Desired Torque Trajectory Research Articles

Motorized FES-cycling and closed-loop nonlinear control for power tracking using a finite-time stable torque algorithm

Functional electrical stimulation (FES)-induced cycling is a rehabilitation strategy that activates lower-limb muscles to achieve coordinated pedaling in individuals with movement disorders. An electric motor is included in-the-loop assisting the rider as needed to prolong exercise duration and mitigate muscle fatigue. Power tracking objectives have been prescribed for motorized FES-cycling, where muscles and the electric motor are assigned to track desired cadence (speed) and torque trajectories. However, predetermined desired trajectories can yield poor cycling performance since the functional capacity of each individual is unknown. In particular, when muscles are tasked to track a desired torque, a dynamic approach is well-motivated to adjust the torque demand for the rider in real-time (e.g., a constant torque demand may be unfeasible throughout a cycling session since muscles fatigue). In this paper, input-output data is exploited using a finite-time algorithm to estimate the target desired torque leveraging an estimate of the active torque produced by muscles via FES. The convergence rate of the finite-time algorithm can be adjusted by tuning selectable parameters. The cycle-rider system is modeled as a nonlinear, time-varying, state-dependent switched system to activate lower-limb muscles and an electric motor. To achieve cadence and torque tracking, nonlinear robust tracking controllers are designed for muscles and motor. A robust sliding mode controller is designed for the electric motor to track a desired constant cadence trajectory. Moreover, an integral torque feedback controller is designed to activate quadriceps, hamstrings, and gluteus muscle groups to track the desired torque trajectory computed by the finite-time algorithm. A Lyapunov-based stability analysis is developed to ensure exponential tracking of the closed-loop cadence error system and global uniformly ultimate bounded (GUUB) torque tracking. A discrete-time Lyapunov-based stability analysis leveraging a recent tool for finite-time systems is developed to ensure convergence and guarantee that the finite-time algorithm is Hölder continuous. The developed tracking controllers for the muscles and electric motor and finite-time algorithm to compute the desired torque are implemented in real-time during cycling experiments in seven able-bodied individuals. Multiple cycling trials are implemented with different gain parameters of the finite-time torque algorithm to compare tracking performance for all participants.

Neural control of an induction motor with regenerative braking as electric vehicle architecture

This paper presents the synthesis of an induction motor neural controller and a regenerative braking controller for an electric vehicle architecture, based on two energy system, a Main Energy System (MES) and an Auxiliary Energy System (AES). Such controllers are based on system identification, trajectory tracking and state estimation. System identification uses a Recurrent High Order Neural Network (RHONN), trained with an Extended Kalman Filter (EKF). RHONN obtains an accurate motor model which is robust in presence of external disturbances and parameter variations. To force the motor to track a desired torque trajectory and to reject undesired disturbances, an inverse optimal controller based on the identified neural model is proposed. Therefore, the proposed scheme does not need a-priori knowledge of motor parameters. For state estimation a super-twisting observer is implemented to estimate the rotor magnetic fluxes. The regenerative braking controller addresses the issue when the battery is not capable to accept the generated energy due to braking; Therefore, an AES based on a super capacitor and a buck–boost converter is a solution to recover the braking energy and give power to the motor during acceleration. The regenerative braking controller is based on a PI control to regulate voltage and current of the super capacitor. Simulation and experimental results illustrate the performance of the proposed controllers which are implemented using a rapid control prototyping platform integrated by a dSPACE board. Experimental tests are carried out for a topology with and without AES to illustrate the improvement of the proposed EV architecture.

Transmission Characteristics Analysis and Compensation Control of Double Tendon-sheath Driven Manipulator.

The double tendon-sheath drive system is widely used in the design of surgical robots and search and rescue robots because of its simplicity, dexterity, and long-distance transmission. We are attempting to apply it to manipulators, wherenon-linear characteristics such as gaps, hysteresis, etc., due to friction between the contact surfaces of the tendon sheath and the flexibility of the rope, are the main difficulties in controlling such manipulators. Most of the existing compensation control methods applicable to double tendon-sheath actuators are offline compensation methods that do not require output feedback, but when the system’s motion and configuration changes, it cannot adapt to the drastic changes in the transmission characteristics. Depending on the transmission system, the robotic arm, changes at any time during the working process, and the force sensors and torque sensors that cannot be applied to the joints of the robot, so a real-time position compensation control method based on flexible cable deformation is proposed. A double tendon-sheath transmission model is established, a double tendon-sheath torque transmission model under any load condition is derived, and a semi-physical simulation experimental platform composed of a motor, a double tendon-sheath transmission system and a single articulated arm is established to verify the transfer model. Through the signal feedback of the end encoder, a real-time closed-loop feedback system was established, thus that the system can still achieve the output to follow the desired torque trajectory under the external interference.

Torque and cadence tracking in functional electrical stimulation induced cycling using passivity-based spatial repetitive learning control

Due to the inherent periodic nature of cycling tasks, iterative and repetitive learning controllers are well motivated for rehabilitative cycling. Motorized functional electrical stimulation induced cycling is a rehabilitation treatment where multiple lower-limb muscle groups are activated jointly with an electric motor to achieve cycling objectives such as speed (cadence) and torque tracking. This paper examines torque tracking accomplished by the stimulation of six lower-limb muscles via a novel spatial repetitive learning control and cadence regulation by an electric motor using a sliding-mode controller. A desired torque trajectory is constructed based on the rider’s kinematic efficiency, which is a function of the crank position. The learning controller takes advantage of the periodicity of the desired torque trajectory to provide a feedforward input to the stimulated muscles. A passivity-based analysis is developed to ensure stability of the torque and cadence closed-loop error systems. The muscle learning and electric motor controllers were implemented in real-time during cycling experiments on five able-bodied individuals and three participants with movement disorders. The combined average cadence tracking error was 0.01±1.20 RPM for a 50 RPM trajectory and the combined average power tracking error was 1.78±1.25 W for a peak power of 10 W.

A Novel Control Method of Clutch During Mode Transition of Single-Shaft Parallel Hybrid Electric Vehicles

The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor starting engine and the clutch control problem have an important influence on driving quality, and solutions have a bit of room for improving dynamic performance. In this paper, a novel mode transition control method is proposed to guarantee a fast and smooth mode transition process in this regard. First, an adaptive sliding mode control (A-SMC) strategy is presented to obtain the desired torque trajectory of the clutch transmission. Second, a proportional-integral (PI) observer is designed to estimate the actual transmission torque of the clutch. Meanwhile, a fractional order proportional-integral-differential (FOPID) controller with the optimized control parameters by particle swarm optimization (PSO) is employed to realize the accurate position tracking of the direct current (DC) motor clutch so as to ensure clutch transmission torque tracking. Finally, the effectiveness and adaptability to system parameter perturbation of the proposed control approach are verified by comparison with the traditional control strategy in a MATLAB environment. The simulation results show that the driving quality of the closed-loop system using the proposed control approach is obviously improved due to fast and smooth mode transition process and better adaptability.

Fuzzy-PID 알고리듬을 이용한 MR 브레이크의 토크 추종 제어

In the present work, torque tracking control performance of MR brake is evaluated through experimental test. After manufacturing the MR brake, which has been originally designed for haptic application, torque characteristics are investigated with respect to input currents. To achieve enhanced tracking control performance, a new Fuzzy-PID control algorithm is designed and implemented to the system. Torque tracking control performances are evaluated by adopting various desired torque trajectories with sinusoidal, square input signals and square input with multi-magnitudes. It is demonstrated that the proposed MR brake can successfully generate braking torques according to desired inputs by applying proper input current which can be determined based on the proposed control algorithm.

Design of a 4-DOF MR haptic master for application to robot surgery: virtual environment work

This paper presents the design and control performance of a novel type of 4-degrees-of-freedom (4-DOF) haptic master in cyberspace for a robot-assisted minimally invasive surgery (RMIS) application. By using a controllable magnetorheological (MR) fluid, the proposed haptic master can have a feedback function for a surgical robot. Due to the difficulty in utilizing real human organs in the experiment, the cyberspace that features the virtual object is constructed to evaluate the performance of the haptic master. In order to realize the cyberspace, a volumetric deformable object is represented by a shape-retaining chain-linked (S-chain) model, which is a fast volumetric model and is suitable for real-time applications. In the haptic architecture for an RMIS application, the desired torque and position induced from the virtual object of the cyberspace and the haptic master of real space are transferred to each other. In order to validate the superiority of the proposed master and volumetric model, a tracking control experiment is implemented with a nonhomogenous volumetric cubic object to demonstrate that the proposed model can be utilized in real-time haptic rendering architecture. A proportional-integral-derivative (PID) controller is then designed and empirically implemented to accomplish the desired torque trajectories. It has been verified from the experiment that tracking the control performance for torque trajectories from a virtual slave can be successfully achieved.

Design of a New 4-DOF Haptic Master Featuring Magnetorheological Fluid

This work presents a novel 4-degree-of-freedom (4-DOF) haptic master using magnetorheological (MR) fluid which is applicable to a robot-assisted minimally invasive surgery (RMIS) system. By using MR fluid, the proposed haptic device can easily generate bidirectional repulsive torque along the directions of the required motions. The proposed master consists of two actuators: an MR bidirectional clutch associated with a planetary gear system and an MR clutch with a bevel gear system. After demonstrating the configuration, the torque models of MR actuators are mathematically derived based on the field-dependent Bingham model. An optimal design that accounts for spatial-limitation and the desired torque constraint is then undertaken. An optimization procedure based on finite element analysis is proposed to determine optimal geometric dimensions. Based on the design procedure, MR haptic master with the optimal parameters has been manufactured. In order to demonstrate the practical feasibility of the proposed haptic master, the field-dependent generating repulsive force is measured. In addition, a proportional-integral-derivative (PID) controller is empirically implemented to accomplish the desired torque trajectories. It has been shown that the proposed haptic master can track the desired torque trajectory without a significant error.

Control of haptic master – slave robot system for minimally invasive surgery (MIS)

In this work, 4 degrees-of-freedom (DOF) haptic master featuring electrorheological (ER) fluid is proposed and integrated with a slave. Using an ER fluid, the haptic master is devised which can generate a repulsive force/torque with the 4-DOF motion and provide stimulus information to operator. For realization of master-slave MIS system, an encoder is installed with the ER haptic master to establish the MIS master system. The motion command of the haptic master is realized by slave surgery robot. In order to follow the motion of the haptic master, the mechanism of slave surgery robot is devised. Accordingly, the haptic master-slave system is established by incorporating the slave robot with the haptic master device in which the repulsive force/torque and desired position are transferred to each other. In order to obtain the desired torque trajectories, a sliding mode controller (SMC) is designed and implemented. It has been demonstrated that the desired effective torque tracking control performance is well achieved using the proposed master-slave system.

Optimal Control of Digital Hydraulic Drives using Mixed-Integer Quadratic Programming

Abstract Control of dynamical systems gets considerably harder with an increasing number of control variables. Especially when the control variables are restricted to integer values, the solution is of combinatorial complexity. An example of such systems are Digital Hydraulic Drives, where several cylinders contribute to the output torque independently. In this work we present an optimal control approach for torque control of Digital Hydraulic Drives using Mixed-Integer Quadratic Programming in a Model Predictive Control framework. The nonlinear behavior and discrete valued inputs resulting from the use of on-off valves, are accommodated in the control model using a Mixed Logical Dynamical System representation. With the presented approach, optimal switching sequences for the electrical valves are computed that produce the desired torque trajectory with fast tracking and minimal ripple, while keeping switching events at a minimum and respecting physical system constraints.

Speed control of electrical machines: unknown load torque case

The problem of specifying a desired torque trajectory to achieve speed tracking in passivity-based control of induction motors is addressed. This paper presents a solution to the problem that does not require an acceleration measurement nor knowledge of the load torque. To prove the main result a variant of Sontag's input to state stability is used.