Torque Saturation Research Articles

Handling Actuator Saturation as Underactuation: Case Study With Acroboter Service Robot

Model-based control methods such as inverse dynamics control and computed torque control encounter difficulties if actuator saturation occurs. However, saturation is a common phenomenon in robotics leading to significant nonlinearity in system behavior. In this study, the saturation of the actuator torques is considered as a temporary reduction of the number of independent control inputs. The reduction of the number of actuators leads to an underactuated control problem which typically involves the handling of differential algebraic equation systems. The saturated system may become especially complex when intricate combinations of the actuator saturations appear. A servoconstraint-based inverse dynamics control method for underactuated multibody systems is applied for the treatment of actuator torque saturation. In case of human-friendly robots, the problem of saturation cannot be avoided on the level of trajectory planning because unexpected human perturbations may take place, which result in such abrupt changes in the desired trajectory that lead to saturation at some actuators. A case study for the service robot Acroboter shows the applicability of the proposed approach.

Linear quadratic-based optimal current control of BLDC motor minimizing control error and considering accurate finite element model

Purpose Brushless DC (BLDC) motors are commonly used in the industry. The improvement of power switching electronic elements, especially integrated circuits, has led to the development and improvement of control strategies. The purpose of this paper is to apply the well-known LQR control method for the highly accurate model of the BLDC motor, which is a must for the control system to be optimal and stable. Design/methodology/approach The employed distributed parameter finite element motor model uses a state vector which is dependent not only on time but also on space configuration, thus enabling the end-winding effect, cogging torque or magnetic saturation to be taken into account. The adopted infinite horizon linear quadratic-based controller aims at optimally minimizing current control error considering the energy delivered to the motor. For this reason, the relationship between the quadratic forms of the performance index is investigated and the reference currents’ influence on the results was studied. The presented methodology was confirmed with the numerical analysis of the problem. Findings It was found how the configuration of the optimal control objective function influences the performance and the stability of the drive system subject to energy delivery minimization. An exact configuration was calculated for which the control error was reasonably small. The applicability of the infinite horizon optimal current control for the BLDC drive applications was proved. Originality/value The authors introduced an innovative approach to the well-known control methodology and settled their research in the newest literature coverage for this issue.

Spacecraft fault‐tolerant control using adaptive non‐singular fast terminal sliding mode

Finite-time convergence control strategies based on adaptive non-singular fast terminal sliding mode are proposed for spacecraft attitude tracking subject to actuator faults, actuator saturations, external disturbances and inertia uncertainties. The designed non-singular fast terminal sliding mode control law can converge in a finite time and avoid singularity, hence it can be used to develop a finite-time fault-tolerant attitude tracking controller that meets multiple constraints. It is demonstrated that the controller is independent of inertia uncertainties and external disturbances with adaptive parameters. The controller designed considers the actuator output torque saturation amplitude requirements and makes the spacecraft accomplish certain operations within the saturation magnitude and without the need for on-line fault estimate. The Lyapunov stability analysis shows that the controller can guarantee the fast convergence of a closed-loop system and has a good fault-tolerant performance on actuator faults and saturations under the multiple constraints on actuator faults, actuator saturations, external disturbances and inertia uncertainties. Numerical simulation verified the good performance of the controller in the attitude tracking control.

Design and Finite Element Analysis for the Single-Phase Variable Reluctance Motor

The article presents a review of the design procedures for a switched reluctance machine. A finite element simulation is used to obtain the operating data of the designed prototype. These data are flux linkage, inductance, torque and magnetic saturation. With them it is possible to profile and inductance torque and verification of design for the prototype. It also presents a criterion for analysis operational limit for the machine, based on data collected in the simulation.

Online optimization scheme with dual-mode controller for redundancy-resolution with torque constraints

In this paper, an online optimization scheme is proposed for the real time path-tracking control of the redundant robot manipulator. In the proposed scheme, the inequality constraints are extended to the torque level to avoid the torque saturation. Besides, a dual-mode optimal controller is used to yield a feasible input during each control period, to resolve the solution space decreasing problem. Then the scheme is formulated as a Quadratic Program (QP), the computationally efficient Knitro-Based solver is applied to remedy the inescapable redundancy-resolution problem. Furthermore, the comparisons based on the different path tracking simulations between the proposed method and the velocity-level schemes demonstrate that the former is safer and more applicable. The experiment on a physical robot system further verifies the physical realizability of the proposed method. A dual-mode online optimization method for the redundancy-resolution with torque constraints is proposed in this paper, which extends the constraints in the kinematics level to the dynamics level.The inequality constraints model is designed in the torque level, synthetically considered the constraints in the joint velocity and acceleration level.Besides, a Kintro instrument is applied for redundancy-resolution first time.

Energy Consumption Optimization for Mobile Robots Motion Using Predictive Control

Operation of mobile robots in off-road environment requires the attention to the torque saturation problem that occurs in the wheels DC motors while climbing hills. In the present work, off-road conditions are utilized to benefit while avoiding torque saturation. Energy optimization algorithm using predictive control is implemented on a two-DC motor-driven wheels mobile robot while crossing a ditch. The predictive control algorithm is simulated and compared with the PID control and the open-loop control. Predictive control showed more capability to avoid torque saturation and noticeable reduction in the energy consumption. Furthermore, using the wheels motors armature current instead of the supply voltage as control variable in the predictive control showed more efficient speed control. Simulation results showed that in case of known ditch dimensions ahead of time, the developed algorithm is feasible. Experimental examination of the developed energy optimization algorithm is presented. The experimental results showed a good agreement with the simulation results. The effects of the road slope and the prediction horizon length on the consumed energy are evaluated. The analytical study showed that the energy consumption is reduced by increasing the prediction horizon until it reaches a limit at which no more energy reduction is obtained. This limit is proportional to the width of the ditch in front of the mobile robot. Curve fitting is applied to the obtained results to address further the effect of the parameters on the energy consumption.

입력 토크 포화를 갖는 로봇 매니퓰레이터에 대한 분산 강인 적응 제어

This paper proposes a decentralized robust adaptive control scheme for robot manipulators with input torque saturation in the presence of uncertainties. The control system should consider the practical problems that the controller gain coefficients of each joint may be nonlinear time-varying and the input torques applied at each joint are saturated. The proposed robot controller overcomes the various uncertainties and the input saturation problem. The proposed controller is comparatively simple and has no robot model parameters. The proposed controller is adjusted by the adaptation laws and the stability of the control system is guaranteed by the Lyapunov function analysis. Simulation results show the validity and robustness of the proposed control scheme.

Decentralized sliding-mode control for spacecraft attitude synchronization under actuator failures

This paper examines attitude synchronization and tracking problems with model uncertainties, external disturbances, actuator failures and control torque saturation. Two decentralized sliding mode control laws are proposed and analyzed based on algebraic graph theory. Using Barbalat׳s Lemma, it is shown that the control laws guarantee each spacecraft approaches the desired time-varying attitude and angular velocity while maintaining attitude synchronization among the other spacecraft in the formation. The first controller is designed in the presence of model uncertainties, external disturbances, and actuator failures. The results are extended to the case with control input saturation in the second controller. Both control laws do not require online identification of failures. Numerical simulations are presented to show the effectiveness of the proposed attitude synchronization and tracking approaches.

On the formation of planetary systems via oligarchic growth in thermally evolving viscous discs

We present N-body simulations of planetary system formation in thermally-evolving, viscous disc models. The simulations incorporate type I migration (including corotation torques and their saturation), gap formation, type II migration, gas accretion onto planetary cores, and gas disc dispersal through photoevaporation. The aim is to examine whether or not the oligarchic growth scenario, when combined with self-consistent disc models and up-to-date prescriptions for disc-driven migration, can produce planetary systems similar to those that have been observed. The results correlate with the initial disc mass. Low mass discs form close-packed systems of terrestrial-mass planets and super-Earths. Higher mass discs form multiple generations of planets, with masses in the range 10 < mp < 45M_Earth. These planets generally type I migrate into the inner disc, because of corotation torque saturation, where they open gaps and type II migrate into the central star. Occasionally, a final generation of low-to-intermediate mass planets forms and survives due to gas disc dispersal. No surviving gas giants were formed in our simulations. Analysis shows that these planets can only survive migration if a core forms and experiences runaway gas accretion at orbital radii r > 10 au prior to the onset of type II migration. We conclude that planet growth above masses mp > 10M_Earth during the gas disc life time leads to corotation torque saturation and rapid inward migration, preventing the formation and survival of gas giants. This result is in contrast to the success in forming gas giant planets displayed by some population synthesis models. This discrepancy arises, in part, because the type II migration prescription adopted in the population synthesis models causes too large a reduction in the migration speed when in the planet dominated regime.

컨택트 작업 시 햅틱 인터렉션의 투명성 향상을 위한 Virtual Coupling 기법의 설계

Since its introduction (e.g., [4, 6]), virtual coupling technique has been de facto way to connect a haptic device with a virtual proxy for haptic rendering and control. However, because of the single dependence on spring-damper feedback action, this virtual coupling suffers from the degraded transparency particularly during contact tasks when large device/proxy-forces are involved. In this paper, we propose a novel virtual coupling technique, which, by utilizing passive decomposition, reduces device-proxy position deviation even during the contact tasks while also scaling down (or up) the apparent inertia of the coordinated device-proxy. By doing so, we can significantly improve transparency between multiple degree of freedom (possibly nonlinear) haptic device and virtual proxy. In other to use passive decomposition, disturbance observer of [3] is adopted to estimate human force with some dead-zone modification to avoid "winding-up" force estimation in the presence of device torque saturation. Some preliminary experimental results are also given to illustrate efficacy of the proposed technique.

Adaptive neural tracking and obstacle avoidance of uncertain mobile robots with unknown skidding and slipping

This paper presents a neural-network-based adaptive control approach for path tracking and obstacle avoidance of a class of mobile robots in the presence of unknown skidding, slipping, and torque saturation. The model of mobile robots consists of kinematics and dynamics considering skidding and slipping where all robot parameters as well as skidding and slipping effects are unknown. The proposed adaptive controller is designed using systematic and recursive design methodologies, without the assumption of perfect velocity tracking, where the function approximation technique using neural networks is employed to compensate unknown nonlinear functions including the model uncertainties and bounds of the skidding and slipping. From Lyapunov-stability analysis, it is shown that all signals of the controlled closed-loop system are semiglobally uniformly ultimately bounded, point tracking errors converge to an adjustable neighborhood of the origin outside the obstacle detection region, and the obstacle avoidance is guaranteed inside the region. The effectiveness of the proposed control system is demonstrated by simulation results.

Dynamically optimal trajectories for earthmoving excavators

We consider the problem of generating time-efficient, minimum torque motions for earthmoving excavators. Limits on actuator forces, as well as on joint velocities and accelerations, are assumed given, and the objective is to produce the fastest possible minimum torque motions while avoiding torque saturation limits. Relying on a set of recursive geometric algorithms for calculating the excavator dynamics that also calculates analytic gradients and Hessians of the dynamics as a by-product, we develop robust, reliable algorithms that generate such optimal trajectories. The resulting trajectories are compared with actual digging motions of experienced operators.

Formation tracking control for a class of multiple mobile robots in the presence of unknown skidding and slipping

This study investigates the formation control problem for a class of multiple mobile robots considering unknown skidding and slipping, and torque saturation. The kinematics and dynamics of multiple mobile robots with skidding and slipping effects are considered. The proposed formation control scheme is derived from the dynamic surface design and virtual structure approach where the reference trajectories consisting of path parameters are employed to satisfy both the tracking control and the formation maintenance. The adaptive technique is used to compensate the unknown skidding and slipping effects. From Lyapunov-stability analysis, we prove regardless of unknown skidding and slipping that all signals of the total closed-loop system are semiglobally uniformly ultimately bounded and the point-tracking errors and the synchronisation error for the desired formation converge to an adjustable neighbourhood of the origin. In addition, it is analysed that the orientation error for each robot is related to the speed of the reference trajectory and the skidding effect. The performance and stability of the proposed approach are verified from simulation results.

Adaptive stabilization and tracking control of a nonholonomic mobile robot with input saturation and disturbance

In this paper, we deal with the problem of global tracking and stabilization control of internally damped mobile robots with unknown parameters, and subject to input torque saturation and external disturbances. To overcome the difficulties due to these factors, a new adaptive scheme is proposed to ensure the bounds of the control torques as functions of only design parameters and reference trajectories and thus computable in advance. Then suitable design parameters are determined so that such bounds are within the given saturation limits. To compensate for the disturbances, we estimate their unknown bounds and employ the estimates in controller design. System stability, perfect tracking and stabilization to the origin are established. Simulation studies conducted also verify the effectiveness of the proposed scheme.

Gain-Scheduled Inverse Optimal Satellite Attitude Control

Despite the theoretical advances in optimal control, satellite attitude control is still typically achieved with linear state feedback controllers, which are less efficient but easier to implement. A switched controller is proposed, based on inverse optimal control theory, which circumvents the complex task of numerically solving online the Hamilton-Jacobi-Bellman (HJB) partial differential equation of the global nonlinear optimal control problem. The inverse optimal controller is designed to minimize the torque consumption pointwise, while imposing the stabilization rate of a linear benchmark controller. The controller is then modified by gain scheduling to achieve a tradeoff enhancement compared with the benchmark controller, while maintaining torque saturation limits. The extent to which performance can be enhanced is shown to be dependent on the controller parameters. A controller tuning analysis shows how a design settling time limit can be achieved, within the problem's constraints on the maximum torque and the total integrated torque. The proposed optimization approach is globally stabilizing and presents low implementation complexity, which is highly desirable given the limited resources onboard satellites.

Attitude Control Considering Variable Input Saturation Limit for a Spacecraft Equipped with Flywheels

A new attitude controller is proposed for spacecraft whose actuator has variable input saturation limit. There are three identical flywheels orthogonally mounted on board. Each rotor is driven by a brushless DC motor (BLDCM). Models of spacecraft attitude dynamics and flywheel rotor driving motor electromechanics are discussed in detail. The controller design is similar to saturation limit linear assignment. An auxiliary parameter and a boundary coefficient are imported into the controller to guarantee system stability and improve control performance. A time-varying and state-dependent flywheel output torque saturation limit model is established. Stability of the closed-loop control system and asymptotic convergence of system states are proved via Lyapunov methods and LaSalle invariance principle. Boundedness of the auxiliary parameter ensures that the control objective can be achieved, while the boundary parameter's value makes a balance between system control performance and flywheel utilization efficiency. Compared with existing controllers, the newly developed controller with variable torque saturation limit can bring smoother control and faster system response. Numerical simulations validate the effectiveness of the controller.

A New Spacecraft Attitude Controller Considering Variable Saturation Limit of Flywheels Output Torque

A new attitude controller is proposed in this paper considering variable flywheels output torque saturation limit. Control model is discussed while the time-varying and state-dependent torque saturation limit is derived. The new controller is similar to linear assignment of torque limit and covers attitude feedback information. With Lyapunov method, the asymptotic convergence of controlled system states is proved. The auxiliary parameter contained in the controller is guaranteed to be bounded to make sure that the control objective can be achieved. All of the simulation results validate the analysis and controller.

A structurally optimal control model for predicting and analyzing human postural coordination

This paper proposes a closed-loop optimal control model predicting changes between in-phase and anti-phase postural coordination during standing and related supra-postural activities. The model allows the evaluation of the influence of body dynamics and balance constraints onto the adoption of postural coordination. This model minimizes the instantaneous norm of the joint torques with a controller in the head space, in contrast with classical linear optimal models used in the postural literature and defined in joint space. The balance constraint is addressed with an adaptive ankle torque saturation. Numerical simulations showed that the model was able to predict changes between in-phase and anti-phase postural coordination modes and other non-linear transient dynamics phenomena.

Adaptive tracking control for a class of wheeled mobile robots with unknown skidding and slipping

This study presents an adaptive tracking control approach for trajectory tracking of wheeled mobile robots with torque saturation in the presence of unknown skidding and slipping. The robot kinematics and dynamics are induced from the perturbed non-holonomic constraints. The adaptive control system using the kinematics transformed in polar coordinates is developed to compensate unknown skidding and slipping at the dynamic level of mobile robots with the input saturation. All signals of the controlled closed-loop system are uniformly bounded and the point tracking errors converge to an adjustable neighbourhood of the origin regardless of large initial tracking errors, input saturation and unknown skidding and slipping. Simulation results are provided to demonstrate the performance and stability of the proposed control scheme.

Constrained motion planning for open-chain industrial robots

SUMMARYIn the industrial environment, several constraints affect the robot motion planning. These are imposed by manufacturing considerations, such as, e.g., to strictly follow a given path, or by physical constraints, such as, e.g., to avoid torque saturation. Among the others, limitation on the velocity, acceleration, and jerk at the joints is often required by the robot manufacturers. In this paper, a motion planning algorithm for open-chain robot manipulators that takes into account several constraints simultaneously is presented. The algorithm developed approaches the motion planning algorithm from a wide perspective, solving systematically the joint as well as the Cartesian motion, both for the point-to-point and the fly movements. The validation has been performed first by numerical simulations and then by experiments on two different industrial manipulators, with different size, with and without the presence of a payload, by imposing demanding trajectories where all the constraints have been excited.