Thao Tran Phuong

FPGA-Based High-Performance Force Control System With Friction-Free and Noise-Free Force Observation

In this paper, a novel force-sensing method is proposed for a high-performance force control system based on friction-free and noise-free force observation. A periodic signal is inserted into the control system for friction reduction. A combination of a high-order disturbance observer (DOB) (HDOB) and a Kalman filter is constructed to perform the force sensing. The HDOB is designed to estimate the force and reject oscillatory disturbances in the estimation. The force-sensing bandwidth is improved through effective noise suppression by the Kalman filter. Additionally, this paper proposes the application of the HDOB to the bilateral control system of a different master-slave mechanism. All the control algorithms are implemented in a field-programmable gate array with a high sampling rate that also enables the widening of the bandwidth of the force control system. The effectiveness of the proposed method is verified by experimental results.

FPGA-based wideband force sensing with Kalman-filter-based disturbance observer

Haptic technology has been attracting widespread attention in the fields of robotics and medicine. The bandwidth of force sensing is vital to reproduce the vivid force sensation. This paper proposes a method to enlarge the bandwidth of force sensing. In this paper, the force sensing operation is constructed by a combination of a Kalman-filter and a disturbance observer for multi-sensor. In order to achieve the high sampling rate, the control algorithm together with the force estimation function is implemented in a field programmable gate array (FPGA). The wide bandwidth of force sensing is obtained owing to the shortened sampling period by FPGA and the noise suppression by Kalman-filter. The experimental results show the viability of the proposed method.

Multi-sensor fusion in Kalman-filter for high performance force sensing

Sensorless force sensation by disturbance observer has been widely employed in numerous applications due to its superiority to the measurement by a force sensor. This paper introduces the development of the disturbance observer to obtain the high performance force sensing with a wideband force sensation. In this paper, a multi-sensor data fusion by Kalman-filter algorithm is exploited for velocity estimation which plays the role of an input of the disturbance observer. The combination of multi-sensor-based Kalman-filter and the disturbance observer provides the enhanced force sensing performance and the effective noise reduction. The proposed method is implemented in FPGA with the sampling period of 5 µs. Experimental results confirm the feasibility of the proposed method.

Variable noise-covariance Kalman filter based instantaneous state observer for industrial robot

To enhance the productivity and quality, high speed and high precision industrial robots are required. In the highspeed motion, the dynamic torque of industrial robot prevents the precise operation. To achieve high speed and high precision operation, the dynamic torque calculation is often used to compensate the dynamic torque. Although, it is difficult to calculate the accurate dynamic torque because the accurate dynamic parameters is difficult to obtain. To estimate the dynamic torque without the dynamic torque calculation, this paper uses the disturbance observer (DOB). To achieve the instantaneous dynamic torque estimation of industrial robot, the authors have proposed an instantaneous state observer (ISOB). However, the load torque estimated by the ISOB becomes noisy because the acceleration sensor has the measurement noise. To overcome this problem, this paper proposes a new method for instantaneous load torque estimation using the ISOB and a variable noise-covariance (VNC) Kalman filter. The effectiveness of VNC Kalman filter based ISOB is confirmed by the numerical simulation and experiments using the single joint of industrial robot arm.

Force sensation improvement in bilateral control of different master-slave mechanism based on high-order disturbance observer

In this work, we present a bilateral control system with different mechanisms of master and slave sides. A linear shaft motor and a ball screw perform the roles of the master and slave, respectively. To reduce the friction effect on force estimation due to the ball screw mechanism, a periodic signal is inserted into the control signal of the slave side. The addition of periodic signal causes oscillatory force responses on both master and slave sides. Therefore, a high-order disturbance observer is designed for force sensing operation on the slave side to reduce the effect of oscillatory disturbance on force information. The control algorithm consists of a conventional disturbance observer and a high-order disturbance observer for master and slave sides, respectively. The numerical simulation results verify the effectiveness of the proposed method.

Wideband force control system based on friction free and noise free observation

In this paper, a new force sensing technique is proposed to achieve a friction free and wideband force control of a ball screw system. A periodic signal is inserted into the control system for friction reduction. A combination of a high-order disturbance observer and a Kalman-filter is constructed to perform the force sensing operation. The high-order disturbance observer is designed to obtain force estimation with the cancellation of oscillatory disturbance caused by additional periodic signal. The force sensing bandwidth is improved owing to the effective noise suppression in the estimated force by Kalman-filter. Additionally, all of the control algorithms are implemented in a Field Programmable Gate Array (FPGA) with a fast sampling rate that also enables the ability to widen the bandwidth of the force control system. The effectiveness of the proposed method is verified by experimental results.

Force sensing considering periodic disturbance suppression based on high order disturbance observer and Kalman-filter

Disturbance rejection has been one of foremost issues in control engineering for the past several decades. Disturbance observer is an effective technique to diminish the adverse effects of disturbances. However, in practical applications, there are cases in which the estimated disturbance is affected by vibration phenomenon or additional oscillatory disturbance which is not addressed by the conventional disturbance observer. This paper proposes a high order disturbance observer for force sensing operation and suppression of periodic disturbance in order to achieve an efficient force control. To be practical, the noisy problem of the measurement is taken into account. A Kalman-filter is used in combination with the high order disturbance observer to reduce the noise effect. The feasibility of the proposed method is demonstrated by numerical simulation results.

Kalman filter based fine force sensation with periodic component extraction

This paper proposes a force sensing method with periodic component extraction based on Kalman filter algorithm. In a ball-screw system exhibiting high friction, a dither is inserted to the desired reference signal to eliminate the effect of friction. The force estimation by a disturbance observer is integrated with the force estimation by Kalman filter to construct the force sensation with effective oscillatory component extraction. The disturbance observer estimates the oscillatory torque caused by dither signal. The Kalman filter uses this oscillatory torque as a measurable input to estimate the periodical torque, the first derivative and second derivative of periodical torque. The torque with oscillatory component extraction is generated from estimations achieved by Kalman filter. Moreover, because the force sensation is based on Kalman filter, the effect of noise in force estimation is suppressed effectively. Therefore, it is possible to increase the bandwidth of the force sensing. The effectiveness of the proposed method is verified by numerical simulation results based on experimental data of force control of a ball-screw system.

High performance load acceleration control based on singular spectrum analysis for industrial robot

Rapid and accurate motion control of industrial robots has a vital demand on the precise load torque estimation. To achieve highly robust motion control against dynamic torque, our previous research had introduced the Kalman-filter based instantaneous state observer (ISOB) to attain the instantaneous load torque estimation of a robot arm. This paper proposes the load torque estimation by ISOB based on singular spectrum analysis (SSA) to improve the torque estimation performance. The proposed method achieves highly precise load torque estimation, especially in impulsive responses, with effective noise suppression. The proposed method is targeted to realize the high performance load acceleration control for industrial robots. The validity of the proposed method is verified by numerical simulation results based on the speed-control experimental data of a robot arm.

Robust position control using double disturbance observers based state feedback for two mass system

This paper proposes a robust position control based on state feedback using double disturbance observer for two mass system. In load-side position control based on state feedback using disturbance observer, performance of control system is depend on bandwidth of disturbance observer. To solve problem, the load-side position control using I2-PI controller based on state feedback is proposed. The proposed system consists of PD position controller, motor-side acceleration controller, I2- PI controller equivalent of states feedback, velocity deviation feedback, and a zero-order load-side disturbance observer (ZLDOB) with variable noise-covariance (VNC) Kalman filter. The simulation and experimental results confirm that the load-side position control using I2-PI controller based on state feedback reduces the vibration in response load-side position. Additionally, the proposed method reduces the vibration in response load-side acceleration.