Controller Design For Systems Research Articles

Shifting and state transformations-based adaptive tracking control for deferred full state-constrained uncertain nonlinear systems

This paper concerns the tracking control problem of a class of uncertain nonlinear systems subject to deferred time-varying state constraints and external disturbances. The states of the system are free in the initial phase and are restricted by some time-varying constraints after a particular time. A class of novel shifting functions are defined, which make any initial states that beyond the constraint region move to the desired position (such as zero). Thereafter, a new state transformation is implemented for the shifted state, which transforms the state constraint problem into the boundedness of a new variable. Compared with the existing BLF method, this approach avoids feasibility test for virtual control variables. Adaptive backstepping control and dynamic surface control are used in system controller design and stability analysis, and the ideal tracking performance is achieved. Finally, simulation example and comparative studies are carried out to illustrate the effectiveness and outstanding characteristics of the proposed approach. Simulation results show that the proposed control scheme broadens the scope of application, shortens running time and improves control efficiency compared with the existing control strategies.

Non‐singular terminal sliding mode controller design for nonlinear systems with prescribed convergence time guarantees

AbstractThis paper considers the prescribed‐time non‐singular terminal sliding mode control (TSMC) for nonlinear systems with uncertainties bounded by non‐negative functions. At first, a new Lyapunov theorem for prescribed‐time stability is introduced. Then, a novel terminal sliding surface together with a non‐singular TSMC input is constructed by using a time‐varying scaling function. Strict analysis shows that the proposed controller is able to ensure the exact reaching of the sliding surface as well as the system states to zero in a prescribed time independent of the system initial conditions. Moreover, all the state signals and the control input remain uniformly bounded. Finally, simulation comparison with the existing fixed‐ and prescribed‐time TSMC is given to verify the effectiveness of the theoretical results.

Distributed adaptive neural network consensus control of fractional-order multi-agent systems with unknown control directions

In this work, adaptive consensus control of leader-following fractional-order multi-agent systems whose each subsystem includes functional uncertainties, external disturbances, and unknown control directions is investigated utilizing neural networks and the Nussbaum function. The controller is synthesized within the framework of the backstepping algorithm, where the “explosion of complexity” problem is mitigated through the use of a command filter, and the adverse impact of filtered errors is decreased using compensation signals. The function uncertainties of each follower are approximated by neural networks, and a disturbance update law is developed to identify the boundary of the disturbance. Importantly, a general conclusion is provided to affirm the applicability of the Nussbaum function in addressing controller design for fractional-order systems with unknown control directions. Finally, the validity of the proposed approach is verified via two numerical examples.

Active Disturbance Rejection-based Double-loop Control Design for Large Antenna's Servo System

Radio astronomical observations put stringent requirements on the tracking and pointing accuracy of radio telescope antennas. High inertia, low stiffness, underdamped, and multi-resonant frequencies of a large aperture radio telescope’s antenna make the high-accuracy control difficult. It is not easy to satisfy control performance using only conventional PID controllers. A low-order Active Disturbance Rejection-based double-loop controller for large antenna is designed in this paper and tested on the Green Bank Telescope model. First, the first-order Linear Active Disturbance Rejecting Controller (LADRC) cascading a first-order low-pass filter and a notch filter is designed for the antenna’s velocity loop to achieve the dual-objective optimal velocity tracking. Second, the position loop controller is designed to realize the antenna’s position-tracking control by combining the PD controller and a low-pass filter. Further optimization of the position-loop controller helps improve the dynamic performance of the system. The simulation results indicate that the response curves of the proposed PD-LADRC control are smother than those of the Quantitative Feedback Theory (QFT) based controller; the settling time of the PD-LADRC system is 10.1 s and reduces by about 8.2 s than that of the QFT. While using a better position controller reduces settling time to 5 s. The PD-LADRC system also has better wind-disturbance rejection; the worst disturbance response reduces at the gearbox by 68.3% and 60% at the dish, and the recovery time reduces by more than 15 s than the QFT-based controller. In addition, besides easier parameter tuning, the proposed PD-LADRC has better robustness to systematic parameter perturbations and minor tracking error rms in position tracking.

Compact Design and Task Space Control of a Robotic Transcatheter Delivery System for Mitral Valve Implant.

Mitral regurgitation (MR) is one of the most common valvular abnormalities, and the gold-standard for treatment is surgical mitral valve repair/replacement. Most patients with severe MR are over the age of 75, which makes open-heart surgery challenging. Thus, minimally invasive surgeries using transcatheter approaches are gaining popularity. This paper proposes the next generation of a robotic transcatheter delivery system for the mitral valve implant that focuses on the design of the actuation system, modeling, and task space control. The proposed actuation system is compact while still enabling bidirectional torsion, bending, and prismatic joint motion. A pulley structure is employed to actuate the torsion and bending joints using only one motor per joint in conjunction with an antagonistic passive spring to reduce tendon slack. The robotic transcatheter is also optimized to increase its stability and reduce bending deflection. An inverse kinematics model (with an optimization algorithm), singularity analysis method, and joint hysteresis and compensation model are developed and verified. Finally, a task space controller is also proposed. Experiments, including trajectory tracking and demonstrations of the robot motion in an ex vivo porcine heart and a phantom heart through a tortuous path are presented.

Adaptive Fuzzy Nonsingular Fixed-Time Control for a Class of MIMO Nonstrict Feedback System

This paper studies the adaptive fuzzy practical fixed-time control design for MIMO nonlinear systems with non-strict feedback. The extant practical fixed-time stability criterion cannot obtain an accurate settling time upper bound or exists some constraints on parameters that lead to a conservative result. Thus a novel practical fixed-time stability criterion is proved in this paper to resolve the above problem and can obtain the precise value of the settling time upper bound. The control singular issue caused by the fixed-time stability criterion form is avoided by introducing adding power integration method. Compared with other approaches, this method is easy to apply in control design, and it's convenient to prove its effectiveness. And fuzzy logic system is adopted to approximate the unknown nonlinear items. Combining the proposed fixed-time stability criterion, traditional backstepping scheme, and fuzzy logic system, an adaptive practical fixed-time controller is proposed. The simulation of the actual physical system demonstrates the effectiveness of the controller and practical fixed-time criterion.

The application of embedded system on electric devices

Embedded system control technology is widely used in airborne electronic equipment. Embedded system control technology is at the core of the development process of airborne electronic devices, but currently the overall design of system control for airborne electronic devices is not planned from the top level of the system, which may cause the system control of the device to not fully meet the user’s needs in terms of use functions, and the system control software often needs to be modified, wasting a large amount of human, material, and financial resources. Aiming at this, this paper discusses the embedded system control technology and design methods applied in airborne electronic equipment. This article will analyze the current research status of the application of embedded systems in electrical equipment from multiple aspects, and provide prospects for its future development. Through analysis, the entire development process and shortcomings of embedded systems can be clarified, providing reference for their better application in industrial environments in the future.

Safety critical control design for nonlinear system with tracking and safety objectives

This paper proposes a safety critical control law for the tracking with safety of an affine nonlinear control system, which demonstrates how to sacrifice the tracking performance to keep the system trajectory in the safe zone and how to design a performance indicator function for the tradeoff between decreasing the tracking error and satisfying the safety requirement. Our design is essentially a nonlinear multi-objective control to achieve both safety and asymptotic tracking if there is no conflict between the tracking and safety, or to decrease the tracking error under the safety constraints otherwise. Different from existing methods for safety critical control problems, the design idea is to find a tracking controller without safety consideration, and then design a safety controller based on a control barrier function, which is capable of dealing with both tracking and safety issues. The efficiency of our design is illustrated by a mechanical system in both non-conflicted and conflicted cases.

Decentralized Controller Design for Large-Scale Uncertain Discrete-Time Systems with Non-Block-Diagonal Output Matrix

This research paper addresses the challenge of designing a decentralized controller for a discrete-time uncertain polytopic system with a linear large-scale (LSS) structure. Specifically, we investigate this problem in cases where the subsystem’s output matrix lacks a decentralized structure. Firstly, the proposed novel procedure of a decentralized controller design transforms the LSS model to have a fully decentralized structure (both input and output matrices are block-diagonal). Then, the robust stability boundary parameter is calculated for the open-loop system. This stability boundary parameter is considered in robust decentralized controller design where an appropriate controller design method is used. The entire process of designing a robust decentralized controller takes place at the subsystem level, and the influence of interaction is considered through the robust stability boundary parameter. Lastly, we present an example of a five-order system comprising two subsystems to show the effectiveness of the new method.

Observer-based SMC design for stochastic systems with Levy noise

Abstract This work addresses the problem of sliding mode control (SMC) design for a continuous-time non-linear stochastic system with Levy-type noise. A state observer model is constructed to estimate the unavailable state information. Furthermore, Levy-type noise is considered to analyse small perturbations and to characterize the appearance of large samples that will occur in the system. Lyapunov stability and SMC theory are used to provide some sufficient conditions that ensure the stochastic stability of the error system and reachability of the predefined sliding surface. Finally, an example is given to demonstrate the feasibility of the proposed approach.

Anti-disturbance observer-based proportional-retarded control design for polytopic uncertain fractional-order systems

This study deals with the stabilisation problem of fractional-order time-delay systems with polytopic uncertainties and multiple disturbances with the use of Lyapunov stability theory. Notably, the multiple disturbances comprising both the known and unknown signals, are respectively characterised by the norm-bounded and exogenous system which signifies the harmonic signals with modelling perturbations. The control protocol is configured by the integration of proportional-retarded controller with gain perturbations and the output of an anti-disturbance observer. Precisely, the disturbance observer is taken into account for attenuating the influence of disturbance signals. Moreover, the implementation of a time-delay term in the feedback loop replicates the dynamic features of a derivative action that relies only on position measurements and its time differencing capabilities make it to be minimally sensitive against noise and provide a smoothing effect. By virtue of these circumstances, the asymptotic stability of the considered system is assured. With the aid of a suitable Lyapunov function, a set of robust order-dependent sufficient conditions is derived and then solved through the MATLAB LMI toolbox. As a result, the controller gain matrices can be computed and two numerical examples, including an electrical circuit model with simulation results are presented to certify the inherent potential of the theoretical outcomes.

Fault‐tolerant control design for stochastic distribution control systems based on k‐step fault estimation

AbstractA novel scheme of fault‐tolerant control (FTC) and fault estimation (FE) for the stochastic distribution control (SDC) system with disturbance is investigated. The output probability density function (PDF) is modelled by the weight vector of the B‐spline neural network with the given basis function, and control of output probability density function can be converted to control of the weight vector of the B‐spline neural network. A k‐step fault estimation algorithm aiming at enhancing the accuracy of fault estimation is first applied to the stochastic distribution control system. Subsequently, a dynamic output feedback fault‐tolerant control algorithm is constructed by using the k‐step fault estimation information to guarantee that the target weight vector can be still approximated by the output weight vector in case of actuator fault. A simulation example is used to confirm the availability of the presented method.

Adaptive Variable Structure Controller Design for Uncertain Switched Systems With Unknown Time-varying Delay

Adaptive Variable Structure Controller Design for Uncertain Switched Systems With Unknown Time-varying Delay

Integral sliding mode control design for uncertain impulsive systems with delayed impulses

This paper addresses the integral sliding mode control (ISMC) problem of uncertain impulsive systems with delayed impulses. Firstly, an integral sliding surface with embedded impulse information is constructed, which is able to counteract the intermittent impact of delayed impulses. Then an ISMC law is designed to guarantee the finite-time reachability of the predefined sliding surface without special restriction on system dynamics. Secondly, two different types of linear control laws with switching gains are proposed to robustly stabilize the sliding mode dynamics. The first type is independent of the size of impulse delays, and is used to tackle the impulses with unknown bounded delays. The second type aims at providing impulse-delay-dependent stabilization algorithms under the assumption that the delays are smaller than the impulse intervals. In the situation where the upper bounds of the uncertainties are characterized by two unknown constants, an adaptive ISMC law is proposed to ensure the existence of sliding mode. Switching Lyapunov functions and the state augmentation technique are introduced to exploit the positive/negative effects of delayed impulses. Several tractable conditions for designing the switching gains and the sliding surfaces are derived in terms of linear matrix inequalities. Finally, three numerical examples are presented to show the effectiveness of the proposed control algorithms and highlight their merits.

Composite fault reconstruction and fault-tolerant control design for cyber-physical systems: An interval type-2 fuzzy approach

This article scrutinizes the stabilization and fault reconstruction issues for interval type-2 fuzzy-based cyber–physical systems with actuator faults, deception attacks and external disturbances. The primary objective of this research is to formulate the learning observer system with the interval type-2 fuzzy technique that reconstructs the actuator faults as well as the immeasurable states of the addressed fuzzy based model. Further, the information of reconstructed actuator faults is incorporated in the developed controller with the imperfect premise variables for ensuring the stabilization of the system under consideration. At the same time, the H∞ technique is employed to reduce the impact of external disturbances in the considered model. In addition to that, the deception attacks are represented as a stochastic variable that satisfies the Bernoulli distributions. On the ground of this, a set of sufficient criteria is deduced in the context of linear matrix inequalities to affirm the stability of the addressed systems. Furthermore, the requisite gain matrices are computed by resolving the obtained linear matrix inequality based stability criteria. At last, two simulation examples, including the mass–spring–damper system are exhibited to demonstrate the usefulness of analytical findings of the developed strategy.

Explicit model predictive control design for artificial respiratory ventilation system

Explicit model predictive control design for artificial respiratory ventilation system

Detailed analysis and modeling of improved cascade buck converter

ABSTRACT – This paper presents ready-to-use nonlinear and linear averaged models of an improved cascade buck converter (ICBC) for the first time. A detailed steady-state analysis is also given, providing its operating modes, equilibrium values, and design guidelines. The modelling process consists of two stages. First, the nonlinear model is obtained using the state-space averaging technique. Subsequently, the averaged model is linearised by applying the small-ripple approximation and the small-signal model is achieved. Furthermore, the developed small-signal model is employed to derive three significant transfer functions of the converter. The proposed converter model is valid for the continuous conduction mode (CCM) when the duty cycle is lower than . To be used in validation studies, an exemplary converter with rated power that steps down input voltage to is designed. The accuracy of theoretical analyses is confirmed by the simulation results of the designed converter. Similarly, all proposed models are validated with the simulations done in both frequency-domain and time-domain. The results show that the proposed parametric model response closely matches that of the switching (non-parametric) model and hence it can be safely used for controller design in feedback systems.

A novel honey badger algorithm based load frequency controller design of a two-area system with renewable energy sources

When it comes to the process of ensuring the stability, quality, and reliability of a power system, one of the most crucial components is known as the load frequency controller (LFC). It does this by ensuring that there is a balance between the amount of power that is produced and the amount that is consumed. This paper proposes a novel evolutionary approach, referred to as the Honey Badger Algorithm (HBA), PI/PID controllers should be configured in the best possible way in order to address the LFC problem in the electrical power system. The research takes into account a power system that is integrated between two areas and uses renewable energy sources, such as a wind system and a solar system. The utilization of renewable energy sources has the potential to yield favorable outcomes in frequency control through the provision of prompt and adaptable responses to fluctuations in system frequency, helping to maintain grid stability. The proposed HBA method is utilized to refine the controller parameter values, using a fitness function anchored on the integral of absolute error (IAE) and the integral time multiplied by absolute error (ITAE). The performance of the proposed HBA-based controller has evaluated under 5% step load perturbation (SLP) in area-1. The HBA-based controllers demonstrate greater performance in terms of settling time, overshoot, and fitness value when compared to other well-known optimization algorithms such as Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimization (GWO). According to the obtained results, the IAE-based PID controller has the best performance. The HBA-based PID controller is evaluated according to the following performance criteria; the objective function value is 0.4201, the settling time values and overshoot values for the area-1, area-2 and tie-line are 15.6, 33.7 and 27.9 s and −6.6, −0.7 and −0.0071 Hz, respectively. According to the findings, the HBA is both a dependable and effective tool for finding solutions to LFC research problems in multi-source power systems.

Neural networks-based adaptive output-feedback control design for nonlinear systems with dead zone output and uncertain disturbances

This work focuses on the issue of neural networks-based adaptive output-feedback control for nonlinear systems with dead zone output and immeasurable states. Radial basis function neural networks (RBFNN) are utilised to approximate the unknown functions and an input-driven filter is used to estimate the immeasurable states. Nussbaum function is employed to address the issue of uncertain virtual control coefficient, which is brought by the dead zone in the output mechanism, and the presented control scheme requires only one adaptive law, making the structure of the controllers very realistic. Based on the approximation capabilities of NNs and the backstepping method, an adaptive controller is designed. Based on the Lyapunov stability theory, all signals in closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small area near the origin. The effectiveness of the proposed adaptive control method is proved with the help of two examples.

Design and Development of Swimming Pool Water pH Level Monitoring System and Automatic Selenoid Valve Control Based on the Internet of Things

A device for monitoring the pH level of swimming pool water and an IoT-based automatic solenoid valve control has been specially designed. This system consists of several main components, including a pH sensor that continuously monitors the pH level in swimming pool water. This sensor will be connected to the Esp32 Board microcontroller which has been programmed to retrieve pH data periodically. The collected data will be sent via an internet connection to the cloud platform and can then be accessed via a mobile application to display real-time pH level messages. In addition, this system is also equipped with automatic solenoid valve control. Based on the measured pH data, the system will be able to make a decision to open or close the solenoid valve. If the pH level is outside the set limit, the system will automatically activate the solenoid valve to open the floodgates for filling water into the swimming pool, thus maintaining the pH balance automatically. In the design system for monitoring the pH level of swimming pool water and controlling this automatic solenoid valve using a pH-014 sensor which functions to detect the pH level in swimming pool water.