Stability Of Control System Research Articles

Devising a combined method for setting PI/PID controller parameters for oil and gas facilities

The object of this study is automatic control systems of the first, second, and third orders. The principal task was to ensure the stability of control systems while minimizing overshot and regulation time. A combined method for determining the tuning parameters of PI/PID controllers has been devised, which combines the s-plane method and the generalized quadratic criterion. The s-plane method is based on the Vieta theorem, which relates the roots of the characteristic equation of a closed-loop control system to its parameters. They are functions of the tuning parameters of PI/PID controllers. By choosing the left roots of the characteristic equation of a closed-loop system on the s-plane, the desired quality indicators of the control system can be achieved. The roots of the equation are functionally related to the parameters of PI/PID controllers. From the system of algebraic equations that follow from the Vieta theorem, the tuning parameters for PI/PID controllers are found as a solution to such a system. At the second stage of solving the problem, the roots of the characteristic equation are chosen so that the generalized quadratic criterion is a function only of real part of one of the characteristic equation’s roots. As a result, we obtain a one-dimensional minimization problem, the local minimum of which was sought within a predetermined search interval. This interval was chosen on the condition that the parameters for PI/PID controllers would be strictly positive. The roots of the characteristic equation of the closed-loop system would belong to the left half-plane of the s-plane. Such a choice of the search interval guarantees the stability of the closed-loop automatic control system. It was found that compared to the s-plane method, the overshot and regulation time were reduced by an average of 73.5 % and 66.5 %. This could increase the speed of industrial controllers

Constrained Nonlinear MPC with Rudder-Roll Stabilization for Integrated Path Following and Collision Avoidance in Underactuated Surface Vessels

This study develops a constrained nonlinear model predictive control (NMPC) framework, integrating rudder roll stabilization to address coupled path-following and collision avoidance challenges for underactuated surface vessels (USVs). The compact state-space model integrates both navigational states and roll dynamics through augmentation, facilitating real-time optimization of the trade-off between safety margins for roll movements and path-following accuracy. Given that excessive roll movement during obstacle avoidance in the USV path following can readily lead to USV capsizing, the NMPC approach is employed to explicitly address multiple constraints, including obstacle avoidance constraint, roll movement safety, and control input rudder angle constraints, thereby achieving precise path following for the rudder-roll reduction control system. Different from traditional methods that adhere to a pre-planned obstacle avoidance path, the proposed NMPC approach formulates obstacle avoidance as a nonlinear inequality constraint, significantly enhancing the maneuverability of the USV during obstacle avoidance. To validate the effectiveness of the proposed algorithm, the stability and optimality of the rudder-roll reduction control system are analyzed. The advantages of the proposed algorithm are ultimately demonstrated through both theoretical analysis and simulation results.

The Impact of PID Control Parameters on DC Motor Performance

This paper investigates the influence of PID control parameters on the performance of DC motors, which are integral components in industrial automation and robotics. DC motors require precise control for applications demanding high accuracy in speed and position, and the PID (Proportional-Integral-Derivative) controller remains one of the most effective tools for this purpose. Through a comprehensive literature review, this study explores the effects of proportional (P), integral (I), and derivative (D) components on the stability, accuracy, and responsiveness of DC motor control systems. The findings indicate that proportional gain (Kp) impacts system stability and responsiveness, integral gain (Ki) addresses steady-state errors, and derivative gain (Kd) enhances transient response. The results of this research contribute to the optimization of PID controller tuning strategies, offering practical insights for improving the efficiency of motor control in diverse applications.

Root distribution of complex coefficient polynomials

The Routh Array is known to be a very convenient way to determine the number of polynomial roots that lie in the right half of the complex plane using only the polynomial coefficients. Extensive use of this is made particularly in control system stability studies [1]. We now show that the same real-coefficient Routh algorithm can be used to obtain this information for polynomials with complex coefficients, which are prominent in areas of engineering such as electrical inductance theory [2]. The method is easy to apply and is seen to be more straightforward than existing methods for this task [e.g. 3,4]. If required, it also enables the use of appropriate root-finding methods for real-coefficient polynomials to obtain the roots of complex- coefficient polynomials.

FOPID controller design for pneumatic control valves with ultra-low overshoot, rapid response and enhanced robustness

The performance of pneumatic control valves, characterized by speed, stability, and accuracy, is critical for industrial production and energy efficiency. Traditional PID and fuzzy control methods face limitations in achieving high-precision control due to structural constraints. This study proposes a fractional-order proportional-integral-derivative (FOPID) controller optimized for pneumatic control valves, incorporating a novel overshoot-penalty objective function. To enhance optimization, the Hippopotamus Optimization (HO) is improved with Genetic Algorithm (GA). Simulation and experimental results demonstrate the proposed GAHO-based FOPID controller achieves a settling time of 5.25 s and an overshoot of 0.88%, significantly surpassing conventional methods. These results establish that the proposed FOPID controller as an effective solution for improving the stability, efficiency, and safety of pneumatic control systems in industrial applications.

The effect of head-tracking resolution on the stability and performance of a local active noise control headrest system.

Incorporating head-tracking techniques into local active noise control headrest systems enables the plant model used in the controller to be updated dynamically as the user moves their head. This reduces the mismatch between the plant model and the physical plant responses from the secondary sources to the users' ears, which increases the achievable noise reduction when head movement occurs. In practice, since the plant models for different head positions must be identified during a calibration procedure, it is necessary to limit the head-tracking resolution to constrain the complexity of this procedure. This leads to errors between the physical and modelled plant responses as the user's head moves, which impacts the control system's stability and performance. However, the relationship between the control system behaviour and the tracking accuracy is not well understood. This paper investigates the impact of head-tracking resolution, considering translational and rotational movements, on the stability and performance of an active headrest. Assuming the error signals at the user's ears are available for adaptive control, it is shown that the system has an upper-frequency limit beyond which controller instability occurs, and this frequency is influenced by the tracking resolution, the initial head position, and the type of head movement.

Communication Security and Stability in NNCSs: Realistic DoS Attacks Model and ISTA-Supervised Adaptive Event-Triggered Controller Design.

This article addresses the challenge of achieving asymptotic stability in nonlinear networked control systems (NNCSs) amid denial-of-service (DoS) attacks, particularly under constrained communication resources. We begin by establishing a practical DoS attack model using the NSL-KDD dataset, which provides a realistic depiction of DoS attack dynamics based on real-world data. We then introduce the iterative shrinkage-thresholding algorithm (ISTA) to supervise the adaptive event-triggered controller (AETC), ensuring that system parameters are adjusted effectively while conserving communication resources. We develop an enhanced data compression mechanism to further mitigate the impact of DoS attacks on communication servers. Additionally, we construct an asymmetric Lyapunov-Krasovskii function (LKF) to rigorously verify the asymptotic stability of NNCSs. Finally, we empirically validate the effectiveness of our proposed AETC using an autonomous vehicle (AV) model.

Self-triggered neural tracking control for discrete-time nonlinear systems via adaptive critic learning.

Self-triggered neural tracking control for discrete-time nonlinear systems via adaptive critic learning.

Experimental research on the optimization and evaluation of the polymer/Cr3+ deep profile control system for heterogeneous fractured low-permeability reservoirs

There are strong heterogeneities in fractured low-permeability reservoirs, and the fracture network leads to a sharp increase of the water cut in production wells, which causes a rapid decline in production, and overall poor recovery efficiency. This article focuses on the effects of fractures on water cut in reservoir developments for Chaoyang Gou Oilfield of China, the formula of the profile control system of the polymer/Cr3+ has been determined by taking the conducting indoor profile control experiments, and the injectability, sealing ability, compatibility of formation water, thermal stability, and shear resistance of the profile control system are evaluated by taking the long core experiments. Then, the reasonable formulas for different matrix/fracture permeability levels’ combinations are determined through the profile control system oil displacement experiments and the field test effects are evaluated. The results show that a series of profile control systems suitable for heterogeneous fractured low-permeability reservoirs are optimized. For the 15 × 10−3 μm2 permeability level, the concentration of 13 million molecular weight polymer is recommended to be more than 1500 mg/L, and the 16 million molecular weight with 1000 mg/L for the 30 × 10−3 μm2 level, the 19 million molecular weight with 500 ∼ 1000 mg/L for the 45 × 10−3 μm2 level. The application effect in oil fields shows that the water cut decreased by 8.65% points, and the cumulative oil increase is 1601t after profile control. The research results provide an effective formula for improving the oil recovery in low-permeability reservoirs.

Rotor Position Estimation Algorithm for Surface-Mounted Permanent Magnet Synchronous Motor Based on Improved Super-Twisting Sliding Mode Observer

In response to the chattering issue inherent in sliding mode observers during rotor position estimation and to enhance the stability and robustness of sensorless control systems for surface-mounted permanent magnet synchronous motors (SPMSM), this study proposes a rotor position estimation algorithm for SPMSM based on an improved super-twisting sliding mode observer (ISTSMO) and a second-order generalized integrator (SOGI) structure. Firstly, the super-twisting algorithm is introduced to design the observer, which effectively attenuates the sliding mode chattering by using continuous control signals. Secondly, SOGI is introduced in the filtering stage, which not only effectively addresses the time delay issues caused by traditional low-pass filters but also enables the observer to extract rotor position information by monitoring only the back electromotive force (back-EMF) signal of the α-phase, thereby simplifying the observer structure. Finally, the proposed scheme is experimentally compared with the traditional sliding mode observer on the YXMBD-TE1000 platform. The experimental results showed that during motor acceleration and deceleration tests, the average speed estimation error was reduced from 141 r/min to 40 r/min, and the maximum position estimation error was reduced from 0.74 rad to 0.29 rad. In load disturbance experiments, the speed variation decreased from 781 r/min to 451 r/min, and the steady-state speed fluctuation was significantly reduced. These results confirm that the proposed observer exhibits superior stability and robustness.

Management control system stability and change in a global corporation: the role of cultural capital

Purpose This paper aims to understand the role that the “cultural capital” of managers has on the stability and change of management control systems (MCS) in the subsidiary of a global corporation. Design/methodology/approach A seven-year longitudinal case study was conducted at the US subsidiary of a Japanese-based global corporation. The theoretical concepts of cultural capital and MCS package typology are used to examine how management controls were understood by locally hired employees and expatriate Japanese managers at the case study site. Findings The findings show that the managers at the Japanese headquarters transferred an MCS package that had a high level of interdependence between cultural control and results control to their US subsidiary in the 1960s. This MCS package did not influence the behavior of locally hired employees in ways that the Japanese expatriate managers expected; instead, it led to the cultural exclusion of local employees. Even when the Japanese managers were faced with a changing environment, the MCS package did not change. When Japanese managers realized they could not achieve their goals in the USA without local managers, they slowly started to hire mid-career local managers. As the number of local managers increased, the expatriate Japanese managers started to become more aware of the impact of their cultural capital. This has resulted in changes in the MCS package for local managers in the US subsidiary. Originality/value This study revealed that even when the strategy of a company and the environment in which it operates changes, an MCS package may not change quickly. The authors show that the cultural capital of managers plays a role in MCS stability and change.

Vibration Control of Flexible Launch Vehicles Using Fiber Bragg Grating Sensor Arrays

The effects of mechanical vibrations on control system stability could be significant in control systems designed on the assumption of rigid-body dynamics, such as launch vehicles. Vibrational loads can also cause damage to launch vehicles due to fatigue or excitation of structural resonances. This paper investigates a method to control structural vibrations in real time using a finite number of strain measurements from a fiber Bragg grating (FBG) sensor array. A scaled test article representative of the structural dynamics associated with an actual launch vehicle was designed and built. The main modal frequencies of the test specimen are extracted from finite element analysis. A model of the test article is developed, including frequency response, thruster dynamics, and sensor conversion matrices. A model-based robust controller is presented to minimize vibrations in the test article by using FBG measurements to calculate the required thrust in two cold gas actuators. Controller performance is validated both in simulation and on experiments with the proposed test article. The proposed controller achieves a 94% reduction in peak–peak vibration in the first mode, and 80% reduction in peak–peak vibration in the second mode, compared to the open loop response under continuously excited base motion.

Robust adaptive fuzzy type-2 fast terminal sliding mode control of robot manipulators in attendance of actuator faults and payload variation

Introduction. This study presents a robust control method for the path following problem of the PUMA560 robot. The technique is based on the Adaptive Fuzzy Type-2 Fast Terminal Sliding Mode Control (AFT2FTSMC) algorithm and is designed to handle actuator faults, uncertainties (such as payload change), and external disturbances. The aim of this study is to utilize the Fast Terminal Sliding Mode Control (FTSMC) approach in order to ensure effective compensation for faults and uncertainties, minimize tracking error, reduce the occurrence of chattering phenomena, and achieve rapid transient response. A novel adaptive fault tolerant Sliding Mode Control (SMC) approach is developed to address the challenges provided by uncertainties and actuator defects in real robotics tasks. Originality. The present work combined the AFT2FTSMC algorithm in order to give robust controllers for trajectory tracking of manipulator’s robot in presence parameters uncertainties, external disturbance, and faults. We use an adaptive fuzzy logic system to estimate the robot’s time-varying, nonlinear, and unfamiliar dynamics. A strong adaptive term is created to counteract actuator defects and approximation errors while also guaranteeing the convergence and stability of the entire robot control system. Novelty. The implemented controller effectively mitigates the chattering problem while maintaining the tracking precision and robustness of the system. The stability analysis has been conducted using the Lyapunov approach. Results. Numerical simulation and capability comparison with other control strategies show the effectiveness of the developed control algorithm. References 53, table 1, figures 8.

Optimal Performance Analysis for Networked System with Quantitative Control Input Over Feedback Channel

ABSTRACTNetworked control systems (NCS) have become an emerging and important research area given the rapidly developing network communication technology. Numerous studies in this area concentrate on the stability of control systems, while little has been done on its performance analysis, especially the index of an optimal control system. We fill this gap here by analysing the optimal tracking performance for an NCS that has quantitative control inputs over feedback channels. We design a dual‐degree‐of‐freedom controller along with an optimal control system, by applying the Youla parameterization method based on the time domain and coprime decompositions. The proposed methodology is assessed by numerical simulations. The system's tracking performance is found to be deteriorated by the unstable poles and non‐minimum phase zeros of the controlled object, as well as by quantization signal errors. These findings are beneficial for analysing and designing practical control systems.

Robust formation control of multiple aerial robotic vehicles using near neighbor cyclic deviation with time-varying disturbances.

Robust formation control of multiple aerial robotic vehicles using near neighbor cyclic deviation with time-varying disturbances.

A Nonlinear Noise-Resistant Zeroing Neural Network Model for Solving Time-Varying Quaternion Generalized Lyapunov Equation and Applications to Color Image Processing.

The time-varying Lyapunov equation (TVLE) plays a crucial role in control design and system stability. However, there has been limited research conducted on the time-varying generalized Lyapunov equation in the quaternion field. To tackle the time-varying quaternion generalized Lyapunov equation, a nonlinear noise-resistant zeroing neural network (NNR-ZNN) model with a novel power activation function (NPAF) is devised. The issue of non-commutativity within quaternion is circumvented by utilizing the real representation. The theoretical analyses provide a sufficient explanation for the global stability, fixed-time convergence, and robustness of the NNR-ZNN model. Under several different kinds of noises, the exceptional robustness of the NNR-ZNN model is highlighted by comparison with other existing models. In the end, the successful applications of the NNR-ZNN model to color image fusion and color image denoising confirm the practical value of the NNR-ZNN model.

On the absolute stability of automatic control systems in the vicinity of a program manifold

The problem of constructing automatic control systems according to a given program manifold is considered. First, a general method for constructing ordinary differential equations is given, which reduced to choosing some function that provides the stability of a given manifold. Then the absolute stability of automatic control systems in the vicinity of given program manifold is investigated. Nonlinearities satisfy to the conditions of local quadratic connections and they are differentiable in all variables. Sufficient conditions of the absolute stability of the program manifold with respect to the given vector functions are obtained by constructing the Lyapunov function, in the type of “quadratic form plus an integral from nonlinearity”. Frequency conditions of absolute stability for the program manifold of control systems are established. Also sufficient conditions of the absolute stability automatic control systems with non-stationary nonlinearities are received.

Control System of Medical Robot Based on BCI and High-speed Communication

This article examines the utilisation and integration of brain-computer interface (BCI) technology and high-speed communication technology in the control system of a medical robot. The article begins by providing an overview of the development of BCI technology and its significance in assisting individuals with paralysis to regain their communication abilities. This is achieved by recording brain signals through non-invasive methods, thereby enabling the control of external devices. Subsequently, the article provides a comprehensive account of the ways in which high-speed communication technologies, particularly 5G networks, can markedly enhance the real-time and stability of medical robot control systems. These technologies offer low latency and high bandwidth. This enables more precise and secure telesurgery and complex medical operations Furthermore, the article examines the optimisation of communication protocols to reduce latency and enhance the reliability of data transmission, as well as the role of artificial intelligence and machine learning technologies in improving the decision-making capabilities of medical robots. In conclusion, the article addresses the safety and ethical concerns associated with medical robot control systems. It underscores the pivotal role of design and protocols in mitigating safety hazards and examines the prospective developments of BCI and high-speed communication technologies and their profound implications for the medical domain.

Adaptive Neural Network-Based PID Controller Design for Velocity Control of an Internal Combustion Engine Using Back Propagation Technique

Precise velocity control in internal combustion engines (ICEs) is essential for optimizing performance, improving fuel efficiency, and minimizing emissions. However, the nonlinear dynamics and inherent uncertainties within ICE systems present substantial challenges for traditional control methods. In this paper, we propose an adaptive control strategy that integrates a Proportional-Integral-Derivative (PID) controller with Back Propagation Neural Networks (BPNNs) to effectively address these complexities. The proposed controller architecture consists of two key components: a BPNN to estimate modelling uncertainties, such as unknown friction and external disturbances affecting the ICE, and a primary PID controller responsible for velocity regulation. The BPNN functions as a dynamic estimator, continuously learning and adapting to changes in system dynamics, thereby enhancing the robustness and adaptability of the control system. By accurately capturing the nonlinearities and uncertainties inherent in ICEs, the BPNN contributes to improved control performance and system stability. To validate the effectiveness of the proposed approach, extensive numerical simulations are performed using MATLAB Simulink. These simulations encompass a range of operating conditions and scenarios to thoroughly evaluate the controller's performance. Additionally, the proposed method is compared to conventional PID control techniques found in the literature, with a focus on robustness, tracking accuracy, and disturbance rejection. The results indicate that the adaptive PID controller, incorporating BPNNs, outperforms traditional PID methods, delivering superior velocity regulation and disturbance rejection. Furthermore, the proposed approach demonstrates significant potential for real-world applications in ICE systems, providing enhanced control performance and efficiency. This study advances the field of control engineering by introducing an innovative adaptive control strategy tailored specifically for velocity control in internal combustion engines. Leveraging the capabilities of BPNNs to address uncertainties, this approach contributes to improved system performance and offers a promising direction for future advancements in engine control technologies.

Stabilization of control systems associated with a strongly continuous group

This paper is devoted to the stabilization of a linear control system $y' = A y + B u$ and its suitable non-linear variants where $(A, \cD(A))$ is an infinitesimal generator of a strongly continuous {\it group} in a Hilbert space $\mH$, and $B$ defined in a Hilbert space $\mU$ is an admissible control operator with respect to the semigroup generated by $A$. Let $\lambda \in \mR$ and assume that, for some {\it positive} symmetric, invertible $Q = Q(\lambda) \in \cL(\mH)$, for some {\it non-negative}, symmetric $R = R(\lambda) \in \cL(\mH)$, and for some {\it non-negative}, symmetric $W = W(\lambda) \in \cL(\mU)$, it holds [[EQUATION]] We then present a new approach to study the stabilization of such a system and its suitable nonlinear variants. Both the stabilization using dynamic feedback controls and the stabilization using static feedback controls in a weak sense are investigated. To our knowledge, the nonlinear case is out of reach previously when $B$ is unbounded for both types of stabilization.