Influence Of External Disturbances Research Articles

Experimental studies of the influence of elastic-dissipative parameters of engine mounting units on the dynamic characteristics of the “wing model – elastic pylon – engine” system

A feature of modern heavy transport aircraft is their layout with engines on elastic pylons under the wing, with the fuel tanks located in the wing consoles. In this case, the main elastic tones of the aircraft’s own oscillations, which determine its dynamic response to external disturbing influences, include the so-called motor tones (vertical and horizontal (lateral) oscillations of engines on elastic pylons). A new type of flutter has appeared – pylon, which for some aircraft determines the critical flutter speed of the aircraft as a whole. The main reason for this phenomenon is the low oscillation damping of the engine on the pylon under the wing. Therefore, research aimed at modernizing the engine mounting points on the pylon in order to reduce the level of elastic oscillations during aircraft operation seems relevant. One of the possible ways to solve this problem is to use the concept of a freed engine, when the engine attachment points to the pylon are modernized, providing more effective damping of engine oscillations. In order to confirm the possibility of practical implementation of these solutions, corresponding experimental studies were carried out on an experimental setup developed by the authors. A design of engine mounting units has been developed that allows specified displacements of the engine relative to the pylon during forced elastic oscillations of the system, which includes a hinged suspension, installation of additional elastic elements and hydraulic dampers.The article presents the results of studies of the influence of elastic-dissipative parameters (partial frequency of natural oscillations and partial decrement of oscillations) of an engine mount on an elastic pylon on the dynamic characteristics of the dynamic system “wing model – elastic pylon – engine”. It is shown that by introducing specially designed engine suspension units on pylons, it is possible to significantly change the dynamic characteristics (frequencies and amplitudes of natural oscillations) of the elastic system as a whole. Thus, the amplitudes of oscillations of the engine’s center of mass in the region of motor tones decrease by 3...7 times during forced harmonic oscillations.

Reachable set performance and quantized sampled-data synchronization analysis of neural networks under random packet dropouts via enhanced looped functional

The study aims to present the synchronization concerns of neural networks with stochastic packet dropouts utilizing a quantized memory sampled-data control (QMSDC) scheme and the problem of reachable set analysis (RSA) for NNs under the influence of external disturbances are discussed. To do this, a novel free-weighting matrix integral inequality (FWMII) is proposed with an augmented Lyapunov-functional. Furthermore, at this time, we show that the proposed inequality is less conservative due to the delay information. In the meantime, a novel enhanced looped function is created that utilizes not only sampling information but also incorporates both transmission delay information and a quantized sampling pattern. Next, using the proposed FWMII technique, several sufficient conditions in terms of linear matrix inequalities (LMIs) are derived to suggest how an augmented closed-loop system can achieves stochastic mean-square exponential synchronization under random packet loss situations. Finally, the proposed approach demonstrates its usefulness and superiority by comparing it with existing methods through numerical simulation of the secure communications.

Vessel Dynamic Positioning System Mathematical Model

This study aims to examine two potential approaches for addressing the challenge of synthesizing control laws in the Dynamic Positioning (DP) system. Both approaches pertain to the same ship model but are rooted in distinct ideologies concerning how to account for the influence of external disturbances on a closed system. The findings of this investigation could offer valuable insights for enhancing DP systems and formulating more efficient management strategies in maritime conditions. The research delves into the structure and principles of the DP system as a sophisticated control complex, identifying associated challenges in its application. Despite numerous implemented projects and considerable developer efforts, sustaining a ship in a specified position during rough seas remains a formidable task, partly due to the ship’s lack of energy armament. Exploration in the realm of regulatory system development has yet to yield the anticipated results. The present study constructs a mathematical model depicting the dynamics of a ship during positioning, considering two versions of automatic control laws aimed at stabilizing the ship’s position. The second model demonstrates superior efficiency in the control system, surpassing the first by at least 14%. A comparative analysis of two control system options with filtering properties in dynamic positioning mode for the vessel was conducted. For better results, it is recommended to implement filtering on the relevant data source before this procedure on a specific data consumer. This preliminary testing helps to remove duplicate and inaccurate data, reducing the load on the data link. Final filtering should be performed on high-performance systems. In summary, the originality and novelty of this article stem from its comparative analysis of control laws, exploration of DP system dynamics, acknowledgment of existing challenges, and practical recommendations for data filtering in dynamic positioning. The study brings a tangible contribution to the field, paving the way for advancements in the development of DP systems management and control methods.

Adaptive Set-Membership Filter Based Discrete Sliding Mode Control for Pneumatic Artificial Muscle Systems With Hardware Experiments

Pneumatic artificial muscle (PAM), featuring good flexibility and safety, has been widely used in rehabilitation and bionic robots. However, the complex hysteretic nonlinearities and uncertainties of the PAM cause great difficulties and challenges to the accurate modeling and controller design, especially when confronted with unknown external disturbances in applications. This paper proposes a robust control strategy with disturbance compensation for the hysteresis compensation and trajectory tracking of PAMs. Considering the high hysteretic nonlinearity of the PAM, a modified Prandtl-Ishlinskii model is used as a feedforward hysteresis compensator. For the linearized system, adaptive set-membership filtering (ASMF) is used to estimate the nonlinear terms and external disturbances of the overall system. A sliding mode controller (SMC) with disturbance compensation is designed and cascaded to the feedforward hysteresis compensator in series. The stability of the closed-loop system is theoretically proved. The proposed method guarantees that the tracking error of the PAM system is bounded. Finally, the effectiveness and robustness of the proposed controller are verified via a series of experiments on an in-house built testbench for PAMs. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —With the increasing demand on human-robot interaction, the safety and compliance of robots have become one key requirement. PAM is a compliant actuator, exhibiting good flexibility, safety, and clean energy. PAM is widely used in rehabilitation robots, whereas its strong hysteresis nonlinearity and sensitivity to external disturbances affect its motion accuracy. This paper proposes an ASMF-based discrete SMC, which uses an inverse hysteresis model to compensate for the strong hysteresis of the PAM and uses ASMF to estimate the lumped disturbance of the system. Compared with the other filters, ASMF is unique in that its estimation error is bounded, which is very useful in the stability proof of the overall system. The effectiveness of the proposed controller is experimentally verified. Experimental results show that PAM’s hysteresis can be efficiently compensated, and the influence of external disturbances can be attenuated by the proposed controller, resulting in improved motion accuracy and robustness. In future work, efforts will be directed towards the modeling and control of PAMs in multi-DOF robots.

Stages and main tasks of the century-long control theory and system identification development. Part IV. Methods and problems of designing robust control systems

The article provides a review of the most important methods and problems in the design of robust discrete control systems. In this case, the main attention was focused on the problems of suppressing limited external disturbances, information about which is presented only in the form of a limitation on their maximum value. The use of invariant ellipsoids is considered as the first mathematical apparatus for describing the characteristics of the influence of external disturbances on the trajectory of motion of dynamic systems. Theorems on the representation of invariant ellipsoids in the form of linear matrix inequalities (LMI) are formulated, which are further used to synthesize discrete state controllers that suppress external disturbances. The solution to a more general problem of robust suppression of limited disturbances based on the use of LMI in the presence of system uncertainties in the parameters of the mathematical model of the control object is considered. The use of H∞-control theory is considered as a second mathematical apparatus for suppressing external l2-limited external disturbances. In this case, the optimality criterion consists in minimizing the maximum ratio of the l2-norm of the vector of output stabilized coordinates to the l2-norm of the vector of input disturbances. The problem is solved by reducing it to the problem of robust control of a discrete dynamic system in space H∞ based on the Two-Ricatti approach. The standard H∞-optimization problem is also considered.

A Study on Robust Finite-Time Visual Servoing with a Gyro-Stabilized Surveillance System

This article presents the design and validation of a novel visual servoing scheme for a surveillance system. In this system, a two-axis gimbal mechanism operates the rotation of a camera which is able to provide visual information on the tracked target for the control system. The control objective is to bring the target’s projection to the center of the image plane with the smallest steady-state error and a smooth transient response, even with the unpredictable motion of the target and the influence of external disturbances. To fulfill these tasks, the proposed control scheme is designed consisting of two parts: (1) an observer estimates simultaneously the matched and unmatched disturbances; and (2) a motion control law guarantees the finite-time stability and visual servoing performance. Finally, experiments are conducted for validation and evaluation. The proposed control system shows its consistency and ought to perform better than previous approaches.

Computational approach based on use of multilayer neural networks in classification of rail line states

The article considers the issue of classification of the states of rail lines using multilayer neural networks. It is shown that with significant external disturbing influences, the most promising direction is the retraining of classification models using neural networks. The representativeness of the sample is proposed to be realized by applying the scaling of informative features. It is proposed to minimize classification errors by gradient optimization methods. In the work during classification of rail lines states by neural networks, at the first stage, artificial classes of states are formed. At the second stage, the classification of states by the trained neural network is considered, classification errors are identified. On the basis of these errors the network is retrained until acceptable results are obtained. The article presents neuron learning algorithms: Hebb’s algorithm, error backpropagation method (for training a multilayer neural network), Konohen’s, Hopfield’s, Hamming’s algorithm and network. In the presented revision of the classification model, the correction is carried out according to the Widrow-Hoff algorithm.

Prescribed-time event-triggered fault-tolerant formation control of multiple UAVs under tracking error constraints

This paper studies an event-triggered fault-tolerant tracking control strategy design of multiple quadrotor UAVs (MQUAVs) formation subject to the composite influence of external disturbance, tracking error constraints and actuator faults. A prescribed time prescribed performance function is employed to solve tracking error constraints and it ensures the tracking error enters into the constraint boundary in the prescribed time. A first-order filter is designed to solve the problem of computational explosion caused by reference trajectory and unknown external disturbance. The adaptive method is used to deal with the unknown parameters and the comprehensive uncertainty which contains actuator faults and external disturbance. Furthermore, the event-triggered controller is designed to achieve the formation tracking with the reduction of update number of controller to save resources. The bounded stability of the tracking error is proved via the Lyapunov theory. At last, the effectiveness of the control strategy is verified by simulation.

Integral BLF-Based Adaptive Dynamic Event-Triggered Boundary Control for a Flexible Riser System.

For the flexible riser systems modeled with partial differential equations (PDEs), this article explores the boundary control problem in depth for the first time using a dynamic event-triggered mechanism (DETM). Given the intrinsic time-space coupling characteristic inherent in PDE computations, implementing a state-dependent DETM for PDE-based flexible risers presents a significant challenge. To overcome this difficulty, a novel dynamic event-triggered control method is introduced for flexible riser systems, focusing on optimizing available control inputs. In order to save computational costs from the controller to the actuator, a dynamic event-triggered adaptive boundary controller is designed to effectively reduce boundary position vibrations. Additionally, considering external disturbances, an adaptive bounded compensation term is incorporated to counteract the influence of external disturbances on the system. Addressing boundary position constraints, a new integral barrier Lyapunov function (iBLF) tailored specifically for flexible riser systems is introduced, thereby alleviating conservatism in the controller design of flexible risers modeled by PDEs. At last, the validity of the proposed method is demonstrated through a simulation example.

Unmeasurable flexible dynamics monitoring and tracking controller design for guidance and control system of hypersonic flight vehicle

The guidance and control system (GCS) is an important and indispensable component of hypersonic flight vehicle (HFV), and it can be viewed as a special cyber–physical system (CPS). However, the monitoring of the HFV dynamics is difficult since the inertial navigation equipment can only provides the information of acceleration and angular rate. In this case, the flexible states of HFV are difficult to be measured. This paper proposes a sliding mode observer (SMO) based GCS design method for HFV. With considering the measurement difficulties, the flexible states of HFV are assumed to be unmeasurable. Then a SMO is designed to estimated them. Combined with the actual flight environment of HFV, the measuring devices are assumed to be suffering from disturbance, then the SMO should not only guarantee the estimation error stable, but also reduce the influence of external disturbances. What is worse, the input of HFV is suffering from input delay, which brings more difficulties to the controller design. By state transformation,input delay model of HFV is transformed into a delay free model,then a SMO based robust controller is proposed for HFV based on the stable inversion controller design strategy. By the proposed SMO based controller, the GCS can be constructed for HFV. Numeral simulation are carried on HFV, and simulation results show shat, the designed SMO can realize the monitoring of flexible states of HFV and the designed GCS can get a good tracking performance.

Adaptive output-constrained finite-time formation control for multiple unmanned surface vessels with directed communication topology

This paper tackles the intricate task of leader-following formation control for multiple unmanned surface vessels (USVs) operating over a directed communication network. Our investigation takes into meticulous consideration several critical variables, including prescribed output constraints, the presence of enigmatic dynamics, and the pervasive influence of external disturbances on each individual USV. Our methodology commences with the introduction of an ingenious output transformation technique, which adeptly converts constrained output variables into their unconstrained counterparts. Subsequently, we craft a novel distributed tracking error metric, artfully harnessing the potential of the transformed output. We build an adaptive, non-singular finite-time formation controller, firmly rooted in the backstepping framework. This controller seamlessly integrates vital components such as virtual velocity control, command filters, neural networks, and parametric adaptive strategies, which is underpinned by our meticulous attention to maintaining C1 continuity within our proposed virtual control law. Furthermore, we introduce the concept of minimum parameter learning, a strategic inclusion aimed at streamlining the computational demands of our controller. Significantly, any potential output overshoot resulting from minimum parameter learning is adeptly managed through our innovative output-constrained control strategy. To substantiate the effectiveness and robustness of our approach, we provide an exhaustive stability analysis, which offers conclusive evidence of our controller’s performance under a diverse array of conditions.

On error-driven nonlinear ESO based control design with application to air–fuel ratio control of engines

In this paper, the tracking control problem of the uncertain control system is studied in the frame of uncertainties estimation and compensation. To eliminate the influence of external disturbances and internal uncertainties on the control system, the error-driven nonlinear extended state observer (EDN-ESO), whose gain is set as an increasing function with respect to the absolute value of estimation error of the system output, is proposed to improve the estimation performance for the “total disturbance”. Next, both the estimation error of proposed ESO and the tracking error of system output are proven to be bounded by selecting the lower bound and variation range of ESO’s bandwidth. Moreover, the convergence of the estimation error as well as the tracking error to zero is proven under certain conditions. Finally, the proposed design method is applied to the air–fuel ratio control system of gasoline engines, and the experimental results show that the proposed EDN-ESO can effectively adjust the observer gain, so as to enhance the tracking performance.

Bipartite Consensus Problems for Directed Signed Networks with External Disturbances

The intention of this paper is to explore the distributed control issues for directed signed networks in the face of external disturbances under strongly connected topologies. A new class of nonsingular transformations is provided by introducing an output variable, with which the consensus can be equivalently transformed into the output stability regardless of whether the associated signed digraphs are structurally balanced or not. By taking advantage of the standard robust H∞ control theory, the bipartite consensus and state stability results can be built for signed networks under structurally balanced and unbalanced conditions, respectively, in which the desired disturbance rejection performances can also be satisfied. Furthermore, the mathematical expression can be given for the terminal states of signed networks under the influence of external disturbances. In addition, two simulations are presented to verify the correctness of our developed results.

Design of fuzzy sliding mode controller for islanded AC/DC hybrid microgrid with cyber‐attacks

AbstractThis paper presents a fuzzy sliding mode control method for voltage control of islanded AC/DC hybrid microgrid. The T‐S fuzzy model is utilized to approximate initial non‐linear dynamic model of the microgrid. The fuzzy rules and membership functions are designed according to the coupling relationship between AC part and DC part. To reduce the influence of external disturbance and cyber‐attacks, an integral sliding mode controller is considered. Furthermore, a sufficient condition is proposed with attenuation performance to ensure the asymptotic stability of sliding motion. The set of gain matrices can be acquired via solving the linear matrix inequalities deduced from the Lyapunov stability analysis. The reachability to the proposed sliding mode surface can be guaranteed via switching control law based on a Lyapunov function. In addition, to eliminate chattering performance of the sliding mode control theory, the fuzzy logic controller is designed to optimize the switching region in boundary layers of saturation functions. Finally, the simulation results for the islanded AC/DC hybrid microgrid are implemented to verify the robustness and effectiveness of the designed fuzzy sliding mode control method.

A reinforcement learning integral sliding mode control scheme against lumped disturbances in hot strip rolling

In the hot strip rolling production process, due to the influence of external disturbances and unmodeled errors which are defined as lumped disturbances (LDs), the looper operating angle and strip tension may not satisfy the requirements of normal production under the set values, which may lead to the product not satisfying the requirements. In this paper, an advanced reinforcement learning (RL) algorithm combined with integral sliding mode control (ISMC) is utilized to deal with LDs, and then the robustness of the system is improved. Firstly, the hot strip rolling is a complex nonlinear system, the looper model is linearized to be approximated around the operating point for simplicity. Secondly, the ISMC is addressed for LDs in hot strip rolling; meanwhile, due to the chattering phenomenon in conventional sliding mode control, a novel reaching law is designed; whereafter an off-policy RL algorithm is adopted to obtain the optimal controller. Finally, the effectiveness and superiority of the addressed method are elaborated by an example.

A novel collaborative control algorithm for maximum power point tracking of wind energy hydraulic conversion system

AbstractWind has been admitted as one of the most promising renewable energy resources in multinational regionalization policies. However, the energy conversion and utilization are challenging due to the technique reliability and cost issues. Hydraulic wind turbine (HWT) may solve the above problems. HWT is taken as a research object, and the maximum power point tracking (MPPT) control strategy is proposed collaborating with active disturbance rejection control (ADRC) and linear quadratic regulator (LQR) control methods, to solve multiplicative nonlinearity problems in the plant models and the influence of external disturbance on control performance in the MPPT control process. A nonlinear simulation model is built to explain the main findings from the experiments and obtain a better understanding of the effect of time‐varying system parameters and random fluctuation in wind speed. The collaborative control algorithm is experimentally verified on a 24‐kW HWT semi‐physical test platform that results in a promising energy conversion rate, plus the hydraulic parameters can satisfy the demand, accordingly. Ultimately, the potential challenges of implementing this technique in a smart wind energy conversion system are discussed to give a further design guidance, either theoretically or practically.

Reinforcement-Learning-Based Composite Optimal Control for Looper Hydraulic Servo Systems in Hot Strip Rolling

The control scheme of the looper angle plays an essential role in hot rolling, which is directly related to the tension maintenance of the strip. The conventional scheme uses a proportion–integration–differentiation (PID) controller to control the servo valve to drive the hydraulic actuator. For different steel types and production temperature changes, the PID control mainly relies on empirical parameter adjustment, which may bring inaccuracy or inefficiency. The objective of this article is to propose a reinforcement-learning-based looper hydraulic servo optimization control scheme to automatically tune the control gain to optimum. First, the modeling error caused by variable parameters and the influence of external disturbance are considered, and the corresponding control model of the looper system is given. Subsequently, a feedforward controller with a radial basis neural-network-based disturbance observer is used to deal with modeling errors and disturbances. A feedback controller with off-policy reinforcement learning is applied in the meantime. The proposed control scheme can realize uniformly ultimately bounded of the system with Lyapunov theory. Simulation results verify the effectiveness of the proposed method.

Особенности функционирования СВЧ-радиометров в условиях внешних помех.

The influence of external disturbances on the sensitivity and dynamic range of the microwave radiothermograph is considered. The results of an experimental study of the interference situation in the range up to 3 GHz are presented. The diagram of the spectral density of interference adjacent to radio astronomy windows is analyzed. The features of real observed disturbances are investigated. The classification of possible disturbances according to their characteristics is given. Algorithms for discrimination of various types of interference are considered. The sensitivity and dynamic range of the microwave radiometer are evaluated using the pulse noise suppression algorithm.

Fixed time prescribed performance dynamic positioning control design for surface vessels

This paper addresses the problem of fixed time dynamic positioning (DP) control for surface vessels under the influence of external disturbances, while considering input and output constraints. Using the hyperbolic tangent function, a saturation handling method with an auxiliary control system is constructed, which can handle the saturation constraints of both the control input and its rate of change within a same control framework. By incorporating an auxiliary sliding mode variable, a fixed time disturbance observer (FTDO) is developed to estimate external disturbances. This FTDO ensures that the estimation error converges within a fixed time and provides users with the flexibility to determine the desired convergence time. Moreover, a nonlinear function is introduced in the FTDO to reduce the possibility of singular problems in the control system. Combining the developed FTDO, prescribed performance control strategy and backstepping control technique, a novel DP control strategy is proposed, which not only ensures that the positioning error satisfies the output constraint requirements within a fixed time but also guarantees the fixed time stability of the closed-loop system. Finally, to validate the effectiveness of the proposed DP control law, numerical simulation analysis is carried out on a supply vessel.

Development of trajectory-tracking maneuvering system for automatic berthing/unberthing based on double deep Q-network and experimental validation with an actual large ferry

The development of an automatic berthing and unberthing system is essential for realizing autonomous ship navigation systems. Although numerous berthing/unberthing methods using neural networks (NNs) have been proposed in recent years, whether NNs trained via numerical simulations including modeling errors can be used for the automatic berthing/unberthing of actual ships in natural external disturbances is not clear. Hence, in this study, a maneuvering system for automatic berthing/unberthing was developed using a NN that solves the trajectory-tracking problem. The proposed method considered future targets as discrete points in learning, such as to absorb the modeling error and reduce the influence of external disturbances; thus, it achieved a more robust control compared to path planning methods. The system achieved trajectory tracking at low speeds by offline learning without teaching data to follow a target ship with the same maneuverability as its own ship and operated randomly under external disturbances. Furthermore, an online target correction logic function that locally corrects targets was developed to increase the tracking ability in external disturbances. Subsequently, a berthing and unberthing experiment was conducted using an actual large ferry to ensure the applicability of simulation-based NNs to the trajectory-tracking control of an actual ship in a real-life environment.