman filter is used as a robust state estimator. Among the advantages of this control method, one can note that (i) unlike the popular computed-torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs and (ii) it achieves fast and accurate tracking of reference set points under minimal energy consumption by the robot’s actuators.

A robust sliding mode control of mecanum wheel-chair for trajectory tracking

This paper presents a brief study of a dynamic control system and explains a control approach for a mecanum wheel-based mobile robot, such as Mecanum Wheelchair (MWC). The MWC has 4 mecanum wheels which are operated by individual motors and is capable of agile movement in a limited space while maintaining omnidirectional ability. Due to the presence of many external disturbances and uncertainties, the MWC's dynamic and kinematic models are constructed, and different types of control techniques are being categorized. The trajectory tracking control of a parallel wheeled holonomic drive MWC is explained in this manuscript, in which the wheelchair must reach its goal/target by following a pre-determined trajectory under variousinitial states. The proposed robust velocity controller was built using the sliding mode control technique to control the trajectory of a three-degree-of-freedom MWC that was subjected to various external disturbances and uncertainties. The results show that the proposed controller has superior performance as compared to the other methods such as the Computed Torque Method (CTM) in presence of uncertainties.

A Self-Adaptive-Coefficient-Double-Power Sliding Mode Control Method for Lower Limb Rehabilitation Exoskeleton Robot

Lower limb rehabilitation exoskeleton robots have the characteristics of nonlinearity and strong coupling, and they are easily disturbed during operation by environmental factors. Thus, an accurate dynamic model of the robot is difficult to obtain, and achieving trajectory tracking control of the robot is also difficult. In this article, a self-adaptive-coefficient double-power sliding mode control method is proposed to overcome the difficulty of tracking the robot trajectory. The method combines an estimated dynamic model with sliding mode control. A nonlinear control law was designed based on the robot dynamics model and computational torque method, and a compensation term of control law based on double-power reaching law was introduced to reduce the disturbance from model error and environmental factors. The self-adaptive coefficient of the compensation term of the control law was designed to adaptively adjust the compensation term to improve the anti-interference ability of the robot. The simulation and experiment results show that the proposed method effectively improves the trajectory tracking accuracy and anti-interference ability of the robot. Compared with the traditional computed torque method, the proposed method decreases the tracking error by more than 71.77%. The maximum absolute error of the hip joint and knee joint remained below 0.55° and 1.65°, respectively, in the wearable experiment of the robot.

Gravity compensation and optimal control of actuated multibody system dynamics

This work investigates the gravity compensation topic, from a control perspective. The gravity could be levelled by a compensating mechanical system or in the control law, such as proportional derivative (PD) plus gravity, sliding mode control, or computed torque method. The gravity compensation term is missing in linear and nonlinear optimal control, in both continuous- and discrete-time domains. The equilibrium point of the control system is usually zero and this makes it impossible to perform regulation when the desired condition is not set at origin or in other cases, where the gravity vector is not zero at the equilibrium point. The system needs a steady-state input signal to compensate for the gravity in those conditions. The stability proof of the gravity compensated control law based on nonlinear optimal control and the corresponding deviation from optimality, with proof, are introduced in this work. The same concept exists in discrete-time control since it uses analog to digital conversion of the system and that includes the gravity vector of the system. The simulation results highlight two important cases, a robotic manipulator and a tilted-rotor hexacopter, as an application to the claimed theoretical statements.

Dynamic Modeling and Torque Feedforward based Optimal Fuzzy PD control of a High-Speed Parallel Manipulator

Dynamic modeling and control of high-speed parallel manipulators are of importance due to their industrial applications deployed in production lines. However, there are still a number of open problems, such as the development of a precise dynamic model to be used in the model-based control design. This paper presents a four-limb parallel manipulator with Schönflies motion and its simplified dynamic modeling process. Then, in order to fix the issue that computed torque method control (CTC) will spend a lot of time to calculate dynamic parameters in real-time, offline torque feedforward-based PD (TFPD) control law is adopted in the control system. At the same time, fuzzy logic is also used to tune the gains of PD controller to adapt to the variation of external disturbance and compensate the un-modeled uncertainty. Additionally, bottom widths of membership functions of fuzzy controller are optimized by bat algorithm. Finally, three controllers of CTC, TFPD and bat algorithm-based torque feedforwad fuzzy PD controller (BA-TFFPD) are compared in trajectory tracking simulation. Fro the result, compared with TFPD and CTC, BA-TFFPD can lead faster transient response and lower tracking error, which prove the validity of BA-TFFPD.

Dynamic Modeling and Torque Feedforward based Optimal Fuzzy PD control of a High-Speed Parallel Manipulator

Dynamic modeling and control of high-speed parallel manipulators are of importance due to their industrial applications deployed in production lines. However, there are still a number of open problems, such as the development of a precise dynamic model to be used in the model-based control design. This paper presents a four-limb parallel manipulator with Schonflies motion and its simplified dynamic modeling process. Then, in order to fix the issue that computed torque method control (CTC) will spend a lot of time to calculate dynamic parameters in real-time, offline torque feedforward-based PD (TFPD) control law is adopted in the control system. At the same time, fuzzy logic is also used to tune the gains of PD controller to adapt to the variation of external disturbance and compensate the un-modeled uncertainty. Additionally, bottom widths of membership functions of fuzzy controller are optimized by bat algorithm. Finally, three controllers of CTC, TFPD and bat algorithm-based torque feedforwad fuzzy PD controller (BA-TFFPD) are compared in trajectory tracking simulation. Fro the result, compared with TFPD and CTC, BA-TFFPD can lead faster transient response and lower tracking error, which prove the validity of BA-TFFPD.

Control de posición y fuerza con estimación de masa para sistemas cooperativos

<p>La manipulación cooperativa de un objeto por dos o más brazos robóticos requiere controlar tanto el movimiento del objeto como las fuerzas ejercidas por los manipuladores. En términos de cinemática y estática, el enfoque elegido se basa en la denominada formulación simétrica. Se diseña un algoritmo de control que utiliza una modificación del método híbrido de torque computarizado basado en el Principio de Ortogonalización. Además, la masa del objeto se estima calculando la fuerza aplicada por cada efector final para sostener el objeto. El método propuesto es una extensión natural del esquema de control adaptativo previamente reportado para manipuladores geométricamente restringidos. La prueba de estabilidad se desarrolla utilizando la teoría de Lyapunov. Se presentan resultados experimentales.</p>

Dynamics and Control of a Flexible-Link Flexible-Joint Space Robot with Joint Friction

Multi-DOF flexible space robots play a significant role in the on-orbit service. The flexibility of the robots is mainly caused by the flexible links and some flexible drive elements in joints. The vibration generated by the component flexibility can affect the accuracy of control. In this paper, the dynamics and control issues of flexible-link flexible-joint (FLFJ) space robots considering joint friction are studied. Firstly, the Spong’s model is employed to depict flexible joints, and the Coulomb friction model is adopted to describe joint friction. Then based on the single direction recursive construction method and velocity variation principle, dynamic equations of the system are derived. Secondly, a trajectory of joint motion is given and a trajectory tracking controller with friction compensation is designed with the computed torque method. Finally, several numerical simulations are carried out to verify the accuracy of the dynamic model and illustrate the effect of joint friction and joint flexibility on the dynamic characteristics of space robots. Besides, simulation results suggest that the controller designed in this paper could effectively achieve the trajectory tracking control for the 6-DOF FLFJ space robot with joint friction.

Control system of trajectory tracking of discretely-actuated manipulator based on computed torque method

In the past, in the process of tracking and controlling the discretely-actuated manipulator, the tracking result has a large error. To this end, a control system of trajectory tracking of discretely-actuated manipulator based on computed torque metho

여유자유도 로봇 매니퓰레이터를 위한 동적제어시스템

This paper deals with the dynamic control of redundant robot manipulator. Traditionally, the kinematic control schemes for redundant robot manipulator were developed from the point of speed and used under the assumption that the dynamic control of manipulator is perfect. However, in reality, the precise control of redundant robot manipulator is very difficult due to their dynamics. Therefore, the kinematic controllers for redundant robot manipulator were employed in the acceleration dimension and may be combined with the computed torque method to achieve the accurate control performance. But their control performance is limited by the accuracy of the manipulator parameters such as the link mass, length, moment of inertia and varying payload. Hence in this paper, the proportional and derivative control gains of the computed torque controller are optimized by the genetic algorithm on the typical payloads, and the neural network is applied to obtain the proper control gains for arbitrary loads. The simulation results show that the proposed control method has better performance than the conventional control method for redundant robot manipulator.

Design, Modeling, and Control of a New Manipulating Climbing Robot Through Infrastructures Using Adaptive Force Control Method

SUMMARYIn this paper, design, modeling, and control of a grip-based climbing robot are performed, which consists of a triangular chassis and three actuating legs. This robot can climb through any trusses, pipeline, and scaffolds structures and can perform any inspectional and operational tasks in the high height which decreases the falling danger of operation and increases the safety of the workers. The proposed robot can be substituted for the workers to decrease the risk of death danger and increase the safety of the operation. Since these kinds of infrastructures are truss shaped, the traditional wheel-based climbing robots are not able to travel through these structures. Therefore, in this paper, a grip-based climbing robot is designed to accomplish the climbing process through the trusses and infrastructures in order to perform inspecting and manipulating tasks. Hence, a proper mechanism for the mentioned robot is designed and its related kinematic and kinetic models are developed. Robot modeling is investigated for two different modes including climbing and manipulating phases. Considering the redundancy of the proposed robot and the parallel mechanism employed in it, the active joints are selected in a proper way and its path planning is performed to accomplish the required missions. Concerning the climbing mode, the required computed torque method (CTM) is calculated by the inverse dynamics of the robot. However, for the manipulation mode, after path planning, two controlling strategies are employed, including feedback linearization (FBL) and adaptive force control, and their results are compared as well. It is shown that the latter case is preferable since the external forces implemented on the end effector tool is not exactly predetermined and thus, the controller should adapt the robot with the exerted force pattern of the manipulator. The modeling correctness is investigated by performing some analytic and comparative simulation scenarios in the MATLAB and comparing the results with the MSC-ADAMS ones, for both climbing and manipulating phases. The efficiency of the designed controller is also proved by implementing an unknown force pattern on the manipulator to check its efficiency toward estimating the mentioned implemented forces and compensating the errors. It is shown that the designed robot can successfully climb through a truss and perform its operating task by the aid of the employed adaptive controller in an accurate way.