Servo Gain Research Articles

Enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic

Visual servoing is a commonly employed approach in robotics and unmanned aerial vehicles (UAVs) that facilitates accurate object positioning and movement control by utilizing visual feedback. As quadrotors gain popularity, more control methods have been developed. This article presents a method for enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic. Unlike traditional visual servoing, which relies on a fixed gain and often encounters challenges with velocity convergence and maintaining the object in the field of view, this method is designed to enhance the visual servo control of quadrotors by dynamically adjusting the gain of the IBVS system through a fuzzy logic controller. This controller adaptively adjusts the servo gain in response to feature errors and the depth of the object's feature points. MATLAB simulations clearly demonstrate the superior performance of this fuzzy logic integrated method compared to classical approaches, showcasing enhanced control capabilities in challenging environments.

Feasibility of loop-gain tuning for general measurement systems inspired by quantum locking for DECIGO

Abstract A series of quantum locking theories have been proposed to enhance the quantum-noise-limited target sensitivity of the DECi-hertz Interferometer Gravitational wave Observatory. The quantum locking that uses a square completion optimizes the sensitivity across all frequencies. However, a substantial amount of data-series must be post-processed since the square completion is a form of signal processing technique. This paper approaches the optimal sensitivity across all frequencies from an alternative perspective: by optimizing the frequency dependence of a servo gain in a feedback loop. The optimal servo gain is formulated by comparing the alternative method with the square completion method for the same optical setup. This will be shown in general noise issues extending the framework of the quantum locking. We find that the optimal servo gain forms a non-feasible filter but has certain characteristics. We also find that the noise of the measurement signal deteriorates proportionally to the noise measured in the feedback loop when the servo gain is slightly imperfect.

Image-based visual servoing with Kalman filter and swarm intelligence optimisation algorithm

The article proposes a new Kalman depth estimation and an improved swarm intelligence optimisation algorithm for adaptive tuning of servo gain for image-based visual servo control. First, a Kalman depth estimation model is established from the principle of image-based visual servoing, and two state equations are designed for depth estimation based on the number of state quantities. Second, the improved sparrow search algorithm is proposed to tune the servo gain adaptively to improve the convergence speed and stability. To verify the effectiveness of the proposed method, the conventional image-based visual servoing and conventional Kalman estimation are reproduced and compared with the proposed method, and the simulation is completed on the Simulink simulation platform for verification. Finally, the experiments are completed in the robotic arm experimental platform. Both the simulation and experimental results show the effectiveness of the proposed method, which reduces the redundancy of the camera and shortens the convergence time.

Adaptive visual servoing for the robot manipulator with extreme learning machine and reinforcement learning

AbstractIn this study, a novel image‐based visual servo (IBVS) controller for robot manipulators is investigated using an optimized extreme learning machine (ELM) algorithm and an offline reinforcement learning (RL) algorithm. First of all, the classical IBVS method and its difficulties in accurately estimating the image interaction matrix and avoiding the singularity of pseudo‐inverse are introduced. Subsequently, an IBVS method based on ELM and RL is proposed to solve the problem of the singularity of the pseudo‐inverse solution and tune adaptive servo gain, improving the servo efficiency and stability. Specifically, the ELM algorithm optimized by particle swarm optimization (PSO) was used to approximate the pseudo‐inverse of the image interaction matrix to reduce the influence of camera calibration errors. Then, the RL algorithm was adopted to tune the adaptive visual servo gain in continuous space and improve the convergence speed. Finally, comparative simulation experiments on a 6‐DOF robot manipulator were conducted to verify the effectiveness of the proposed IBVS controller.

Deep Reinforcement Learning for the Visual Servoing Control of UAVs with FOV Constraint

Visual servoing is a control method that utilizes image feedback to control robot motion, and it has been widely applied in unmanned aerial vehicle (UAV) motion control. However, due to field-of-view (FOV) constraints, visual servoing still faces challenges, such as easy target loss and low control efficiency. To address these issues, visual servoing control for UAVs based on the deep reinforcement learning (DRL) method is proposed, which dynamically adjusts the servo gain in real time to avoid target loss and improve control efficiency. Firstly, a Markov model of visual servoing control for a UAV under field-of-view constraints is established, which consists ofquintuplet and considers the improvement of the control efficiency. Secondly, an improved deep Q-network (DQN) algorithm with a target network and experience replay is designed to solve the Markov model. In addition, two independent agents are designed to adjust the linear and angular velocity servo gains in order to enhance the control performance, respectively. In the simulation environment, the effectiveness of the proposed method was verified using a monocular camera.

An image-based visual servoing control method for UAVs based on fuzzy logic

Visual servoing is a method to achieve precise positioning and motion control of objects by visual feedback, and it is widely applied in the fields of robotics and unmanned aerial vehicles (UAVs) in recent years. This paper presents a novel image-based visual servoing (IBVS) control method for UAVs based on fuzzy logic to effectively solve the problem under field of view constraint and improve the control efficiency. In this paper, a fuzzy logic of servo gain is designed for the control input of visual servoing, which solves the problem of feature loss in IBVS and improves the efficiency. Meanwhile, a deep computing method based on known data is proposed to solve the unknown depth of Jacobian matrix, which makes the control easier to converge. The effectiveness of the proposed method is verified by the simulation of a quadrotor UAV equipped with a monocular camera.

Homography‐based uncalibrated visual servoing with neural‐network‐assisted robust filtering scheme and adaptive servo gain

AbstractIn this paper, a homography‐based uncalibrated visual servo system with neural‐network‐assisted robust filtering scheme and adaptive servo gain is presented. This system employs a homography‐based task function which is robust to image defects. A neural‐network‐assisted robust filtering method which combines the new form of smooth variable structure filter (SVSF) with a radial basis function (RBF) neural network is proposed to estimate the total Jacobian between task function and robot joints. The RBF neural network in this filtering method plays the role as a corrector to further improve the accuracy and compensate the interference caused by the measurement errors of image features. The controller that directly controls the robot joints based on the estimated total Jacobian is designed for achieving the robustness to robot parameters errors. By adopting this filtering scheme, the visual servo system shows better accuracy and convincing anti‐interference ability. In addition, a novel Q‐learning strategy is introduced for this homography‐based system to make adaptive adjustment for the servo gain. This adaptive gain enables the system to achieve a faster convergence speed while ensuring the accuracy. Several simulations and experiments have been carried out to verify the performance of the proposed system.

Forward Kinematics Model for Evaluation of Machining Performance of Robot Type Machine Tool

Robot-type machine tools are characterized by the ability to change the tool posture and machine itself with a wider motion range than conventional machine tools. The motion of the robot machine tool is realized by simultaneous multi-axis control of link mechanisms. However, when the robot machine tool performs a general milling process, some problems that affect the machining accuracy occur. Moreover, it is difficult to identify the motion errors of each axis, which influence machining accuracy. Thus, it is difficult to adjust the servo gain and alignment error. In addition, the machining performance is unidentified because of the rigidity differences when the posture changes. In this study, the focus was on robot-type machine tools consisting of a serial and a parallel link mechanism. A geometric model is described, and the forward kinematics model is derived based on the geometric model. Machining tests were then carried out to evaluate the machining accuracy by measuring the machined surfaces and the simulated motion of the tool posture based on the proposed forward kinematics model to identify the mechanism that affects the machined surface roughness and surface waviness. As a result, it was shown that the proposed model can separate and reproduce the behavior of each axis of the machine. Finally, it was clarified that the behavior of the second axis has a great influence on the tool posture and machined surface.

Adaptive visual servoing with an uncalibrated camera using extreme learning machine and Q-leaning

In this paper, a novel image-based visual servoing (IBVS) method using Extreme Learning Machine (ELM) and Q-learning is proposed to solve the problems of complex modeling and selection of the servo gain. First, the pseudoinverse of the interaction matrix is approached by ELM which avoids the singularity of the interaction matrix effectively and is robust to interferences such as feature noises and camera calibration errors. Second, a reinforcement learning method, Q-learning, is adopted to adaptively adjust the servo gain in order to improve the convergence speed and stability. Compared with other methods, ELM has better generalization performance, faster operation speed and a unique optimal solution. Also, Q-learning has self-learning ability without experience in advance. The effectiveness of the proposed method is validated by simulations and experiment on a 6-DOF robot with eye-in-hand configuration.

Design and Experimental Verification of Voltage Measurement Circuits Based on Linear Optocouplers with Galvanic Isolation for Battery Management Systems

A battery management system (BMS) design, based on linear optocouplers for Lithium-ion battery cells for automotive and stationary applications is proposed. The critical parts of a BMS are the input voltages and currents measurement circuits. In this design, they include linear optocouplers for galvanic isolation between the battery pack and the BMS. Optocouplers based on AlGaAs light emitted diodes (LED) and PIN photodiode with external operational amplifiers are used. The design features linear characteristics, to ensure the accuracy of the measurements. The suggested approach is based on graphical data digitalizing, which gives the precise values for the most sensitive parameters: photocurrent, normalized and transferred servo gain and helps the calculation procedure to be automated with MATLAB scripts. Several mathematical methods in the analysis are used in order for the necessary equations to be derived. The results are experimentally verified with prototypes.

A learning approach to image-based visual servoing with a bagging method of velocity calculations

Visual servoing allows accurate control of positioning and motion relative to a stationary or moving target using vision and is the subject of many studies. Most servoing gains for image-based visual servoing methods are selected heuristically or empirically so accuracy is affected. This study uses reinforcement learning to adaptively tune the proportional servoing gain over sequences of image based visual servoing, instead of using a constant gain. The system is used to control hovering and tracking for a stationary or slowly moving target. An image Jacobian matrix with four dimensions is constructed because a quad-rotor drone features under-actuated dynamics. The Moore-Penrose pseudo inverse method is usually used to calculate the inverse image Jacobian matrix, but this study uses a bagging approach to calculate the inverse kinematics. The desired velocity is obtained from time-varying image errors, which gives greater robustness. An adaptive method to calculate the servoing gain method is proposed, whereby the selection of an appropriate servo gain over time is regarded as a reinforcement learning problem. The proposed visual servoing control system is implemented and tested experimentally using a quad-rotor drone system. The experimental results demonstrate that the proposed method is more robust and converges faster than other methods.

Investigation of Linear DC Motor Focused on Displacement Sensor Position not Affected by Pitching of Mover

Linear DC motors often fit the drive field of which you request single stroke fast response below the 100 mm in particular. It is necessary to make the servo gain increased to drive LDM by fast-response. But displacement of LDM is easy to oscillate in increased gain. Amount of displacement is increase by pitching of LDM. It is desirable to install the displacement detection sensor at a position not affected by pitching behavior. This paper introduces the displacement detection position not affected by pitching.

Evaluation of Effect of Cushioning Material and Servo Gain on Parachute Landing Impact Using a Small One-Legged Robot

Evaluation of Effect of Cushioning Material and Servo Gain on Parachute Landing Impact Using a Small One-Legged Robot

Simple and robust phase-locking of optical cavities with > 200 KHz servo-bandwidth using a piezo-actuated mirror mounted in soft materials.

We present an approach to locking of optical cavities with piezoelectric actuated mirrors based on a simple and effective mechanical decoupling of the mirror and actuator from the surrounding mount. Using simple elastic materials (e.g. rubber or soft silicone gel pads) as mechanical dampers between the piezo-mirror compound and the surrounding mount, a firm and stable mounting of a relatively large mirror (8mm diameter) can be maintained that is isolated from external mechanical resonances, and is limited only by the internal piezo-mirror resonance of > 330 KHz. Our piezo lock showed positive servo gain up to 208 KHz, and a temporal response to a step interference within < 3 μs.

Effects of temperature on control performance of magnetically levitated planar actuators

During the operation of magnetically levitated planar actuators (MLPAs), the temperature of current coils is rising and the resistance varies in proportion, thus changing the current loop’s gain and directly affecting the system’s control performance. The coil temperature also affects the temperature of adjacent magnetic steel, attenuating the residual flux density of magnetic steel and changing the driving force and torque outputted from coils. In this paper, we analyzed the effects of temperature rise on the control performance of MLPAs. 1) A coil temperature analytical model was used to compute real-time coil temperature, and the temperature parameters were predicted to linearly modify the servo gain coefficient of current loop controller, ensuring that the dynamic performance of current loop is consistent during the operation of MLPAs. 2) A correction factor modifying the effect of temperature on magnetic field intensity was added into the current decoupled model, which improved the precision of the dynamics model and satisfied the strict requirement on the precision of MLPAs.

Prototyping a compact system for active vibration isolation using piezoelectric sensors and actuators

Being small in size and weight, piezoelectric transducers hold unique positions in vibration sensing and control. Here, we explore the possibility of building a compact vibration isolation system using piezoelectric sensors and actuators. The mechanical resonances of a piezoelectric actuator around a few kHz are suppressed by an order of magnitude via electrical damping, which improves the high-frequency response. Working with a strain gauge located on the piezoelectric actuator, an auxiliary control loop eliminates the drift associated with a large servo gain at dc. Following this approach, we design, optimize, and experimentally verify the loop responses using frequency domain analysis. The vibration isolation between 1 Hz and 200 Hz is achieved and the attenuation peaks at 60 near vibration frequency of 20 Hz. Restrictions and potentials for extending the isolation to lower vibration frequencies are discussed.

Motion Control Techniques for Synchronous Motions of Translational and Rotary Axes

This study proposes motion control techniques which can improve dynamic synchronous accuracy between translational and rotary axes in five-axis machining centres. The proposed techniques consist of servo gain tuning, feed forward controller design, signal delay and backlash compensator, rotational fluctuation compensator and jerk limited acceleration process design. In order to evaluate the effect of proposed techniques, experimental tests are carried out. An experimental apparatus consists of X, Y, and C axes is provided for the experiments. Any control algorithm can be implemented into the experimental apparatus because the system is controlled by a personal computer with a DSP board. Translational X and Y axes are powered by AC servo motors and ball screws. A rotary C axis is powered by an AC servo motor, spur and worm gears. Three kinds of synchronous motions are applied to evaluate the dynamic synchronous accuracies. They are; non-uniformed simultaneous 3-axis motion, simultaneous 2-axis motion of X and C axes, and ellipse shape machining motion using simultaneous 3-axis motion. It is clarified from the experiments various factors including signal delay of rotary encoders influence the dynamic synchronous accuracy between translational and rotary axes, and the proposed motion control techniques can significantly improve the dynamic synchronous accuracy without velocity limitations.

Calibration of the total irradiance monitor

Launching on the SORCE (SOlar Radiation and Climate Experiment), the total irradiance monitor (TIM) will measure the total solar irradiance to a relative standard uncertainty of 10−4 and a noise level of 2×10−6 each 400 s. Because of the outstanding brightness, uniformity, stability and collimation of the Sun, this ambient temperature primary radiometer achieves an absolute accuracy comparable to that of a cryogenic radiometer. The major paradigm shift from previous solar radiometers is the use of phase-sensitive detection at the shutter fundamental. We describe the equivalence between replacement power and radiant power as a complex number, the ratio of the (complex) thermal impedances. Our aperture measurements are provided by NIST, with added corrections for diffraction and scattering. We measure the cavity reflection losses versus wavelength using laser scans. We have verified methods for measuring, in flight, the servo gain, cavity reflection changes and shutter-modulated infrared offset (dark signal).

슬림형 광 디스크 드라이브의 축방향 진동에 대한 실험적 해석

As the demand for slim laptops requires low-height optical disc drives, vibration problems of optical disc drives are of great concern. Additionally, with the decrease of a track width and a depth of focus in high density drives, studies on vibration resonance between mechanical parts become more important. From the vibration point of view, the performance of optical disc drives is closely related with the relative displacement between a disc and an objective lens which is controlled by servo mechanism. In other words, to read and write data properly, the relative displacement between an optical disc and an objective lens should be within a certain limit. The relative displacement is dependent on not only an anti-vibration mechanism design but also servo control capability. Good servo controls can make compensation for poor mechanisms, and vice versa. In a usual development process, robustness of the anti-vibration mechanism is always verified with the servo control of an objective lens. Engineers partially modify servo gain margin in case of a data reading error. This modification cannot correct the data reading error occasionally and the mechanism should be redesigned more robustly. Therefore it is necessary to verify a mechanism with respect to the possible servo gain plot. In this study we propose the experimental verification method for anti-vibration mechanism with respect to the existing servo gain plot. Thismethod verifies axial vibration characteristics of optical disc drives on the basis of transmissibility. Using this method, we verified our mechanism and modified the mechanism for better anti-vibration characteristics.

Study on High Gain Feedback Control of Direct-Drive Motor. (Application of Variable Damper Using Homogeneous ER Fluid).

Since a direct-drive(DD) motor system doesn't use the reduction gear, the structure of the servo system can be simple and stiff. On the other hand, in the DD system, the disturbance torque directly influences the accuracy of the control system. The high feedback gain is effective and important for reducing the influence of the disturbance. However, it easily makes the control system vibratory. Therefore, the servo gain has to be lowered for assuring stability, and this causes the influence of the disturbance large. In this study, we aim to realize the high gain feedback control and the DD motor system using an ER fluid damper is developed. By applying the ER damper to the DD motor system, it is possible to obtain the mechanical damping and to realize a high servo gain in the motion control. Finally, the effectiveness of the proposed system is confirmed experimentally.