Open Control System Research Articles

Design of Optical Tweezers Manipulation Control System Based on Novel Self-Organizing Fuzzy Cerebellar Model Neural Network

Holographic optical tweezers have unique non-physical contact and can manipulate and control single or multiple cells in a non-invasive way. In this paper, the dynamics model of the cells captured by the optical trap is analyzed, and a control system based on a novel self-organizing fuzzy cerebellar model neural network (NSOFCMNN) is proposed and applied to the cell manipulation control of holographic optical tweezers. This control system consists of a main controller using the NSOFCMNN with a new self-organization mechanism, a robust compensation controller, and a higher order sliding mode. It can accurately move the captured cells to the expected position through the optical trap generated by the holographic optical tweezers system. Both the layers and blocks of the proposed NSOFCMNN can be adjusted online according to the new self-organization mechanism. The compensation controller is used to eliminate the approximation errors. The higher order sliding surface can enhance the performance of controllers. The distances between cells are considered in order to further realize multi-cell cooperative control. In addition, the stability and convergence of the proposed NSOFCMNN are proved by the Lyapunov function, and the learning law is updated online by the gradient descent method. The simulation results show that the control system based on the proposed NSOFCMNN can effectively complete the cell manipulation task of optical tweezers and has better control performance than other neural network controllers.

Skill Acquisition and Controller Design of Desktop Robot Manipulator Based on Audio–Visual Information Fusion

The development of AI and robotics has led to an explosion of research and the number of implementations in automated systems. However, whilst commonplace in manufacturing, these approaches have not impacted chemistry due to difficulty in developing robot systems that are dexterous enough for experimental operation. In this paper, a control system for desktop experimental manipulators based on an audio-visual information fusion algorithm was designed. The robot could replace the operator to complete some tedious and dangerous experimental work by teaching it the arm movement skills. The system is divided into two parts: skill acquisition and movement control. For the former, the visual signal was obtained through two algorithms of motion detection, which were realized by an improved two-stream convolutional network; the audio signal was extracted by Voice AI with regular expressions. Then, we combined the audio and visual information to obtain high coincidence motor skills. The accuracy of skill acquisition can reach more than 81%. The latter employed motor control and grasping pose recognition, which achieved precise controlling and grasping. The system can be used for the teaching and control work of chemical experiments with specific processes. It can replace the operator to complete the chemical experiment work while greatly reducing the programming threshold and improving the efficiency.

Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm

Assembly robots have become the core equipment of high-precision flexible automatic assembly systems with a small working range. Among different fields of robot technology, path planning is one of the most important branches. In the present study, an elite smoothing ant colony algorithm (ESACO) is proposed for spatial obstacle avoidance path planning of the grasping manipulator. In this regard, the state transition probability and pheromone update strategies are improved to enhance the search capability of path planning symmetry and the convergence of the algorithm. Then a segmented B-spline curve is presented to eliminate path folding points and generate a smooth path. Finally, a manipulator control system based on the Arduino Uno microcontroller is designed to drive the manipulator according to the planned trajectory. The experimental results show that the performance of the ESACO algorithm in different scenarios has symmetry advantages, and the manipulator can efficiently complete the simulation trajectory with high accuracy. The proposed algorithm provides a feasible scheme for the efficient planning of manipulators in equipment manufacturing workshops.

Improving the Accuracy of a Robot by Using Neural Networks (Neural Compensators and Nonlinear Dynamics)

The subject of this paper is a programmable con trol system for a robotic manipulator. Considering the complex nonlinear dynamics involved in practical applications of systems and robotic arms, the traditional control method is here replaced by the designed Elma and adaptive radial basis function neural network—thereby improving the system stability and response rate. Related controllers and compensators were developed and trained using MATLAB-related software. The training results of the two neural network controllers for the robot programming trajectories are presented and the dynamic errors of the different types of neural network controllers and two control methods are analyzed.

Study on Impact Test System of Manipulator Based on Six Axis Force Sensor and Intelligent Controller

With the development and application of intelligent nervous system, intelligent control system represented by machine vision has been promoted and used in various fields, including manipulator control system. Mechanical arm is the main actuator of robot and other mechanical components, but the application environment of mechanical arm is extremely complex, and with the development of industrial process, the sensitivity of technology and operating system for its arbitrary posture operation is also steadily improved. Based on the above problems, this paper designs a manipulator control system based on machine vision theory and orthogonal parallel six-dimensional force sensor to meet the working requirements of manipulator in high-precision environment. Systems hardware are consisted by machine vision structure and six dimensions of force sensor. The practical application effect of the model was verified by collision detection experiment. The relevant research can provide theoretical guidance and practical reference for the research of manipulator control field. Dance and practical application reference for the research of manipulator control field.

End Effector Control System of 6R Manipulator Based on Fuzzy PID

The front three axes of a traditional 6R manipulator move and the back three axes rotate. Given that it is directly connected with the end effector to work and there are some factors such as motor weight, inertia, and material, the end of the manipulator is designed as a system with springs and dampers, so as to improve the stability of the manipulator, reduce errors, and improve production efficiency. Conventional PID control often determines the proportional, integral, and differential effects through simulation, which can not well control the 6R manipulator system in a nonlinear and time-variant state. In order to control the system better, in addition to designing a fuzzy PID control system by making relevant membership functions and fuzzy rules, this paper simulates the end effector of the 6R manipulator by Simulink. The simulation results show that compared with conventional PID, fuzzy PID has better indexes in rapidity, stability, accuracy, and adaptability. The end effector control system of the 6R manipulator based on fuzzy PID is more stable and accurate than the ordinary 6R manipulator.

Using the Mathematical Apparatus of Cellular Automata to Solve the Problem of Monitoring Critical Infrastructure Objects by Unmanned Aerial Vehicles

The purpose of this work is the development of mathematical tools for formalizing decisionmaking problems in open expert real-time control systems. The goal was achieved by defining and formally describing all the elements of a formal system. The most significant result was the proposed approach to formalization. With its help, within the framework of a single formalism, the dynamic properties of the subject area and the logical-analytical activity of the power system dispatcher, presented in different classes of formal logics, were described. The significance of the results obtained lies in the possibility of a rigorous description of various aspects of knowledge within the framework of a single formal apparatus with further pragmatic interpretation in the management process. The proposed approach was distinguished by using the axioms of aletic and deontic logics and the development of axioms that reflect the specifics of the problems being solved. The introduced system of basic concepts and relations makes it possible to classify many decision-making problems for the power systems management. The goals were described within the framework of a single formalism form the basis of the apparatus for formalizing the decision-making problems of the class under consideration. The formalization apparatus provides a description of the dynamic properties of the system within each aspect of knowledge of the content paradigm. The direction of further research is the construction of an appropriate formal theory based on the proposed formal system.

Autonomous 6-DOF Manipulator Operation for Moving Target by a Capture and Placement Control System.

The robot control technology combined with a machine vision system provides a feasible method for the autonomous operation of moving target. However, designing an effective visual servo control system is a great challenge. For the autonomous operation of the objects moving on the pipeline, this article is dedicated to developing a capture and placement control system for the six degrees of freedom (6-DOF) manipulator equipped with an eye-in-hand camera. Firstly, a path planning strategy of online capture and offline placement is proposed for real-time capture and efficient placement. Subsequently, to achieve the fast, stable, and robust capture for a moving target, a position-based visual servo (PBVS) controller is developed by combining estimated velocity feedforward and refined PID control. Feedforward control is designed using the estimated velocity by a proposed motion estimation method for high response speed. PID control is refined by dead zone constraint to reduce the manipulator’s jitter caused by the frequent adjustment of manipulator control system. Besides, the proportional, integral, and differential coefficients of PID controller are adaptively tuned by fuzzy control to reject the noise, disturbance, and dynamic variation in the capture process. Finally, validation experiments are performed on the constructed ROS–Gazebo simulation platform, demonstrating the effectiveness of the developed control system.

Accurate Micromanipulation of Optically Induced Dielectrophoresis Based on a Data-Driven Kinematic Model.

The precise control method plays a crucial role in improving the accuracy and efficiency of the micromanipulation of optically induced dielectrophoresis (ODEP). However, the unmeasurable nature of the ODEP force is a great challenge for the precise automatic manipulation of ODEP. Here, we propose a data-driven kinematic model to build an automatic control system for the precise manipulation of ODEP. The kinematic model is established by collecting the input displacement of the optical pattern and the output displacements of the manipulated object. Then, the control system based on the model was designed, and its feasibility and control precise were validated by numerical simulations and actual experiments on microsphere manipulation. In addition, the applications of ODEP manipulation in two typical scenarios further demonstrated the feasibility of the designed control system. This work proposes a new method to realize the precise manipulation of ODEP technology by establishing a kinematic model and a control system for micromanipulation, and it also provides a general approach for the improvement of the manipulation accuracy of other optoelectronic tweezers.

Design of the MVT RBF neural network robotic manipulator control system based on model block approximation

Due to the uncertain dynamic characteristics, the requirements for robotic manipulator control are increasingly complex. The traditional radial basis function (RBF) neural network has a good generalization ability, but its redundant and tedious training process cannot meet the “Intelligent” control requirement of robotic manipulator. This study designs a new valve-regulated memristive RBF neural network, which adopts the model block approximation control strategy to estimate the three coefficient matrices of the robotic manipulator and uses the memristor with voltage threshold (MVT) as an electronic synapse to provide connections between neurons for the neural network and store information. This study adopts the design idea of software hardening and replaces the updated neural network weight with the change of the memristance value in the MVT network (crossed array), which can effectively improve the control performance of the traditional RBF neural network and can also provide analytical data for the fault detection of the subsequent control system. A simulation analysis is conducted with a single-joint robotic manipulator as the control object, and the results verify the rationality and feasibility of the proposed control algorithm.

An optimal visual servo trajectory planning method for manipulators based on system nondeterministic model

AbstractWhen a manipulator captures its target by a visual servo system, uncertainties can arise because of mechanical system and visual sensors exist error. This paper proposes an intelligent method to predict the successful rate for a manipulator to capture its target with motion and sensor errors. Because the mapping between the joint space of the manipulator and the Cartesian space at the end of the manipulator is nonlinear, when there is a bounded error of the manipulator’s joint, the error range of the end motion is constantly changing with the different joint positions. And at the same time, the visual servo camera will also measure the target from different positions and postures, so as to produce measurement results with different error ranges. The unknown time-varying error property not only greatly affects the stability of the closed-loop control but also causes the capture failure. The purpose of this paper is to estimate the success probability of different capture trajectories by establishing the nondeterministic model of manipulator control system. First, a system model including motion subsystem and feedback subsystem was established with system error described by Gaussian probability. And then Bayesian estimation was introduced into the system model to estimate the executing state of the predefined trajectory. Linear least quadratic regulators (LQR) control is used to simulate the input correction in the closed-loop control between motion subsystem and feedback subsystem. At last, the successful probability of capturing the target is established by the Gaussian distribution at the end point of the trajectory with geometric relationship calculation between tolerance range and error distribution. The effectiveness and practicability of the proposed method are proved by simulation and experiment.

Application of S7-300 PLC and Single Axis Motion Controller in Manipulator Control System

A set of flexible manufacturing production line training equipment in the college carries materials through a manipulator, which is controlled by S7-300 PLC. The FM353 module in the control system is damaged, and the device cannot be used. In order to repair the control system, this paper proposes a low cost solution. By choosing a single axis motion controller to replace the FM353 module function and S7-300 PLC with the control system/PLC control single axis motion controller can send high speed pulse output to the stepper driver, achieve the position and speed control of the stepper motor, and realize the control of a four degrees of freedom manipulator. Based on the design scheme, the control system of the manipulator is reformed. After modification, the system can run normally, which verifies the rationality and effectiveness of the design.

Real-Time Decision-Making Systems: Approaches to Construction

The purpose of this work is the development of mathematical tools for formalizing decisionmaking problems in open expert real-time control systems. The goal was achieved by defining and formally describing all the elements of a formal system. The most significant result was the proposed approach to formalization. With its help, within the framework of a single formalism, the dynamic properties of the subject area and the logical-analytical activity of the power system dispatcher, presented in different classes of formal logics, were described. The significance of the results obtained lies in the possibility of a rigorous description of various aspects of knowledge within the framework of a single formal apparatus with further pragmatic interpretation in the management process. The proposed approach was distinguished by using the axioms of aletic and deontic logics and the development of axioms that reflect the specifics of the problems being solved. The introduced system of basic concepts and relations makes it possible to classify many decision-making problems for the power systems management. The goals were described within the framework of a single formalism form the basis of the apparatus for formalizing the decision-making problems of the class under consideration. The formalization apparatus provides a description of the dynamic properties of the system within each aspect of knowledge of the content paradigm. The direction of further research is the construction of an appropriate formal theory based on the proposed formal system.

Maneuver and formation control of a pair of soft pneumatic bending fingers by a cooperative strategy for planar in-hand object manipulation

In this paper, we seek performing dynamic in-hand object manipulation with two-segmented soft fingers in 2-D plane. Thereby, after the dynamic behavior of the soft fingers was defined, we evaluate the influence of external tip force on the finger. It is shown that the tip position error, under the effect of tip force, can be represented by uncertainties in kinematic parameters of the finger. As a result, we design a sliding-adaptive controller with compensation of kinematic uncertainties to fulfill our expectation that is controlling the tip position of the finger in vertical plane while interacting with the environment. Finally, inspired by the way that human fingers manipulate an object, a cooperative control system for manipulation is proposed which incorporates the states and tip positions of the fingers in its feedback signal. Combination of this controller with the adaptive control system yields more promising results than does the PID controller. In order to evaluate performance of the proposed controller, Simulation results for manipulation of a cubic rigid object are demonstrated.

An Adaptive Fuzzy Control Model for Multi-Joint Manipulators

Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required. Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity, coupling and uncertainty. Therefore, the proposed algorithm has good practical application prospects and promotes the development of complex control systems.

Projektowanie modelu dydaktycznego pozycjonera paneli fotowoltaicznych

The study presents example of didactic model of two-axis PV panel positioner, operating in an open control system. The controller has control algorithm based on astronomical calculations. During the tests, the quality of the control algorithm and the energy efficiency of the system were checked. The conducted tests confirmed the correct operation of the positioner.

Синтез и исследование адаптивной системы управления силовыми взаимодействиями в упругих механизмах многозвенных манипуляторов

Предложена методика синтеза адаптивной электромеханической силокомпенсирующей системы управления шарнирно-балансированным манипулятором с многозвенной структурой упругого исполнительного механизма. Приведено математическое описание электромеханической системы с трёхмассовой механической частью. Получены аналитические выражения для определения параметров адаптивного управляющего устройства при изменении массы перемещаемого объекта и жесткости механических передач и звеньев. Проведено исследование механической части манипулятора без электропривода и с применением предложенной адаптивной системы управления усилиями в упругом исполнительном механизме с синтезированным корректирующим устройством при изменении положения и массы перемещаемого груза от 20 до 160 кг.

DESIGN OF A TWO-LINK ROBOT MANIPULATOR ADAPTIVE CONTROL SYSTEM BY THE GAIN SCHEDULING METHOD

The application areas of robot manipulators are increasingly growing year by year. Rehabilitation exoskeletons and upper limb prostheses are special cases of robot manipulators. Such systems, being nonlinear, multidimensional, and dynamic systems, have parametric uncertainties. All this becomes a challenge in the design process of the control system. One of the advanced technologies in this field is adaptive control, which is an important and interesting area of scientific and industrial research. The nonlinear control system of the two-linked robot manipulator was considered in the work. In this case, classical control methods become inapplicable and there is a need to develop and apply other control methods. Using the gain scheduling method, a group of PID controllers are designed to ensure the stability of the system at various operating points. The non-linearity of the system is compensated by the gain scheduling method and the only problem that remained is the uncertainties of the system depending on the weight of the operator. A model reference adaptive controller (MRAC) was designed and augmented with the gain scheduling method for eliminating uncertainties. Simulation is done in the MATLAB Simulink environment. A comparative performance has been quantified with different adaptation gains for the upper limb prosthesis system. The obtained results show the viability of the proposed control method.

An Architecture for a Multi-Vendor VSC-HVDC Station With Partially Open Control and Protection

High voltage direct current (HVDC) grids are envisioned for large-scale grid integration of renewable energy sources. Upon realization, components from multiple vendors have to be coordinated and interoperability problems can occur. To address these problems, a multi-vendor HVDC system can benefit from a partially open control and protection system. Unwanted interactions can be investigated and solved more easily in partially open software compared to when applying black-boxed and vendor-specific software. Although a partially open approach offers these advantages, practical aspects, such as the implementation in a real station architecture, have to be addressed carefully. This paper covers this important topic, first by reviewing the required control and protection functions and second by discussing the choice for certain open and closed software parts, their implementation in physical units as well as the required communication and interfaces. The result from this discussion is a first proposal of a station architecture for a multi-vendor HVDC system using partially open control and protection. This architecture will be a helpful starting point to industry and academia working with research and harmonization on this topic as ad-hoc solutions in terms of practical aspects can be avoided.

Simulation research on trajectory tracking control system of manipulator based on fuzzy PID control

In view of the influence of external environment interference, parameter changing and random noise in the process of manipulator trajectory tracking, as well as the problems of fuzzy PID control, such as fuzzy rules are not easy to set, quantisation interval and parameters are affected by subjective consciousness, which leads to the problem of insufficient performance of manipulator system. In this paper, firstly, in the MATLAB simulation environment, based on the D-H parameter model, the linkage model of the four degree of freedom manipulator is established, and the homogeneous transformation matrix of the manipulator is calculated. Then, through the application of fuzzy PID control in the Simulink toolbox, the optimal parameters of the controller are found by using the proportion factor self-adjusting strategy, and the corresponding trajectory tracking and forward inverse kinematics simulation are studied. The trajectory tracking curve of the manipulator is obtained. The research method and experimental results in the paper are of great significance for the simulation of articulated manipulator.