Adaptive Control Technology Research Articles

Finite-time robust control of morphing aircraft based on time-varying observer

Morphable vehicles have strong nonlinear, strong coupling and strong time-varying characteristics in the process of variation, which brings great challenges to the design of their flight control systems. To address this problem, a time-varying gain extended state observer is proposed to accurately approximate the system coupling terms. Combining adaptive backstepping control technology and finite-time control theory, a finite-time bounded robust adaptive controller is designed. By designing the barrier Lyapunov function, the actual control law and the adaptive network update law are obtained step by step, ensuring that the system command tracking error can converge to a predetermined range within a finite time. Finally, the effectiveness of the designed control system is verified by attitude control simulation. The simulation results show that the morphable vehicle can track the command signal well in the process of variation and is basically not affected by the variation rate.

Active compliance control of grinding process for stripping enameled copper wire

The hairpin motor is among the motors used in eco-friendly automobiles. Unlike the random-winding method, this method features a square cross-sectional enamel coil formed into several hundred hairpins inserted into the stator. This offers an increased space factor, which leads to enhanced motor power. With the growing use of hairpin motors, there is an increasing demand for automated equipment in their production. With an aim to improve the manufacturing quality of hairpin motors, many countries are conducting research and development. The process of enamel removal is one of the key steps in hairpin-forming equipment and can significantly affect the performance of the motor. A precise machining process technology is required to improve the enamel removal process, achieve higher enamel removal rates, and reduce wire loss rates. Grinding is a technique used for enamel removal. In this study, an adaptive control algorithm was applied to the grinding process to enhance the enamel removal machining performance. During the machining process, the vertical position of the spindle was controlled to maintain a consistent machining depth for tracking the target grinding force. An experimental setup, which included a system for measuring the spindle torque to calculate the grinding force in real time, was created. To validate the performance of the adaptive control technology, experiments were conducted using this setup. Furthermore, experiments were conducted to observe the changes in the grinding force ratio based on the conditions of the grinding wheel. The correlation between the grinding force ratio and tool condition was analyzed, and based on this, the feasibility of assessing tool condition and determining the timing for tool replacement through real-time monitoring of the grinding force ratio was confirmed.

A Digital Twin System for Adaptive Aligning of Large Cylindrical Components

Most large aerospace cylindrical components still adopt a manual aligning method with low automation, large manual intervention, and heavy dependence on operator workers, resulting in the low quality and efficiency of large component aligning, which seriously prolongs the manufacturing time of aerospace products. To cope with this issue, based on closed-loop adaptive control and digital twin (DT) technologies, an adaptive aligning system for large cylindrical components, i.e., the DT aligning system, is proposed in this study. For the DT aligning system, through the DT multi-dimensional modeling, i.e., geometric modeling, physical modeling, functional modeling, and data modeling, it can be divided into a physical space, a virtue space, and twin data. Note that the association, mapping, and interaction between physical space and virtual space of the aligning system can be realized via the twin data, thereby realizing real-time virtual display, monitoring, and control of the large component aligning. In addition, based on the measured pose data, aligning stress, and predicted aligning error, an adaptive force/position control method for large component aligning is proposed, and it can achieve real-time decision-making and precise execution of the aligning process. Finally, through application validation, the DT process system can realize the real-time status perception and process execution decision during the large component aligning. Finally, through experimental validation, it is found that the proposed system, i.e., the DT aligning system, can improve the quality and efficiency of the large aerospace cylindrical component aligning, as well as the automation and intelligent level of the aligning system.

General output constraints control of interconnected nonlinear systems with sensor faults

This paper delves into the problem of generalized output-constrained control for interconnected nonlinear systems, where sensor faults are modeled as time-varying unknown functions. First, a barrier function related to an output transformation function is proposed, which can meet the diverse constraint requirements by adjusting some parameters and functions. Second, the sensor fault is described as an unknown time-varying function, and its difficulties to the controller are successfully overcome with the help of adaptive control technology. Then, an output related function is introduced into the controller to handle the interconnected functions without approximators, while retaining the uncertainties in the interconnected functions. Based on the dynamic surface control technology, an adaptive general output constraint fault-tolerant controller is proposed. With the aid of the Lyapunov stability theory, it rigorously proves that the output satisfies the pre-given constraint requirements, and all signals of the closed-loop systems are bounded. Finally, the numerical simulation is presented to illustrate the validity of the proposed algorithm.

Sampled‐data cooperative semi‐global robust practical output regulation for nonlinear multi‐agent systems with an uncertain leader

AbstractThis article explores the problem of sampled‐data cooperative robust practical output regulation for nonlinear multi‐agent systems whose leader system is unknown. In this study, the nonlinearities of the follower systems are not constrained by the linear growth condition. Based on the robust control technology and the adaptive control technology, a distributed output‐based sampled‐data control protocol is developed to deal with the uncertainty of the exosystem which can belong to any large known compact set. We first perform the coordinate transformation of closed‐loop system to obtain the so‐called augmented system, and then perform the stability analysis for this system. As a result, it is proven that the steady‐state tracking errors are in any small given neighborhood of the origin. Finally, the performance of the proposed controller is validated by a numerical example.

Efficiency of adaptive cruise control in commercial vehicles

AbstractThe evolution of autonomous vehicles hinges significantly upon the advancements in driving assistance systems. Adaptive cruise control, a pivotal component of these systems, warrants continuous real-world examination to assess its operational efficiency. The study investigates these systems integrated into diverse commercial vehicles with a specific focus on the following distances they provide. The findings reveal that camera-based systems offer shorter following distances relative to ISO standards, while radar-based and combined camera and radar-based systems provide larger following distances. The study contributes to understand adaptive cruise control technology and its alignment with safety standards, thereby aiding in the on-going development of self-driving vehicles.

Trajectory Tracking Control of Human Support Robots via Adaptive Sliding-Mode Approach.

In this article, the tracking problem of the adaptive sliding-mode control (SMC) design for human support robots based on a disturbance observer is investigated. First, a finite-time controller using nonsingular fast terminal SMC is proposed. Then, a robust disturbance observer is developed to estimate system uncertainties and disturbances. Simultaneously, to deal with the unknown bounded disturbance observer error, an adaptive control technology is developed. Furthermore, the proposed controller is synthesized to ensure that the tracking errors can be stabilized in finite time. Finally, simulations are performed to demonstrate that human support robots employing the proposed controller can converge to the desired trajectory.

Formalization and modeling of turbocode encoding/decoding processes for 5G communication systems

Improving the energy characteristics in 4G and 5G mobile communication systems is provided by the use of adaptive control technology for encoding, modulation and power parameters. The paper considers promising adaptive coding schemes in mobile communication systems. The article formalizes the process of optimizing the operation of the turbo code encoder and decoder by using adaptive selection of the size of state diagrams based on the proposed decoding uncertainty indicator. In contrast to the known methods of TC adaptation, the size of the TC encoder/decoder state diagram is adaptive depending on the signal-to-noise ratio in the channel and the values of the normalized number of changes in the sign of the a posteriori-a priori logarithmic relations of the likelihood functions about the transmitted data bits of the turbo code decoder. Analysis of the simulation results shows that the reliability of transmission is increased by choosing a rational size of the TC encoder/ decoder state diagram. The proposed formalization of the model of the TC functioning process is a further development of adaptive coding technologies while preserving the transmission system bandwidth and differs from those known in that various TC MLRS polynomials are used for adaptation, which determine the necessary structure and size of the TC encoder and decoder state diagram. The interleader parameters are selected as fixed. Simulation modeling was used to analyze the efficiency of optimizing the operation of the encoder and decoder of the turbo code by using adaptive size selection of state diagrams. For comparison, the fourth-generation LTE-Advanced Mobile Communication Standard was chosen. The simulation was carried out in Visual Studio 2019 the data transmission system with Turbo codes, modulator (demodulator) OFDM, channel with additive Gaussian white noise (ABGN) was modeled. The results of the work can be used in conjunction with other adaptation methods, such as coding rate adaptation, based on polynomials of TC component codes, in systems with multiparametric adaptation that function under conditions of complete or partial a priori uncertainty.

Analysis and Chaos Control and Synchronization of the Nonlinear Newton–Leipnik System Via Feedback Adaptive Control Techniques

This paper presents the system analysis and chaos control synchronization of the Newton–Leipnik system. Uniqueness and existence solutions (equilibrium points or fixed points) of Newton–Leipnik system have been discussed and local analysis of the system at each equilibrium points is studied. Lyapunov exponents and Kaplan–Yorke dimensions, bifurcation diagrams and poincare sections are analyzed and plotted to establish the presence of chaos in the system. Control feedback techniques are simulated in the nonlinear Newton–Leipnik system. Controlling chaos of systems to find the desired result are established. Synchronization methodologies of two identical integer-order Newton–Leipnik systems are yielded applying adaptive control technologies which have been verified through plotting the graphs of tracking the trajectories of master to slave systems, parameter identification results and synchronization of error dynamics diagrams of Newton–Leipnik systems. These findings offer valuable insights and tools applicable to various scientific and technological domains. These results highlight the originality of our study and deepen our understanding of chaos in Newton–Leipnik systems, offering practical applications and enhanced insights for researchers and scientists in chaos analysis.

Fuzzy-based adaptive event-triggered control for nonlinear cyber-physical systems against deception attacks via a single parameter learning method

This paper investigates the adaptive fuzzy control issue of cyber-physical systems (CPSs) against unknown deception attacks and external disturbance. Based on the backstepping design framework, the uncertainty term composed of the approximation error term generated by the fuzzy logic system, the external disturbance and the deception attack signals are regarded as a whole in the recursive design process. Then, by combining the single parameter learning method with the adaptive fuzzy technique, the uncertain terms containing approximation error, disturbance and injection attacks can be transformed into the form of linear parameterization with only one unknown scalar parameter, which greatly reduce the calculation process. In addition, the dynamic event-triggered adaptive control technology can be integrated into the control design to reduce the amount of data transmission. Theoretical analysis shows that all the signals in the closed-loop system are bounded under the proposed control scheme, and the Zeno behavior is excluded. Finally, the two-stage chemical reactor and mass-spring-damper systems are employed to demonstrate the validity of the proposed adaptive fuzzy control solution.

Optimal energy management strategy for dual-power coupling tractor based on the adaptive control technology.

Hybrid tractors (HT) are regarded as the efficient agricultural machine due to their energy conservation performance and faster torque response to deal with load fluctuations. However, the strategy to allocate the battery and fuel energy for demand power should be discussed. In this paper, an on-line management strategy of the HT is proposed to optimize the energy consumption of engine and motor and to reduce torque ripple for power units. A new architecture for replacing power shift and continuously variable transmission technology is proposed. Then, the modified equivalent consumption minimization strategy (ECMS) is used to optimize the torque distribution in which the equivalent factor is further calculated for the real-time process. Besides, the modification of ECMS in variable working conditions can effectively analyse the torque distribution between the motor and engine. The numerical test is implemented that the effectiveness of the proposed energy strategy is validated in plowing conditions. The consequences indicated that the proposed power distribution strategy can adaptively allocate the torque demand according to the fluctuation load. Comparing with the traditional rule-based strategy, the proposed strategy can reduce 6.2% of the energy, and decrease torque ripple with the proposed tractor architecture.

Sampled‐data robust practical tracking of Euler‐Lagrange systems with an uncertain exosystem

AbstractThis article focuses on the problem of sampled‐data practical tracking for Euler‐Lagrange systems subject to uncertain parameters. We assume that the system matrix of the exosystem and the Euler‐Lagrange system both contain unknown parameters, which is clearly more practical. The existence of unknown system parameters invalidates existing control strategies and poses a major challenge to the solvability of the problem. With the help of the internal model principle and the adaptive control technology, we propose a novel sampled‐data dynamic compensator to overcome the challenge of unknown parameters in exosystems. In particular, a virtual sampling adaptive control input is proposed to deal with uncertainties in the exosystem matrix. Then, a sampled‐data control law is constructed to guarantee that, by any fast predefined rate, the tracking error exponentially approaches any small predefined ranges of the origin, thus ensure the tracking performance. Finally, we apply our result to a three‐link robot manipulator system.

Adaptive fault-tolerant fixed-time cruise control for virtually coupled train set

In the cruise control of the virtual coupled train set (VCTS), the control algorithm with high stability, high accuracy, and fast convergence speed is the basic requirement for the smooth and efficient operation of the VCTS. To this end, this paper studies the problem of fixed-time cruise control for VCTS. To begin with, by analyzing the dynamic evolution of the VCTS in an actual environment, a second-order VCTS train-following dynamic model is formulated with considering actuator faults, uncertain resistance, unknown disturbances, and control input saturation. Then, an improved barrier functions-based fixed-time sliding model control method is proposed to deal with the state constraints (i.e., safe distance and speed limit). To deal with parametric uncertainty, adaptive fault-tolerant control and core function technologies are integrated into the same framework. Furthermore, by using a function approximation method to handle the control input saturation, an adaptive fault-tolerant fixed-time cruise controller is designed which not only guarantees the fixed-time stability of the VCTS but also copes with parametric uncertainty, state constraints, and input saturation. Finally, the effectiveness of the proposed method is validated in simulation analysis.

Distributed Adaptive Path-Following Control for Distance-Based Formation of Fixed-Wing UAVs under Input Saturation

This paper investigates the distance-based formation and cooperative path-following control problems for multiple fixed-wing unmanned aerial vehicles (UAVs). In this study, we design the distance-based formation control structure to achieve the virtual leader and followers pre-defined rigid formation pattern, ensuring simultaneously relative localization. A path-following control strategy based on adaptive dynamic surface and neural network control technology is proposed to approximate the uncertain disturbances of the environment and unmodeled dynamics. And the longitudinal and lateral subsystems’ adaptive fault-tolerant controllers are designed, respectively, to achieve the fault-tolerant control of UAVs’ formation in three-dimensional environments. Furthermore, the adaptive sliding mode controller with an auxiliary controller is designed to realize the UAVs path following with limited input saturation. Finally, simulation examples are given to clarify and verify the effectiveness of the theoretical results.

Observer-Based Adaptive Fuzzy Control of Nonstrict Feedback Nonlinear Systems With Function Constraints

In this paper, an adaptive fuzzy tracking control scheme based on fuzzy state observer is proposed for a class of uncertain non-strict feedback nonlinear systems with function constraints. In the first place, based on the approximation characteristic of fuzzy logic systems (FLSs), a fuzzy state observer is designed to estimate the immeasurable state variables in the controlled system. Next, under the framework of adaptive backstepping control technology, FLSs are selected not only to approximate unknown nonlinear functions, but also to avoid algebraic loop problem caused by non-strict feedback structure. At the same time, asymmetric Barrier Lyapunov functions (BLFs) are selected to solve the problem that system states are subject to function constraints, which are related to states and time. Then, Lyapunov stability theory is utilized to prove the stability of the controlled system, the realizability of function constraints and the convergence of output tracking errors. Finally, a simulation is given to check the effectiveness of the proposed control scheme.

A yaw stability-guaranteed hierarchical coordination control strategy for four-wheel drive electric vehicles using an unscented Kalman filter

A novel hierarchical coordination control strategy (HCCS) is offered to guarantee the stability of four-wheel drive electric vehicles (4WD-EVs) combining the Unscented Kalman filter (UKF). First, a dynamics model of the 4WD-EVs is established, and the UKF-based estimator of sideslip angle and yaw rate is constructed concurrently. Second, the equivalent cornering stiffness coefficients are jointly estimated to consider the impact of vehicle uncertainty parameters on the estimator design. Afterwards, a HCCS with two-level controller is presented. The sideslip angle and yaw rate are controlled by an adaptive backstepping-based yaw moment controller, and the computational burden is relieved by an improved adaptive neural dynamic surface control technology in the upper-level controller. Simultaneously, the optimal torque distribution controller of hub motors is developed to optimize the adhesion utilization ratio of tire in the lower-level controller. Finally, the proposed HCCS has shown effective improvement in the trajectory tracking capability and yaw stability of the 4WD-EVs under various maneuver conditions compared with the traditional Luenberger observer-based and the federal-cubature Kalman filter-based hierarchical controller.

Development of resistance spot welding technology applying multi-stage adaptive control for narrow pitch spot welding of high strength steel sheets

In order to expand the application of high strength steel sheets to automotive bodies, stabilizing nugget diameter of resistance spot welds is required in the presence of several industrial disturbances. This study aims to ensure the nugget diameter of high strength steel sheets regardless weld spacing by utilizing adaptive control technology based on real-time feedback of heat quantity. Short weld spacing leads to expulsion from the sheet surface applying conventional adaptive control welding for mild steel sheets, whereas decrease in nugget diameter due to reduction of effective welding current for high strength steel sheets. On the other hand, two-stage adaptive control method enables to ensure nugget diameter regardless of steel strength even with 10 mm weld spacing, in which heat quantity was controlled independently in each stage of welding. The mechanism of these phenomena was revealed by verifying the influence of physical properties of steel and welding current pattern on the shunting phenomena using numerical simulation.

Influence of adaptive signal control technology (ASCT) on severity of intersection-related crashes

Adaptive signal control technology (ASCT) is an advanced traffic control system that optimizes signal timing based on real-time traffic demand. ASCT can potentially improve the operation and safety of intersections by establishing dynamic coordination among signalized intersections in real-time. This study used a binary Bayesian logit model with random effects, which accounts for unobserved heterogeneity, to explore the impacts of ASCT on the severity of intersection-related crashes in Florida. Two distinct ASCT types (Type I and II) were analyzed to assess their impacts on crash severity. The analysis revealed that ASCT reduced the likelihood of a fatal plus injury (FI) crash by 14.6%. This reduction was significant at a 90% Bayesian credible interval (BCI). Also, each ASCT type (Type I and II) showed a potential reduction in the likelihood of a FI crash, although the decrease was not significant at a 90% BCI. Other factors such as driving under the influence, angle crashes, dark lighting conditions, posted speed limit, and median along a minor approach, were associated with a higher risk of a FI crash. Transportation agencies could use the study results to justify the deployment and expansion of ASCT at signalized intersections with a high frequency of severe crashes.

A multi-objective calibration framework for capturing the behavioral patterns of autonomously-driven vehicles

Calibration of car-following (CF) models is considered a very important task towards reproduction of individual vehicle behaviors and collective traffic phenomena. In most works, calibration is performed on trajectories of leading and following vehicles either on speed or spacing quantities, with the combination of the two plus the acceleration quantity to be considered as the most appropriate according to the literature. With the advent of adaptive cruise control (ACC) technology, there are intrinsic behavioral differences between human- and ACC-driven vehicles that are visible in experimental observations. Some examples include constant headway for ACC-enabled vehicles, string instability, hysteretic behavior, human-like response time and others. Since calibration is performed only on basic vehicle dynamics, i.e., the spacing, speed and acceleration, even after proper parametrization we cannot be certain that CF models will be able to reproduce some or all of the above phenomena and to what extend. The aim of this work is to propose a multi-objective calibration framework validated on empirical observations of car platoons. Furthermore, it investigates if, and to what extent, the traffic dynamics and behavioral patterns of ACC-driven vehicles can be reproduced. Two state-of-the-art CF models are tested with the empirical dataset. The results indicate that the proposed framework leads to acceptable errors and comparable performance, facilitating the models to capture phenomena in a way that is not possible until now, using the calibration on basic vehicle dynamics.

Adaptive fault‐tolerant control of nonlinear systems based on tuning functions

AbstractThis article investigates the tracking control problem of adaptive fault‐tolerant control (AFTC) for a class of strict‐feedback nonlinear systems with actuator/sensor faults and unmatched disturbances. The sensor/actuator faults include bias, drift, loss of accuracy, and loss of effectiveness. Our main control objective is to investigate an adaptive fault‐tolerant control algorithm with the help of tuning functions, adaptive control technology, fuzzy logic systems (FLSs) and so on. For unknown nonlinear functions and fault items, FLSs and adaptive control technology are utilized to approximate them. Furthermore, over‐parameterization problem existed in the backstepping‐based controller design is solved by introducing the tuning functions. Theoretical analysis proves that our proposed AFTC scheme can ensure that all the signals in the closed‐loop system are bounded and the tracking error remains within a small range of zero even if a series of faults mentioned above occur. In the end, the simulation results show that the presented AFTC strategy is feasible and effective.