Closed-loop Tracking System Research Articles

Adaptive Output Feedback Control for the Trajectory Tracking of High-Speed Trains with Disturbance Uncertainties on the Basis of Neural Network Observers

The dynamic model of high-speed trains (HSTs) is nonlinear and uncertain; hence, with the decrease in the running interval of HSTs, an accurate and safe train operation control algorithm is required. In this study, an adaptive output feedback trajectory tracking control method for HSTs is proposed on the basis of neural network observers. The proposed method aims to solve problems, such as the immeasurable speed, model parameter disturbance, and unknown external disturbance of HSTs. In this method, a neural network adaptive observer is designed to estimate the velocity of an HST. Another neural network model is used to approximate the model uncertainties. Moreover, a robust controller is constructed by considering the train position and velocity tracking errors. In the proposed observer/controller, the bound function of estimator errors is introduced to increase the accuracy and safety of the tracking system. Furthermore, the adaptive update value of the neural networks, output weights, and bound function are performed online. All adaptive algorithms and the observer/controller are synthesized in nonlinear control systems. The error signals of the closed-loop trajectory tracking system are uniformly and eventually bounded through a formal proof on the basis of the Lyapunov methods. Simulation examples illustrate that the proposed controller is robust and has excellent tracking accuracy for system model parameter and external disturbance.

Piecewise analytic optimized ascent trajectory design and robust adaptive finite-time tracking control for hypersonic boost-glide vehicle

This paper proposes a novel robust real-time trajectory optimization method to obtain the analytic solutions for hypersonic boost-glide vehicle (HBGV), and the corresponding robust adaptive controller is designed to lead the tracking error to a small neighborhood near zero in finite time. The cost functions reflect the constraints and the direction of trajectory optimization about several essential traits, such as dynamic pressure, load factor, heat flux and thrust. Through the conditions on continuity and constraints at the joint points, the parameters of piecewise analytic ascent trajectory could be automatically modulated. Additionally, the real-time robustness of the analytic trajectory is guaranteed by replacing initial values with current states. Then, the referenced program pitch angle with far more practical application value for tracking problem is exported. Next, a controller integrating nonsingular terminal sliding mode control (NTSMC) with adaptive control is employed to guarantee that the closed-loop tracking system is robust under time-varying uncertainties with unknown bounds. The finite-time convergence is theoretically proved by detailed analyses on Lyapunov functions. In the end, simulation results demonstrate the feasibility of the piecewise analytic optimized ascent trajectory and the validity of the tracking controller in comparison with NTSMC and proportional derivative (PD) control.

Research on the application of RANSAC algorithm in electro-optical tracking of space targets

When the electro-optic tracking system is used for space target tracking, it is difficult to extract the target from the field of view occasionally due to the impact of electromagnetic interference, cloud cover or earth shadow etc., and the closed-loop tracking system can barely work in severe cases. At this point the predicted orbit can be used to guide the system to ensure smooth scanning and tracking. In this paper, random sample consensus (RANSAC) algorithm is introduced, which has been widely used in feature extraction in computer vision, to achieve higher prediction accuracy. The loss function of RANSAC algorithm is improved and the WRANSAC algorithm is proposed according to the distribution of observed data, which is used to deal with the limited observation data in real time to track the space target. After the algorithm is adopted, the fault tolerance of observation data is improved and the sensitivity of the model is reduced. The accuracy and robustness of the prediction results are much better than that of the least squares method. The validity of the WRANSAC algorithm is proved by the comparison between the predicted trajectory and the actual trajectory.

The Autosea project: Developing closed-loop target tracking and collision avoidance systems

Autonomous surface vehicles and maritime autonomous surface ships must rely on sense-and-avoid systems for navigating safely among other ships. The main objective of this paper is to present examples of such systems, and their verification in full-scale collision avoidance experiments as part of the research project “Sensor fusion and collision avoidance for autonomous surface vehicles” (Autosea). Lessons learned from the progression of experiments have led to increasing robustness of the methods, and provide a foundation for several important topics of further research in the near future.

Saturation based nonlinear PID control for underwater vehicles: Design, stability analysis and experiments

During sea missions, underwater vehicles are often exposed to changes in the parameters of their control systems and subject to external disturbances due to the influences of ocean currents. These issues make the design of a robust controller quite a challenging task. This paper focuses on the design of a nonlinear PID controller, based on a set of saturation functions for trajectory tracking on an underwater vehicle. The main feature of the proposed control law is that it preserves the advantages of robust control and remains easy to fine-tune in real applications. Using the Lyapunov concept, we prove the asymptotic stability of the closed-loop tracking system. The effectiveness and robustness of our proposed controller for trajectory tracking in depth and yaw dynamics is demonstrated through real-time experiments.

A Low-Cost Closed-Loop Solar Tracking System Based on the Sun Position Algorithm

Sun position and the optimum inclination of a solar panel to the sun vary over time throughout the day. A simple but accurate solar position measurement system is essential for maximizing the output power from a solar panel in order to increase the panel efficiency while minimizing the system cost. Solar position can be measured either by a sensor (active/passive) or through the sun position monitoring algorithm. Sensor-based sun position measuring systems fail to measure the solar position in a cloudy or intermittent day, and they require precise installation and periodic calibrations. In contrast, the sun position algorithms use mathematical formula or astronomical data to obtain the station of the sun at a particular geographical location and time. A standalone low-cost but high-precision dual-axis closed-loop sun-tracking system using the sun position algorithm was implemented in an 8-bit microcontroller platform. The Astronomical Almanac’s (AA) algorithm was used for its simplicity, reliability, and fast computation capability of the solar position. Results revealed that incorporation of the sun position algorithm into a solar tracking system helps in outperforming the fixed system and optical tracking system by 13.9% and 2.1%, respectively. In summary, even for a small-scale solar tracking system, the algorithm-based closed-loop dual-axis tracking system can increase overall system efficiency.

Adoption of a Closed-Loop Communication Tool to Establish and Execute a Collaborative Follow-Up Plan for Incidental Pulmonary Nodules.

PurposeWe designed a closed loop communication and tracking system (RADAR) to enable execution of a collaboratively developed care plan for follow up imaging of incidental pulmonary nodules (IPN). The system requires adoption by radiologists and referring providers. We assess radiologists’ adoption of RADAR and its impact on the clarity of radiologists’ follow up recommendations for IPN.MethodsThis Institutional Review Board-approved study was performed at a large, urban, tertiary care academic center performing 800,000 radiology examinations annually. Radiologists generate critical alerts for all newly discovered incidental pulmonary nodules using a previously described PACS-embedded software tool to track acknowledgement of receipt of critical alerts by ordering providers (i.e., usual care). RADAR (i.e., intervention) is a closed-loop communication tool, embedded in radiology PACS and enterprise provider workflow that enables establishment of a collaborative follow up plan (CFUP) between a radiologist and referring provider and helps automate the tracking and execution of CFUP. RADAR use is at the discretion of the interpreting radiologist. After implementation of RADAR for IPN in thoracic radiology (study period 3/9/2018–8/2/2018), we assessed RADAR adoption (primary outcome: #RADAR alerts for IPN/# of all alert for IPN). Secondary outcome was the clarity of follow up recommendation, defined as explicit documentation of the imaging modality and timeframe for follow up, as well as referring provider agreement with the recommendation. Trend over time was assessed with Cochran Armitage test.ResultsPost implementation, 106 of 183 (58%) IPN alerts were generated using RADAR. RADAR adoption increased by 75% during the study period (40% in first 3 weeks v 70% in last 3 weeks; ([70%−40%]/40%x100= 75%; p<0.001 test for trend). All RADAR alerts had explicit documentation of imaging modality and timeframe for follow up, compared to 71% for non-RADAR alerts for IPNs (p<0.001).ConclusionThoracic radiologists adopted a closed-loop communication system that allows for scheduling and automated tracking of pulmonary nodule follow-up recommendations. This system improved the quality of follow-up recommendations.

A Filtered Sun Sensor for Solar Tracking in HCPV and CSP Systems

Tracking systems with stringent performance are required to take advantage of solar energy produced through the use of high concentration photovolatics and concentrating solar power technologies. Closed-loop tracking systems use measurements provided by a sun sensor, which picks up direct and diffuse sunlight. High levels of diffuse sunlight produce increased levels of measurement noise at the output of the sensor, which in turn limits the maximal achievable gains in the closed-loop controller and consequently the tracking performance deteriorates. The goal of this paper is to present the advantages of equipping a four-quadrant photodiode sun sensor with infrared and linear polarizing optical filters. Experimental results show that these filters reduce the effect of diffuse radiation and allow increasing the performance of sun tracking systems regardless of the type of controller used in the solar tracker. Tracking experiments are presented under indoor and outdoor conditions employing algorithms currently used in solar trackers, including proportional-integral (PI), and proportional-integral-derivative (PID) controllers, and a recently proposed cascade control law. In all the cases, the best performance is obtained with the sun sensor equipped with an infrared filter. Experiments show that an infrared optical filter reduces the filtered mean squared tracking error up to 75% under artificial light conditions and 90% under direct sunlight.

Quadrotor trajectory generation and tracking for aggressive maneuvers with attitude constraints

Abstract This paper addresses the problem of performing quadrotor aggressive maneuvers that are attitude-constrained. The trajectory generation is formulated as a quadratic programming problem with linear constraints. Constraints at a specific time can be imposed on any linear combination of the quadrotor position and its derivatives. The under-actuation of the vehicle is explored to embed the attitude constraints into the trajectory generation via constraints on the desired quadrotor acceleration. A trajectory tracking controller is also proposed that guarantees the asymptotic stability of the closed-loop tracking system. Experimental and simulation results illustrate the application of the proposed method to quadrotor maneuvers involving a 360° flip.

Trajectory tracking for autonomous underwater vehicle: An adaptive approach

During missions at sea, underwater vehicles are exposed to changes in the parameters of the system and subject to persistent external disturbances. These issues make the design of a robust controller a quite challenging task. This paper focuses on the design of an adaptive high order sliding mode controller for trajectory tracking. The main feature of the proposed control law is that it preserves the advantages of robust control. Moreover, it does not need the knowledge of the upper bound of the disturbance and it is easy to tune in real applications. Using Lyapunov concept, asymptotic stability of the closed-loop tracking system is ensured. The robustness of the proposed controller for trajectory tracking in depth and yaw dynamics is demonstrated through real-time experiments.

Active attitude fault-tolerant tracking control of flexible spacecraft via the Chebyshev neural network

This paper describes a novel finite-time attitude tracking control approach for flexible spacecraft. This is achieved by integrating sliding-mode control and the active real-time fault-tolerant reconfiguration method. In this approach, the attitude error dynamics and the kinematics of the flexible spacecraft are first established. Then, a nonsingular terminal sliding-mode surface is designed, based on finite-time control theory. Applying the Chebyshev neural network, the uncertain dynamics induced by external disturbances and uncertain inertia parameters are approximated and estimated. The nominal control law and the compensation control law to obtain the active reconfiguration fault-tolerant controller are finally developed in normal and fault conditions, respectively. The closed-loop tracking system is proved to be uniformly ultimately bounded stable after a finite time. Numerical simulations are presented for a flexible spacecraft to illustrate the efficiency of the proposed controller.

Fuzzy Remote Tracking Control for Randomly Varying Local Nonlinear Models Under Fading and Missing Measurements

This paper proposes a novel remote tracking control strategy for a class of discrete-time Takagi–Sugeno fuzzy systems with randomly occurring uncertainties and randomly varying local nonlinear models . The outputs of the fuzzy system are collected through an unreliable sensor subject to missing measurements. Simultaneously, the outputs of the remote models are transmitted to the controller through wireless channels, in which the fading measurements may inevitably happen. By considering the Rice fading model and the Markovian packet dropouts model, an output-feedback controller is designed such that the closed-loop fuzzy tracking system is robustly stochastically stable and a prescribed $H_\infty$ remote tracking performance is achieved. Furthermore, sufficient conditions are obtained for the existence of admissible tracking controllers in terms of nonstrict linear matrix inequalities. To overcome the difficulty in computation, a modified cone-complementarity linearization algorithm is employed to cast the tracking controller design problem into a sequential minimization one, which can be readily solved by using standard numerical software. Simulation results demonstrate the effectiveness of the developed control algorithm for fuzzy remote tracking controller.

Model-free Adaptive Dynamic Programming Based Near-optimal Decentralized Tracking Control of Reconfigurable Manipulators

In this paper, a model-free near-optimal decentralized tracking control (DTC) scheme is developed for reconfigurable manipulators via adaptive dynamic programming algorithm. The proposed controller can be divided into two parts, namely local desired controller and local tracking error controller. In order to remove the normboundedness assumption of interconnections, desired states of coupled subsystems are employed to substitute their actual states. Using the local input/output data, the unknown subsystem dynamics of reconfigurable manipulators can be identified by constructing local neural network (NN) identifiers. With the help of the identified dynamics, the local desired control can be derived directly with corresponding desired states. Then, for tracking error subsystems, the local tracking error control is investigated by the approximate improved local cost function via local critic NN and the identified input gain matrix. To overcome the overall error caused by the substitution, identification and critic NN approximation, a robust compensation is added to construct the improved local cost function that reflects the overall error, regulation and control simultaneously. Therefore, the closed-loop tracking system can be guaranteed to be asymptotically stable via Lyapunov stability theorem. Two 2-degree of freedom reconfigurable manipulators with different configurations are employed to demonstrate the effectiveness of the proposed modelfree near-optimal DTC scheme.

A General Tracking Control Framework for Uncertain Systems With Exponential Convergence Performance

A difficult problem of exponential tracking control for uncertain systems even with external disturbance is investigated. The systems studied have a general/representative form with the lossless second-order differential systems and Euler-Lagrange systems included. A general control design framework is presented using observer technique. An observer-based estimator is first developed to precisely estimate and or reconstruct the uncertainty and the disturbance, and an estimator-based controller is then developed. Globally exponential stability of the closed-loop tracking system can be achieved by that controller. Moreover, the resulted estimation error of uncertainty can be stabilized with finite-time convergence. The key advantage of this control architecture is that the controller is able to achieve a perfect tracking performance with no overshoot observed and the settling time tuned to be as less as possible. The effectiveness of the approach is validated on a rigid-flexible coupling satellite example.

Trajectory exponential tracking control of unmanned surface ships with external disturbance and system uncertainties

Any unmanned surface ship is subject to system uncertainty, unknown parameters, and external disturbance induced by the wind, the wave loads, and the ocean currents. They may deteriorate ship's control accuracy. This paper aims to solve the trajectory tracking control problem of unmanned surface ships with disturbance and system uncertainty accommodated simultaneously. An estimator-based backstepping controller is presented with an estimator designed to provide a precise estimation of the disturbance and uncertainties. The proposed controller ensures the closed-loop tracking system to be globally exponentially stable. The trajectory tracking error and the estimation error of disturbance and uncertainties are globally exponentially stable. The key feature of the developed control scheme is that it is more robust to disturbances and system uncertainties. Simulation results are further presented to validate the effectiveness of the approach.

Nussbaum-Based Adaptive Fuzzy Tracking Control of Unmanned Surface Vehicles with Fully Unknown Dynamics and Complex Input Nonlinearities

In this paper, subject to both fully unknown dynamics and complex input nonlinearities including unknown control directions and dead zones, a Nussbaum-based adaptive fuzzy trajectory tracking control scheme of an unmanned surface vehicle is addressed by combining adaptive fuzzy backstepping technique with Nussbaum approach. The dead-zone input nonlinearity is firstly divided into input-dependent functions and time-varying input coefficients which can be treated as system uncertainties. Together with disturbances, unknown dynamics and uncertainties, the lumped nonlinearity is online approximated by employing an adaptive fuzzy approximator. Within the backstepping framework, a Nussbaum gain function is further designed to tackle unknown control directions, and thereby devising an adaptive fuzzy trajectory tracking control scheme which is constructed recursively to deal with complex input nonlinearities and fully unknown dynamics. Theoretical analysis reveals that all signals of the closed-loop tracking system are bounded and tracking errors can converge to an arbitrarily small neighborhood of zero. Simulation studies demonstrate the effectiveness and superiority of the proposed approach.

Tracking Control of Surface Ships With Disturbance and Uncertainties Rejection Capability

This paper investigates a difficult problem of tracking control manipulation for surface ships. External disturbances and system uncertainties are simultaneously addressed. The tracking law design is accomplished in a framework of backstepping control. First, a backstepping-based controller is presented to achieve trajectory tracking with desired tracking performance guaranteed. On the basis of this baseline feedback control law, an adaptive version of this controller is further synthesized to handle the uncertainties and disturbances. It is shown by the Lyapunov stability analysis that the closed-loop tracking system is guaranteed to be asymptotically stable. The desired trajectory is successfully followed with the tracking error asymptotically converging to zero. The effectiveness of the controller is validated through a numerical example.

&lt;b&gt;Development of a closed and open loop solar tracker technology

Solar energy is among the renewable energy sources that received greater addition in installed capacity. However, it accounts for a small fraction of the energy matrix of most countries. Electric energy generation by solar systems can be improved through tracking. This work aimed to develop and compare a closed and an open loop solar tracking system. The closed loop system was developed using Light Dependent Resistors. An algorithm was developed for the open loop tracker as a function of the geometric relation between the sun and the photovoltaic module. A simulation was run to compare this algorithm with a system using tracking at fixed time intervals, for clear sky conditions, with different tracking parameters and for five different latitudes. No significant difference was observed between the proposed open loop tracking algorithm and the fixed time interval algorithm for the tracking parameters evaluated. The open and closed loop solar tracking systems were compared experimentally in Rio das Ostras, Brazil (22.49 °S 41.92° W). An average gain of 28.5% was observed for the open loop tracking system over a latitude tilted system and 33.0% for the closed loop tracking system.

A Structure Simple Controller for Satellite Attitude Tracking Maneuver

This paper addresses a difficult problem of designing a control approach with simple structure to perform attitude tracking maneuver for rigid satellites. The satellite is subject to external disturbance torque and uncertain inertia parameters. An observer-based estimation law is first proposed to reconstruct the uncertain dynamics. It is shown that such estimation can be achieved with zero estimation error after finite time. A proportional–derivative (PD)-type controller including a classical PD control effort and a compensation control part is then presented. The compensation control is designed based on the estimated information, and applied to completely reject the uncertain dynamics. The closed-loop attitude tracking system is governed to be asymptotically stable. Moreover, the control performance can be achieved by tuning control gains in the theoretical framework of classic PD control theory. Simulation and experimental test are carried out to verify the effectiveness of the developed approach.

Event‐triggered output tracking control for wireless networked control systems with communication delays and data dropouts

This study addresses the event-triggered output tracking control under wireless network environments. First, an improved event-triggered communication scheme and a sampled-state-error dependent tracking model for wireless networked control systems is presented. In this scheme and model, (a) the sensor takes samples in a periodic manner; (b) an improved event-triggering condition is applied in the communications to determine whether the sampled data is transmitted to the controller or not; and (c) the closed-loop tracking system with a networked state-dependent controller is modelled as an augmented time-delay system. Second, by constructing a novel Lyapunov–Krasovskii functional, two theorems are derived with guaranteed H∞ tracking performance subject to imperfect wireless communications. The tracking performance is based on two permissible limits on the signal transmission. That is, the maximum allowable communication delay bound and maximum allowable number of successive data dropouts. Finally, a satellite tracking example is given to show the effectiveness of the proposed method.