Servo Control Research Articles

Robust Fractional-Order PI/PD Controllers for a Cascade Control Structure of Servo Systems

In this paper, a cascade control structure is suggested to control servo systems that normally include a servo motor in coupling with two kinds of mechanism elements, a translational or rotational movement. These kinds of systems have high demands for performance in terms of fastest response and no overshoot/oscillation to a ramp function input. The fractional-order proportional integral (FOPI) and proportional derivative (FOPD) controllers are addressed to deal with those control problems due to their flexibility in tuning rules and robustness. The tuning rules are designed in the frequency domain based on the concept of the direct synthesis method and also ensure the robust stability of controlled systems by using the maximum sensitivity function. The M-Δ structure, using multiplicative output uncertainties for both control loops simultaneously, is addressed to justify the robustness of the controlled systems. Simulation studies are considered for two kinds of plants that prove the effectiveness of the proposed method, with good tracking of the ramp function input under the effects of the disturbances. In addition, the robustness of the controlled system is illustrated by a structured singular value (µ) plot in which its value is less than 1 over the frequency range.

Target location method of intelligent deicing robot based on nonlinear auto disturbance rejection neural network

A visual navigation scheme for intermittent walking deicing robots was designed to address the issues of multiple iterations, long computation time, and poor real-time performance in the nonlinear optimization of the original SLAM system. A computer image acquisition unit, a computer image processing module, and a visual navigation parameter extraction algorithm were also designed. Implemented a visual navigation system for deicing robots based on image processing. It can meet the navigation requirements of the deicing robot. Simulation and experiments have shown that the method proposed in this paper can quickly and accurately identify abnormal point clouds. The visual servo control scheme constructed in this paper is aimed at robot task operations with unknown system calibration and target depth information. By calibrating the robot vision system, the conversion between camera pixel coordinates and robot base coordinates is achieved, with a transmission frame rate of 53.65 per second; The maximum error in positioning accuracy in space is 10.6 mm. The feature trajectory of visual space is smooth and stable within the camera's field of view, and the end movement of Cartesian space robots is stable without rebound, resulting in high grasping and positioning accuracy.

Parameter adaptive based neural network sliding mode control for electro‐hydraulic system with application to rock drilling jumbo

SummaryRock drilling jumbo is an important large construction machine used for tunneling construction, and its automation has an urgent demand in engineering. However, the electro‐hydraulic system of the rock drilling jumbo has strong parameters uncertainties and some dynamics that are hard to model accurately, which causes certain challenges for designing model‐based high‐performance control algorithms. To solve these challenges, a parameter adaptive based neural network sliding mode control algorithm is proposed to enhance control performance of the electro‐hydraulic system. The parameter adaptive law is developed to estimate unknown parameters of the system, the neural network is applied for compensating unmodeled dynamics, and then the final control law is designed by sliding mode control method, and the stability demonstration of the closed‐loop system is given. In the simulations, the effectiveness of the designed parameter adaptive law is verified. Extensive comparison experiments are performed on a real rock drilling jumbo driven by proportional valves, the experimental results demonstrate that the developed control algorithm obviously improves the control precision of hydraulic cylinder of the rock drilling jumbo compared with the traditional sliding mode and PID control algorithm, thus the designed control algorithm can be expanded and applied for general hydraulic servo control mechanism.

Multi-motor average deviation coupling control strategy based on hyperbolic convergence law high-order sliding mode control using extended state sliding mode observer

This paper aims to develop a multi-motor synchronous drive control system for the direction of the width of the lifting arm of a catamaran. Firstly, we establish a mathematical model of permanent magnet synchronous motor and introduce the composition of AC servo control systems. We then analyze the sources of control interference in multi-motor drive systems. Based on the mean deviation coupling control strategy of multi-motor synchronous control, we design a speed tracking controller and a speed synchronization controller using hyperbolic convergence law high-order sliding mode control. Then, we design an extended state sliding mode observer to estimate the unmodeled dynamics of the system in real time. We prove the global stability of the controller using Lyapunov stability theory. Finally, the control model is simulated, and the results confirm the effectiveness of the multi-motor synchronization control method based on the hyperbolic convergence law of higher-order sliding mode control. The control method effectively mitigates the jitter associated with traditional sliding mode control and demonstrates improved synchronization and tracking performance.

UAV Control Based on Pattern Recognition in Aquaculture Application

This study proposes a drone application for the net cage aquaculture industry. A visual control structure is applied to the drone to obtain water-quality information surrounding the net cages. This study integrates a hexacopter, camera, onboard computer, flight control board, servo motor, and global positioning system’s auto-cruise function to adjust the drone position and control the servo motor retractable sensor to reach the desired target at an accurate location. In object identification, a deep learning neural network is used to identify the net cages. An onboard computer calculates the horizontal distance between the drone and the net cage. A “You only look once” (YOLO) neural network is used to detect the net cage images. Considering the hardware calculation speed and ability, an onboard computer is applied to process the flight control board and control the drone. In the mission, an aerial camera detects targets (net cage) and provides visual information to the drone for the target approaching control process. After executing the water-quality measurement, the drone will end the mission and return to the base. This study modifies the architecture of YOLO, compares it with the original model, and then finds a proper architecture for this mission. This study aims to assist cage aquaculture operators by using drones to measure water quality, which can reduce aquaculture’s labor costs.

Constraint‐following servo control for uncertain flexible transmission system with damping

AbstractDue to the flexible components, damping, underactuation, and uncertainties, the control for flexible transmission system (FTS) becomes very difficult. A constraint‐following servo control is designed to address this issue. The damping and applied load of system are integrated into the constraints, so that the desired performance could be achieved by accomplishing the constraints with Udwadia–Kalaba (U–K) equation. The system is divided into two subsystems by introducing a designed fictitious control to the load end, and the controllers of subsystems are designed, respectively. Since the accurate value of uncertainty is usually unknown, a corresponding leakage type of adaptive law is designed to estimate the size of its boundary without requiring the uncertainty itself. The effectiveness and superiority of proposed controller are verified by simulations.

The Application of a Fisheye Lens in the Automatic Alignment of Wireless Optical Communication

To achieve a lightweight design and wide field of view for the automatic alignment system in wireless optical communication, in the receiving antenna—a fisheye lens is incorporated as the receiving optical system. This feature enables the detection and tracking of lasers. The system utilizes a micro motor as the control servo system and a four-quadrant detector as the detection unit. Sequential and non-sequential ray tracing techniques were used to simulate the analysis of the fish-eye lens. Point array diagrams, ray trace diagrams, and encircled energy analysis were utilized to evaluate the spot’s quality. The simulation results demonstrate that the fish-eye lens has a field of view of 120°, and the spot with 80% energy has a diameter smaller than 30 μm. The experimental results indicate that the fish-eye lens effectively captures the light beam within the range of ±30°. The simulated and experimental results for the sum and difference frequency amplitudes show good agreement. The outdoor experiments have demonstrated a tracking error of 22.757 μrad in this system. After alignment, the average output optical power of the detector is 3.23 μW, and the detected waveform amplitude is 12.48 mV. These findings demonstrate the system’s potential for automatic alignment in wireless optical communication. Additionally, the system is relatively simple and practical.

Online Predictive Visual Servo Control for Constrained Target Tracking of Fixed-Wing Unmanned Aerial Vehicles

This paper proposes an online predictive control method for fixed-wing unmanned aerial vehicles (UAVs) with a pan-tilt camera in target tracking. It aims to achieve long-term tracking while concurrently maintaining the target near the image center. Particularly, this work takes the UAV and pan-tilt camera as an overall system and deals with the target tracking problem via joint optimization, so that the tracking ability of the UAV can be improved. The image captured by the pan-tilt camera is the unique input associated with the target, and model predictive control (MPC) is used to solve the optimization problem with constraints that cannot be performed by the classic image-based visual servoing (IBVS). In addition to the dynamic constraint of the UAV, the perception constraint of the camera is also taken into consideration, which is described by the maximum distance between the target and the camera. The accurate detection of the target depends on the amount of its feature information contained in the image, which is highly related to the relative distance between the target and the camera. Moreover, considering the real-time requirements of practical applications, an MPC strategy based on soft constraints and a warm start is presented. Furthermore, a switching-based approach is proposed to return the target back to the perception range quickly once it exceeds the range, and the exponential asymptotic stability of the switched controller is proven as well. Both numerical and hardware-in-the-loop (HITL) simulations are conducted to verify the effectiveness and superiority of the proposed method compared with the existing method.

Homography-Based Visual Servoing of Eye-in-Hand Robots With Exact Depth Estimation

Visual servoing can effectively control robots using visual feedback to improve their intelligence and reliability. For a feature point detected by a monocular camera, the time-varying depth appearing nonlinearly in the Jacobian matrix is difficult to be measured without the prior geometry knowledge of the observed object. Hence, the depth of the feature point is one of the major uncertain parameters in visual servoing. Considering unknown Cartesian feature positions, this study presents a dynamics-based homography-based visual servoing (HBVS) controller for the three-dimensional (3-D) pose regulation of eye-in-hand robot arms with monocular cameras. The uncertain depth is represented as a linear form of its Cartesian feature position, and a composite learning law is applied to estimate position parameters accurately, resulting in exact depth estimation. Compared to existing adaptive HBVS methods, the distinctive feature of the proposed method is that it is a dynamics-based design and guarantees exact depth estimation under a much weaker condition termed interval excitation than persistent excitation. Simulations and experiments on a collaborative robot with 7 degrees of freedom named Franka Emika Panda have verified the effectiveness of the proposed method.

Uncalibrated and Unmodeled Image-Based Visual Servoing of Robot Manipulators Using Zeroing Neural Networks.

Neural networks have been widely investigated for the control of robot manipulators and recurrent neural network (RNN) is accepted as a powerful tool for visual servoing. Different from existing control schemes for robot-camera systems, this article proposes a novel image-based visual servoing (IBVS) control scheme for both the regulation and tracking control of robot manipulators in the framework of a special class of RNN, termed zeroing neural network (ZNN), which does not require prior knowledge about camera configuration and kinematic model parameters. The proposed control scheme is composed of a data-driven mapping estimator and a controller, both of which are designed based on ZNN. To facilitate the deployment of the proposed IBVS control scheme, a discrete-time version of the proposed control scheme is developed. Theoretical analysis for the proposed method is presented in terms of convergence, stability, and robustness. In addition, simulations and experiments are carried out based on different types of robot-camera systems to verify the efficacy and portability of the proposed control scheme for solving regulation and trajectory IBVS problems. Moreover, comparative studies are performed to reveal the merits of the proposed control scheme.

Sliding-mode Active Disturbance Rejection Permanent Magnet Synchronous Motor Control System

Aiming at the permanent magnet synchronous motor with external perturbations and internal uncertainties such as external load, rotational inertia and armature resistance changes, a servo control system based on sliding mode self-immunity controller is designed. By constructing a mathematical model of the servo system of the permanent magnet synchronous motor, considering the internal uncertainty caused by the change of the system parameters and the external random disturbance as the "total disturbance", and designing the transition process and the linear expansion state observer to observe and compensate for it, the system response can track the input signal quickly and without overshooting, and the sliding-mode state feedback makes the closed-loop servo system achieve fast and stable control, and the sliding-mode Active Disturbance Rejection control controller can be used to control the system. The sliding mode state feedback enables the closed-loop servo system to realize fast and stable control, and its consistent stability is proved by the Lyapunov method. Simulations show that this sliding- mode Active Disturbance Rejection control control strategy improves the system response speed and load carrying capability compared with the traditional sliding-mode control.

Research on Electro-hydraulic Servo Valve Structure and Control Algorithm of System with Servo Valve

Background: With the continuous progress of electronic information technology, people have begun to study the combination of electronic information technology and hydraulic technology to achieve more accurate and flexible control. Electro-hydraulic servo technology was thus developed. Much attanetion has been paid to electro-hydraulic servo valve,a key component of electrohydraulic servo technology. Objective: The number of stages of the electro-hydraulic servo valve, the structure form of the electro- hydraulic servo valve hydraulic front stage, the feedback form of the electro-hydraulic servo valve, the output form of electro-hydraulic servo valve, and the control algorithm based on the application of electro-hydraulic servo valve are analyzed and commented respectively. Combined with associated patents, the research direction and hot topics of electro-hydraulic servo valves are analyzed. Method: The electro-hydraulic servo valves were briefly classified; and then the problems of different types of valves were discussed in depth. Results: By analyzing the problems of electro-hydraulic servo valves, the problems of how to improve the control accuracy, response speed, anti-interference ability, service life and cost reduction of electro-hydraulic servo valves are analyzed comprehensively, and the future development prospect of electro-hydraulic servo valves is predicted and outlooked. Conclusion: Analyzing and discussing the existing hot issues of electro-hydraulic servo valves helps to update and change the electro-hydraulic servo valves, and makes corresponding references for the subsequent research of electro-hydraulic servo valves.

Reliability evaluation method for PID feedback control system considering performance degradation

The reliability of proportional-integration-derivative (PID) feedback control systems is crucial for products due to their critical functions. Traditional reliability evaluation methods of PID feedback control systems usually pose difficulties in comprehensively considering the performance compensation property of feedback mechanisms and the degradation phenomenon in operating processes. This paper proposes a new reliability evaluation method for the PID control system under the framework of belief reliability theory to consider both deterministic and uncertain laws regarding functional logics and degradation effects. For deterministic laws, the interdisciplinary, degradation, and margin equations are established with respect to the steady state error. Various internal and external influencing factors are integrated into these equations by modeling state space and characterizing degradation mechanisms. For uncertain laws, the metric equation is constructed accordingly considering diverse uncertain factors. A Monte Carlo-based algorithm and an analysis framework are further developed to calculate the belief reliability. Finally, the proposed method is implemented to an aero-power hydraulic servo control system as a specific illustration, demonstrating its effectiveness and rationality.

An adaptive predefined time sliding mode control for uncertain nonlinear cyber-physical servo system under cyber attacks

Malicious attacks are often inevitable in cyber-physical systems (CPS). Accuracy in Cyber physical system for position tracking of servos is the major concern now a days. In high precision industrial automation, it is very hard to achieve accuracy in tracking especially under malicious cyber-attacks, control saturations, parametric perturbations and external disturbances. In this paper, we have designed a novel predefined time (PDT) convergence sliding mode adaptive controller (PTCSMAC) for such kind of cyber physical control system. Main key feature of our control is to cope these challenges that are posed by CPS systems such as parameter perturbation, control saturation, and cyber-attacks and the whole system then upgrade to a third-order system to facilitate adaptive control law. Then, we present an adaptive controller based on the novel PDT convergent sliding mode surface (SMS) combined with a modified weight updated Extreme Learning Machine (ELM) which is used to approximate the uncertain part of the system. Another significant advantage of our proposed control approach is that it does not require detailed model information, guaranteeing robust performance even when the system model is uncertain. Additionally, our proposed PTCSMAC controller is nonsingular regardless of initial conditions, and is capable of eradicating the possibility of singularity problems, which are frequently a concern in numerous CPS control systems. Finally, we have verified our designed PTCSMAC control law through rigorous simulations on CPS seeker servo positioning system and compared the robustness and performance of different existing techniques.

Spacecraft Formation Keeping and Reconfiguration Using Optimal Visual Servoing

This paper proposes a direct visual servoing system for spacecraft guidance in formation flying scenarios. The proposed image-based visual servoing system uses image information for planning and executing formation acquisition, reconfiguration, and maintenance maneuvers. The system assumes that LEDs are located at specific points on the satellites, enabling the visual servoing controller to rely on continuous tracking of these features in the camera’s image plane. Analytical developments demonstrate that the proposed optimal visual control system is stable and optimal, and it acts on both the orbital and attitude dynamics of the spacecraft, considering circular and elliptical reference orbits. The distributed image-based controller defines a cost function that minimizes control efforts, and the paper proses an optimal framework for developing controllers that address the issue. A ROS-based simulation tool was used to test the proposed visual servoing controller in a realistic small-sat formation flying scenario. Results indicate that the proposed distributed control strategy is viable and robust against environmental perturbations and disturbances in sensing and actuation.

Surface burn prevention based on the probability control of pulses with ignition delay in WEDM

This study aims to address surface burn and increased probability of wire breakage under high-energy cutting conditions in wire electrical discharge machining (WEDM). Firstly, the causes of surface burns are investigated, revealing that the deterioration of cooling, debris removal, and deionization status in the machining gap are the dominating factors. Maintaining a certain ratio of pulse to ignition delay is essential for proper discharge machining. Secondly, a servo control strategy based on the pulse probability of ignition delay is proposed. When the target probability is preset to 25%, the machining stability is significantly improved, preventing surface burns and decreasing the probability of wire breakage. With this servo control, the maximum average machining current free of surface burn is raised from 6 to 8 A. As a result, the max cutting speed is improved by 24%, and the tensile strength of the wire electrode is enhanced by 23.5%. In addition, the machined surface area increases by 22% when the diameter wear of the wire electrode reaches 0.01 mm. The new servo control has been demonstrated to be effective in facilitating machining efficiency and extending wire electrode durability in WEDM.

CONTROL OF THE MAXIMUM POWER POINT OF A SOLAR PANEL, USING SERVO SYSTEM CONTROLLER WITH INTEGRATOR AND PI CONTROLLER DESIGNED BY THE ROOTS LOCUS METHOD

Photovoltaic system applications require to use a solar panel, a power converter, and a load. When voltage reduction from a panel to a battery is necessary, a buck converter is usually proposed. In the specialized literature, there are a wide variety of controllers oriented to commercial panels; However, even though measuring the energy extraction of a solar panel is the main indicator, there are other metrics such as switching effort that also affect the overall performance of the PV system. The main contribution of this work is the design of two digital controllers for photovoltaic energy extraction: a servo system controller with integrator and a PI controller based on root locus techniques considering an MPPT algorithm and system perturbations to demonstrate the reliability and efficiency of the controllers under different system scenarios. Finally, a detailed explanation of the performance of the controllers is given, showing that the two algorithms are suitable for controlling the point of maximum power in photovoltaic panels.

FI-NPI: Exploring Optimal Control in Parallel Platform Systems

Typically, the current and speed loop closure of servo motor of the parallel platform is accomplished with incremental PI regulation. The control method has strong robustness, but the parameter tuning process is cumbersome, and it is difficult to achieve the optimal control state. In order to further optimize the performance, this paper proposes a double-loop control structure based on fuzzy integral and neuron proportional integral (FI-NPI). The structure makes full use of the control advantages of the fuzzy controller and integrator to improve the performance of speed closed-loop control. And through the feedforward branch, the speed error is used as the teacher signal for neuron supervised learning, which improves the effect of current closed-loop control. Through comparative simulation experiments, this paper verifies that the FI-NPI controller has a faster dynamic response speed than the traditional PI controller. Finally, in this paper, the FI-NPI controller is implemented in C language in the servo-driven lower computer, and the speed closed-loop test of the BLDC motor is carried out. The experimental results show that the FI-NPI double-loop controller is better than the traditional double-PI controller in performance indicators such as convergence rate and RMSE, which confirms that the FI-NPI double-loop controller is more suitable for BLDC servo control.

Dividing‐wall column for separating wide boiling mixture: Optimal design and servo control strategy

AbstractThe dividing‐wall column (DWC) stands as an energy‐efficient distillation technology designed to efficiently separate ternary systems into their pure components within a single column. Despite its efficiency, integrating two towers into a DWC poses challenges in controllability. Published studies have focused on developing controllers for disturbance rejection but have not addressed the issue of servo control. Addressing this, our study proposes a servo controller problem and a methodical approach to strategically select controlled variables that undergo consecutive set point step changes, aiming to track the purity of key products obtained from the DWC. To achieve this goal, we developed a dynamic model specifically tailored to the DWC. Determining the design parameters involved employing a genetic algorithm optimization technique, minimizing the total annual cost. Subsequently, we implemented three servo parallel proportional‐integral (PI) feedback controllers for three distinct product streams. The fine‐tuning of their controller gain and reset time is carried out by minimizing the integrated square error while adhering to valve opening constraints. Our investigation revealed a limitation: the introduction of simultaneous step changes in all three controlled variables proved unfeasible with the three active PI controllers. As an alternative, our findings recommend prioritizing two variables: the lightest (distillate) and heaviest (bottom) key components, alongside the middle component (side stream) and either the lightest or heaviest key component. This research underscores the complexities of implementing step changes in multiple controlled variables within a DWC, offering insights into optimal control strategies for enhancing the efficiency of this innovative distillation technology.

Force Compensation Control for Electro-Hydraulic Servo System with Pump–Valve Compound Drive via QFT–DTOC

Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit (HDU), which features a high power–weight ratio. However, most HDUs are throttling-valve-controlled cylinder systems, which exhibit high energy losses. By contrast, pump control systems offer a high efficiency. Nevertheless, their response ability is unsatisfactory. To fully utilize the advantages of pump and valve control systems, in this study, a new type of pump–valve compound drive system (PCDS) is designed, which can not only effectively reduce the energy loss, but can also ensure the response speed and response accuracy of the HDUs in robot joints to satisfy the performance requirements of robots. Herein, considering the force control requirements of energy conservation, high precision, and fast response of the robot joint HDU, a nonlinear mathematical model of the PCDS force control system is first introduced. In addition, pressure–flow nonlinearity, friction nonlinearity, load complexity and variability, and other factors affecting the system are considered, and a novel force control method based on quantitative feedback theory (QFT) and a disturbance torque observer (DTO) is designed, which is denoted as QFT–DTOC herein. This method improves the control accuracy and robustness of the force control system, reduces the effect of the disturbance torque on the control performance of the servo motor, and improves the overall force control performance of the system. Finally, experimental verification is performed using the PCDS performance test platform. The experimental results and quantitative data show that the QFT–DTOC proposed herein can significantly improve the force control performance of the PCDS. The relevant force control method can be used as a bottom-control method for the hydraulic servo system to provide a foundation for implementing the top-level trajectory planning of the robot.