Networked Motion Control Research Articles

Demonstration of networked motion control using bandwidth-reserved transmission rate control

Demonstration of networked motion control using bandwidth-reserved transmission rate control

Neural Network Motion Control of a Spherical Robot in Planar Case

Neural Network Motion Control of a Spherical Robot in Planar Case

Performance guaranteed attack reconstruction for cyber–physical systems: A new intermediate estimator-based framework

For attack reconstruction issue of cyber–physical systems (CPSs), it is a challenge to guarantee online computational efficiency and reconstruction accuracy simultaneously, especially for cases with actuator attacks. However, most existing approaches are only focused on sensor attacks. This brief paper studies the multiple attack reconstruction problem for CPSs. A new projected intermediate estimator is proposed, where the computation complexity problem is solved by reducing the number of loop iterations significantly via enhancing the designs of loop iteration, termination condition and parameter selection strategy, without sacrificing the attack reconstruction performance. Compared with traditional intermediate estimators, the dependence of linear matrix inequality technique is completely removed, besides, the intrinsic heavy overshooting problem in transient period is effectively alleviated. The application to a networked motion control system verifies the effectiveness and superiority of the presented method.

Networked Motion Control for Smart EV With Multiple-Package Transmissions and Time-Varying Network-Induced Delays

This article aims to address the coupled problem of the multiple-package transmissions (MPT) and time-varying network-induced delays (TND) within the networked motion control systems of smart electric vehicles (EVs). The recent development of advance digital sensors, actuators, and controllers leverage the worldwide upgrade of transportation in terms of electrification and intellectualization. However, for smart EVs, this updating may challenge the in-vehicle network and then the vehicle control performance. In particular, the nonsynchronous MPT and the TND are the key issues in the vehicle's integrated motion control due to the absence of the synchronization mechanism and limitation of communication bandwidth. To deal with the effects of coupled MPT and TND, a hybrid schedule-control framework is developed, where a new MPT scheduler is developed with a flexible time-triggered schedule strategy with fractional-type basic period to eliminate the effect of the MPT and reorganize the TND to a bounded range of delay. Furthermore, an H∞-based linear quadratic regulator control approach is designed to deal with the uncertainties caused by the TND as well as guarantee the system's stability. The effectiveness of the proposed scheme is verified in three cases by the real-time hardware-in-the-loop bed tests.

Hybrid Synchronous–Asynchronous Execution of Reconfigurable PLC Programs in Edge Computing

In edge computing, heterogeneous automation tasks, such as networked motion control and reconfiguration management, have diverse weights on determinism and flexibility. Such heterogeneities escalate the demands on the runtime environments (RTEs) of programmable logic controllers to provide the best-suited rather than one-size-fits-all execution policies for reconfigurable programs. This article presents the proposal and implementation of a novel IEC 61499-based RTE capable of offering hybrid synchronous and asynchronous execution models for function block (FB) based programs. We also construct a runtime reconfigurable FB-type repository by realizing a just-in-time FB-type definitions compiler in the RTE. Finally, we evaluate and compare the proposed RTE and state-of-the-art works by running a set of synthetic benchmark programs and a realistic networked motion control kernel and application. Experiment results from the benchmark programs have shown a maximal 40% faster execution speed in our RTE. Furthermore, our RTE can ensure fewer jitters during distributed motion control with a 1-ms cycle time on a realistic motion control testbed.

Secure Teleoperation Control Using Somewhat Homomorphic Encryption

The goal of this research is to establish control theoretic methods to enhance cyber security of networked motion control systems by utilizing somewhat homomorphic encryption. The proposed approach will encrypt the entire motion control schemes including: sensor signals, model parameters, feedback gains, and performs computation in the ciphertext space to generate motion commands to servo systems without a security hole. The paper will discuss implementation of encrypted bilateral teleoperation control schemes with nonlinear friction compensation. The paper will present (1) encrypted teleoperation control realization with somewhat homomorphic encryption and (2) simulation results.

Dynamic Network Path Provisioning and Selection for the Detection and Mitigation of Data Tampering Attacks in Networked Control Systems

Networked control systems can help build cost-effective and flexible industrial systems. A system that can function while being immune to cyberattacks is necessary. A method called fixed redundant path selection (FRPS) has been proposed to detect and mitigate data tampering attacks in a networked motion control system. This system contains redundant forward network paths from the controller to the motor sides to detect the attacked path by comparing the values that are received through respective paths. Then, a path selector on the motor side chooses a value on the path that is not attacked based on the majority decision. Increasing the number of redundant paths improves the detection performance of simultaneous attacks against multiple paths. However, it also increases the amount of traffic because the same data are transmitted to all of the redundant paths. This study proposes a dynamic redundant path selection (DRPS) method to balance the detection performance and the amount of traffic. The proposed method initially applies three redundant paths and changes the number of redundant paths to five only when the path selector detects a difference among the received values for the three paths. The experiments confirm that the proposed DRPS outperforms the conventional FRPS. The former can detect and mitigate the data tampering attacks while reducing the number of network paths during tampering detection when the system is exposed to simultaneous attacks against up to two of the redundant paths.

Sensor attack detection for cyber‐physical systems based on frequency domain partition

This study is concerned with the attack detection (AD) problems in finite frequency domain for cyber-physical systems with sensor attack. The frequency domain is divided into three frequency domains of low, medium and high, multiple AD filters are designed to work simultaneously. The attack detectionAD problem is transformed into a multi-objective optimisation schemes for each finite frequency domain. Finally, the experimental results of networked motion control system are given to verify the effectiveness and superiority of proposed method.

High-Precision Contour-Tracking Control of Ethernet-Based Networked Motion Control Systems

High-Precision Contour-Tracking Control of Ethernet-Based Networked Motion Control Systems

A GESO based MPC approach to contour error control of networked motion control system

This paper presents a generalised extended state observer (GESO) based model predictive control (MPC) approach to contour error control for networked multi-axis motion system (NMAMS) with network-induced delays. First, the uncertainties induced by the network-induced delays are modelled as an additive bounded disturbance, and a novel model predictive controller based on the GESO is designed for the uniaxial trajectory tracking control system. The GESO is used to estimate the system state and the disturbance simultaneously, and the effects of the uncertainties induced by the delays are eliminated by the proposed GESO based controller. Then the contour error estimation method is adopted, and a PID controller is designed to compensate the contour error. Finally, experiments are carried out to demonstrate the effectiveness of the proposed method.

A LADRC based fuzzy PID approach to contour error control of networked motion control system with time‐varying delays

AbstractThis paper investigate the contour error control problem for networked multi‐axis motion system (NMAMS) with time‐varying delays. Firstly, the uncertainties induced by the delays are modeled as a part of the total disturbance, and a linear active disturbance rejection controller (LADRC) is designed for the uniaxial trajectory tracking control. In the LADRC, a linear extended state observer (LESO) is designed to estimate the system state and the total disturbance simultaneously, and the effect of the total disturbance is eliminated by the designed linear feedback error control law. Then, the classical contour error estimation method is adopted, and a fuzzy PID controller is designed to compensate the contour error to achieve a better contour tracking performance. Finally, experiments are provided to verify the effectiveness of the proposed method.

Implementation of Network Motion Systemusing RTEX Network for XY Gantry

Recently, the weapon systems are more and more complex and the demands for handling and maintaining these complex systems effectively are increased. For this reason, industrial control network had been developed for many years and the needs for the development of a totally networked automation environment are raised. To meet these requirements, networked motion control systems tend more and more to replace the traditional solutions. In this paper, the XY platform motion control system employing RTEX (Real Time Express) network which is one of the Ethernet based vender-oriented industrial networks is tackled. The network motion controller which generates motion profile and outputs the pulse train is implemented and is applied to XY platform. As results, it is shown that the proposed network motion controller works properly to control the XY platform and monitors the system easily through network.

Research and realisation of real-time Ethernet protocol for networked motion control system

Existing control cards typically use non-real-time Ethernet protocols, such as TCP/IP, making it difficult to achieve multi-axis synchronisation between control cards. A practical scheme is proposed in this paper to solve this problem. In this scheme, the internal clocks of control cards are adjusted to the same value by the sync frames periodically sent by the host. The jitter of the sync frame has very little impact on the consistency of the clocks of all control cards. This alleviates the real-time performance requirements of the host, and thus reduces the cost and design difficulty. In addition, all synchronous or asynchronous frames are unified into a cluster frame model, which simplifies the processing of the frames, making it easy to implement in hardware such as FPGAs. This real-time Ethernet protocol has been implemented in a large-scale motion control chip. And the test results showed that this scheme achieves expected performance.

Research and realisation of real-time Ethernet protocol for networked motion control system

Existing control cards typically use non-real-time Ethernet protocols, such as TCP/IP, making it difficult to achieve multi-axis synchronisation between control cards. A practical scheme is propose...

Adaptive recurrent neural network motion control for observation class remotely operated vehicle manipulator system with modeling uncertainty

Precise motion control of remotely operated vehicles plays an important role in a great number of submarine missions. However, the high-performance operations are difficult to realize due to the uncertainty in system modeling with self-disturbance. On the basis of the multibody system dynamics, self-disturbances from the tether and manipulator have been systematically analyzed in order to transform them into observed forces. A novel S surface–based adaptive recurrent wavelet neural network control system has been proposed on the nonlinear control of underwater vehicles, with its recurrent wavelet neural network structure designed for the approximation of the uncertain dynamics. Moreover, a robust function has been proposed to improve system robustness and convergence. The comparison shows that the remotely operated vehicle operation performance including the three-dimensional path following and vehicle-manipulator coordinate control has been greatly improved.

A Double Disturbance Observer Design for Compensation of Unknown Time Delay in a Wireless Motion Control System

Unknown time delay poses a significant challenge to the design of networked motion control systems. Moreover, modeling uncertainties, mechanical disturbance, and sensor noise coexist with time delay in such systems, which makes the controller synthesis even more challenging. It has been proven effective to model the time delay as fictitious disturbance so that a disturbance observer (DOB) can be employed to cancel the negative effect of time delay. In this brief, a new double DOB (DDOB) design is proposed by adding one more DOB into the control system to handle actual external disturbance and enable satisfactory tracking performance. Design considerations of the baseline controller and the two DOBs are illustrated, and robust stability analysis is provided to handle modeling uncertainties. A real-time wireless communication protocol, RT-WiFi, is integrated with a DC motor to examine the performance of the proposed DDOB by simulations and experiments.

Adaptive neural network motion control for aircraft under uncertainty conditions

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Modified Primal-Dual Neural Networks for Motion Control of Redundant Manipulators With Dynamic Rejection of Harmonic Noises.

In recent decades, primal-dual neural networks, as a special type of recurrent neural networks, have received great success in real-time manipulator control. However, noises are usually ignored when neural controllers are designed based on them, and thus, they may fail to perform well in the presence of intensive noises. Harmonic noises widely exist in real applications and can severely affect the control accuracy. This work proposes a novel primal-dual neural network design that directly takes noise control into account. By taking advantage of the fact that the unknown amplitude and phase information of a harmonic signal can be eliminated from its dynamics, our deliberately designed neural controller is able to reach the accurate tracking of reference trajectories in a noisy environment. Theoretical analysis and extensive simulations show that the proposed controller stabilizes the control system polluted by harmonic noises and converges the position tracking error to zero. Comparisons show that our proposed solution consistently and significantly outperforms the existing primal-dual neural solutions as well as feedforward neural one and adaptive neural one for redundancy resolution of manipulators.

Hierarchical Distributed Motion Control for Multiple Linear Switched Reluctance Machines

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on the successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

Frequency-Tracking Clock Servo for Time Synchronization in Networked Motion Control Systems

With the application of internet in manufacturing, motion control system is tend to networking. Clock synchronization is a basic requirement to guarantee capability of coordination in networked motion control systems. In this paper, we propose a frequency-tracking clock servo (FTCS) to adjust the local clock to synchronize with the reference clock. The frequency of FTCS can rapidly lock onto the reference frequency and the offset can be fully compensated within a single synchronizing cycle. Simulations and experiments are performed to validate the feasibility and superiority of FTCS. Compared with the proportional-integral clock servo, FTCS can achieve the rapid synchronized speed and better precision with low frequency of sending synchronization messages.