Controller Design For Systems Research Articles

Sex differences and the effect of female sex hormones on auditory function: a systematic review.

First, to discuss sex differences in auditory function between women and men, and whether cyclic fluctuations in levels of female sex hormones (i.e., estradiol and progesterone) affect auditory function in pre-menopausal and post-menopausal women. Second, to systematically review the literature concerning the discussed patterns in order to give an overview of the methodologies used in research. Last, to identify the gap in knowledge and to make recommendations for future work. Population, Exposure, Control, Outcome and Study design (PECOS) criteria were used in developing the review questions. The review protocol follows the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and was pre-registered in the Prospective Register of Systematic Reviews (PROSPERO; CRD42020201480). Data Sources: EMBASE, PubMed, MEDLINE (Ovid), PsycINFO, ComDisDome, CINAHL, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL) via Cochrane Library, and scanning reference lists of relevant studies, and internet resources (i.e., Mendeley) were used. Only studies published between 1999 and 2022, in English, or in English translation, were included. The quality of evidence was assessed using the Newcastle-Ottawa Scale (NOS). Sex differences: Women had more sensitive hearing (measured at the level of peripheral and central auditory system) than men. Cyclic fluctuations: Auditory function in women fluctuated during the menstrual cycle, while no such fluctuations in men over the same time period were reported. Hearing sensitivity improved in women during the late follicular phase, and decrease during the luteal phase, implying an effect of female sex hormones, although the specific effects of estradiol and progesterone fluctuations on the central auditory system remain unclear. Hearing sensitivity in women declined rapidly at the onset of menopause. The review has shown the following. Consistent sex differences exist in auditory function across the auditory pathway with pre-menopausal women often showing better function than age-matched men. Moreover, pre-menopausal women show fluctuations in hearing function across the menstrual cycle with a better function during the peak of estradiol or when the ratio of estradiol to progesterone is high. Third, menopause marks the onset of hearing loss in women, characterized by a rapid decline in hearing sensitivity and a more pronounced loss than in age-matched men. Finally, the systematic review highlights the need for well-designed and -controlled studies to evaluate the influence of estradiol and progesterone on hearing by consistently including control groups (e.g., age-matched man), using objective tests to measure hormonal levels (e.g., in saliva or blood), and by testing participants at different points across the menstrual cycle. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020201480, identifier CRD42020201480.

Dynamic event-triggered controller design for nonlinear systems: Reinforcement learning strategy

The current investigation aims at the optimal control problem for discrete-time nonstrict-feedback nonlinear systems by invoking the reinforcement learning-based backstepping technique and neural networks. The dynamic-event-triggered control strategy introduced in this paper can alleviate the communication frequency between the actuator and controller. Based on the reinforcement learning strategy, actor–critic neural networks are employed to implement the n-order backstepping framework. Then, a neural network weight-updated algorithm is developed to minimize the computational burden and avoid the local optimal problem. Furthermore, a novel dynamic-event-triggered strategy is introduced, which can remarkably outperform the previously studied static-event-triggered strategy. Moreover, combined with the Lyapunov stability theory, all signals in the closed-loop system are strictly proven to be semiglobal uniformly ultimately bounded. Finally, the practicality of the offered control algorithms is further elucidated by the numerical simulation examples.

The limiting zero dynamics of discrete-time system based on forward triangle sample-and-hold.

Zero dynamics have crucial effect on system analysis and controller design. In the control analysis process, system performance is influenced by the unstable zero dynamics, greatly. This study concerns with the properties of limiting zero dynamics when the signal of controlled continuous-time systems was reconstructed by forward triangle sample-and-hold (FTSH). FTSH is a newly sample and hold method in the signal reconstruction area. However, more theoretical details about the limiting zero dynamics of the resulting discrete-time systems need to be revealed. Firstly, the framework for the limiting zero dynamics in the situation of sufficiently small or large sample period is introduced. Furthermore, this study provides the stable conditions of limiting zeros in the two different sampling situations. The results indicate that one can select a suitable variable parameter value of FTSH to replace the sampling zeros of discrete-time system locate inside the stable region. This paper also reveals the truth that FTSH has the outstanding advantage compared with the BTSH using theoretical analysis method. Finally, example simulations verify the effectiveness of the results in this study.

Adaptive backstepping control design for ATMD systems in nonlinear structures with nonlinear disturbance and parametric uncertainties

Active tuned mass damper (ATMD) devices are recommended in various structures to reduce vibrations. The performance of the ATMD system is closely tied to the control design utilized, according to research in the literature. The designed control input will take into account as much system dynamics as possible, making it possible to use it as a generalized controller in all similar systems. Nonlinear behavior is the natural behavior of engineering structures, and in order to obtain a more realistic and high-performance ATMD system, it can be considered as an appropriate approach to design the controller by considering the structural nonlinearities. In addition, unexpected external influences and parameter uncertainties must be taken into account during control design to ensure that control systems perform successfully in similar systems in all conditions. Therefore, in this study, the nonlinear model of the multi-story building was reconstructed by adding nonlinear disturbance to represent unknown external effects. Band-limited white noise is used as a disturbance function and Gaussian white noise is added to measured states in this study. To obtain a robust controller, unknown structural parameters are compensated for by using adaptive compensation terms. With the controller design supported by the Lyapunov-based stability analysis, the stability of the vibrating structure featuring an ATMD is theoretically guaranteed while achieving the main control goal. Performance analyses of the designed controllers are carried out with simulation studies. The efficiency of the developed Lyapunov-based controller in dampening the unwanted vibrations that occurred on the building is seen in simulation results.

Suboptimal controller design of global active noise control system for various acoustic environments

Conventional active noise control (ANC) systems in enclosed spaces are not easy to implement experimentally because they require a large number of microphones to measure sound pressure in global areas. Even if such systems are possible, if there are any changes in the locations of noise sources or surrounding objects, or if ANC system moves to another enclosed space, an expensive and time-consuming experimental calibration is again required. Implementation of global ANC in enclosed spaces is thus difficult. Therefore, we designed a global ANC system that can be used in various acoustic environments. The main idea involves suboptimal open-loop controller design in the free field. By using an open-loop controller, a controller calibrated once can be used in various acoustic environments. A controller designed in the free field derive a suboptimal solution without bias toward a specific acoustic environment. For controller design in the free field, we propose an experimental calibration approach in which the arrangement and the number of control speakers and microphones are determined by the frequency range and radiation pattern of the noise source. We conducted simulations and experiments to show that the designed controller in the free field is sufficiently effective in other enclosed spaces.

Reduced-Complexity LMI Conditions for Admissibility Analysis and Control Design of Singular Nonlinear Systems

We present a reduced-complexity control approach for a class of descriptor nonlinear systems with a nonlinear derivative matrix, possibly singular. To this end, a systematic approach is proposed to obtain an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">equivalent</i> polytopic representation of a given nonlinear system within a compact set of the state-space. This modeling approach has two particular features compared to the related Takagi–Sugeno (T–S) fuzzy model-based framework. First, the model complexity only grows <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">proportionally</i> , rather than exponentially, with the number of premise variables. Second, the vertices of the proposed polytopic models can admit an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infinite</i> number of representations for the same predefined set of premise variables. This <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nonuniqueness</i> feature allows introducing some specific slack variables at the modeling step to reduce the control design conservatism. Based on the proposed polytopic representation and Lyapunov stability theory, we derive reduced-complexity admissibility analysis and design conditions, expressed in terms of linear matrix inequalities, for the considered class of descriptor systems. In particular, a new nonlinear control law is proposed for regular descriptor systems to avoid using the extended redundancy form, which may yield numerically complex and conservative results due to the imposed special control structure. Both numerical and physically motivated examples are given to demonstrate the interests of the new control approach with respect to existing T–S fuzzy model-based control results.

Adaptive Fuzzy Appointed-Time Control for Uncertain Systems Bounded by Positive Functions

This brief presents an appointed-time prescribed performance control design for uncertain nonlinear systems via adaptive fuzzy technique. Compared with existing results, the controller achieves appointed-time tracking control for higher-order nonlinear systems with uncertainties bounded by positive functions. Firstly, barrier Lyapunov functions integrated with appointed-time prescribed performance functions are designed to cope with the requirements of output constraints and quantitative performance constraints. Then, adaptive fuzzy systems are constructed to approximate the unknown continuous upper-bound functions of the uncertainties. Subsequently, through the backstepping framework, a novel adaptive fuzzy appointed-time control scheme is proposed for the uncertain nonlinear system bounded by positive functions. Thus, the appointed settling time, predetermined steady-state error, and quantitative transient-state performance of the closed-loop system are ensured. Finally, the fixed-time convergence of the closed-loop system is proved via Lyapunov analysis, while comparative simulations are conducted to illustrate the superiority of the proposed scheme.

Controller design of robot nonlinear system based on the improved fuzzy sliding mode control

In this paper, the input-output finite time stability of fuzzy sliding mode control in nonlinear robot systems is discussed. Specifically, the system considers more realistic factors, such as uncertainty, nonlinearity, interference, and state delay. An improved fuzzy sliding mode control (FSMC) scheme is developed, which is considered in most results of FSMC schemes. Based on the input-output finite-time stability characteristics and the proposed control scheme, the objective of this work is to reduce the effects of uncertainty, nonlinearity, disturbance, and state delay. Finally, the effectiveness and superiority of the proposed method are verified by simulation and comparison with other reference methods.

Fixed-Frequency PWM Control and Stability of Series-Stacked Buffer for 2ω-Power Decoupling

Active second-harmonic ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\omega $ </tex-math></inline-formula> ) filters have become an integral technology for single-phase power converters in high-power density designs. The series-stacked buffer (SSB) has emerged as an attractive topology among the existing solutions due to its low power, high efficiency, and compact design. However, one of the challenges in adopting SSB lies in its control, where hysteresis current control has been adopted conventionally. This results in a wide variation in the switching frequency, making the digital control implementation and filter design complex. On the other hand, fixed-frequency pulsewidth modulation (PWM) control necessitates developing a model for the systematic controller design to ensure stability and desired filtering performance. The assumption of SSB modeled as a second-harmonic current source, independent of the dc bus circuit components, fails to capture the dc bus loading effect on the SSB. In this work, a dynamic model of SSB is developed where the main dc bus and its passive elements are considered. The derived model enables a systematic approach for the controller design while ensuring the desired <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\omega $ </tex-math></inline-formula> filtering. The stability limits and parameter sensitivities of the model are studied analytically and in simulations. The analytical model is validated, and the proposed controller performance and stability limit are verified experimentally on a hardware prototype. A video demonstrating the transition from stable to unstable operation is provided.

Improved Dynamic Event-Triggered Control for Nonlinear Systems with Fading Channels

This paper is devoted to the protocol-based control design for nonlinear systems with fading channels. Distinguished from the existing event-triggering criteria associated with only two consecutive packets, an improved dynamic event-triggered protocol is formulated, which accounts for some historical available transmitted packets. As a consequence, the number of triggering times can be reduced efficiently while maintaining desired control performance. Meanwhile, the time-varying fading channel is described by a Markov process within finite space, whose mode can be detected via a hidden Markov mode detector. Based on Lyapunov stability theory, sufficient conditions are derived to achieve the stochastic stability of the closed-loop system. In the end, the validity of the derived results is verified through an application study.

Design of Multivariate PID Controller for Power Networks Using GEA and PSO

The issue of proper modeling and control for industrial systems is one of the challenging issues in the industry. In addition, in recent years, PID controller design for linear systems has been widely considered. The topic discussed in some of the articles is mostly speed control in the field of electric machines, where various algorithms have been used to optimize the considered controller, and always one of the most important challenges in this field is designing a controller with a high degree of freedom. In these researches, the focus is more on searching for an algorithm with more optimal results than others in order to estimate the parameters in a more appropriate way. There are many techniques for designing a PID controller. Among these methods, meta-innovative methods have been widely studied. In addition, the effectiveness of these methods in controlling systems has been proven. In this paper, a new method for grid control is discussed. In this method, the PID controller is used to control the power systems, which can be controlled more effectively, so that this controller has four parameters, and to determine these parameters, the optimization method and evolutionary algorithms of genetics (EGA) and PSO are used. One of the most important advantages of these algorithms is their high speed and accuracy. In this article, these algorithms have been tested on a single-machine system, so that the single-machine system model is presented first, then the PID controller components will be examined. In the following, according to the transformation function matrix and the relative gain matrix, suitable inputs for each of the outputs are determined. At the end, an algorithm for designing PID controller for multivariable MIMO systems is presented. To show the effectiveness of the proposed controller, a simulation was performed in the MATLAB environment and the results of the simulations show the effectiveness of the proposed controller.

Novel extreme seeking control framework with ordered excitation and nonlinear function based PSO: Method and application

The performance of a photovoltaic power system is heavily influenced by mismatches, for example, partial shading effects. In literature, it lacks of a scrupulous study on intelligent control designs whose transient responses and steady state responses are not directly given when achieving the goal of global maximum power point tracking (GMPPT). A novel and systematic control design approach is proposed mathematically to derive explicit discrete controllers for the overall GMPPT performance. Specifically, the new algorithms of nonlinear function (NF) based particle swarm optimization (PSO) and ordered excitation (OE) are incorporated into the extreme seeking controller for the enhancement of both transient and steady state responses when fulfilling the extreme seeking task. The explicit control functions are easy to implement in the applications. Both the simulation based analysis and experimental study are carried out in a statistical manner in order to evaluate the proposed controller through a number of control performance indicators. A comparison analysis of the statistical data reveals that both simulation and experimental results agree with the theory where both algorithms of NF-PSO and OE play a role to improve transient responses and steady state responses for the global extreme seeking. Meanwhile, the proposed intelligent controller outperforms the classical benchmark in tracking the GMPP. The insightful and instructive control design tool is promising in both academia and engineering.

Event-Triggered Sliding Mode Neural Network Controller Design for Heterogeneous Multi-Agent Systems

A class of heterogeneous second-order multi-agent consensus problems is studied, in which an event-triggered method is used to improve the feasibility of the control protocol. The sliding mode control method is used to achieve the robustness of the system. A special type of general radial basis function neural network is applied to estimate the uncertainties. The event-triggered mechanism is introduced to reduce the update frequency of the controller and the communication frequency among the agents. Zeno behavior is avoided by ensuring a lower bound between two adjacent trigger instants. Finally, the simulation results are provided to demonstrate that the time evolution of consensus errors eventually approaches zero. The consensus of multi-agent systems is achieved.

Fixed-order H-infinity controller design for port-Hamiltonian systems

We present a new fixed-order H-infinity controller design method for potentially large-scale port-Hamiltonian (pH) plants. Our method computes controllers that are also pH (and thus passive) such that the resulting closed-loop systems is again passive, which ensures closed-loop stability simply from the structure of the plant and controller matrices. In this way, we can avoid computationally expensive eigenvalue computations that would otherwise be necessary. In combination with a sample-based objective function which allows us to avoid multiple evaluations of the H-infinity norm (which is typically the main computational burden in fixed-order H-infinity controller synthesis), this makes our method well-suited for plants with a high state–space dimension.In our numerical experiments, we show that applying a passivity-enforcing post-processing step after using well-established H-infinity synthesis methods often leads to a deteriorated H-infinity performance. By contrast, our method computes pH controllers, that are automatically passive and simultaneously aim to minimize the H-infinity norm of the closed-loop transfer function. Moreover, our experiments show that for large-scale plants, our method is significantly faster than the well-established fixed-order H-infinity controller synthesis methods.

Design and Assessment of an Anti-lock Braking System Controller

"The anti-lock braking system is a safety equipment that prevents the vehicle wheels from locking up under emergency, panic, or harsh braking conditions, ensuring steering control during braking and reducing braking distance. This system is studied by automotive engineers for performance comparisons and for determining optimal control methods. For this reason, this paper presents a method to mathematically model the anti-lock braking system. The obtained model is afterwards used inside a Simulink simulation to investigate the results with and without the anti-lock braking system and to propose a three-position regulator instead of the generally used bang-bang controller. The simulation results show the improvement of the vehicle braking time and braking distance."

Tracking control design for fractional order systems: A passivity-based port-Hamiltonian framework

This article focuses on the design of tracking control for chaotic fractional order systems subjected to perturbations in a port-Hamiltonian framework. The fractional order systems of general form are modeled into port-controlled Hamiltonian form. Then, the extended results on the dissipativity, energy balance, and passivity of the fractional order systems are proved and presented in this paper. The port-controlled Hamiltonian form of the fractional order systems are proved to be asymptotically stable via energy balancing concept. Furthermore, a tracking controller is designed for the fractional order port-controlled Hamiltonian form by utilizing the matching conditions of the port-Hamiltonian systems. Stability of the system is established and analyzed explicitly for the closed-loop system with the help of direct Lyapunov method. Finally, an application example is solved with simulation results and discussions to prove the effectiveness of the propounded control design approach.

Optimal interval controller design for uncertain systems

AbstractThe interval controller design is a hot issue for uncertain systems, whereas how to design an optimal interval controller under the premise of ensuring system stability is a difficult problem that needs further study. This paper mainly aims at the single input single output uncertain system to propose an optimal interval controller based on the Kharitonov theorem and an interval optimization algorithm, which can guarantee the stability and optimization of a closed‐loop interval system. According to the Kharitonov theorem, the optimal interval controller design can be transformed into an optimal controller synthesis issue of multiple vertex objects. An interval particle swarm optimization (IPSO) algorithm is then used to optimize the quadratic performance index with interval variables for each vertex object to obtain the solution domains of the controller parameters, and the vertex method is utilized to prevent interval width expansion or divergence in the iteration. Finally, the intersections of the solution domains for all vertex objects are obtained as the optimal interval solution of interval controller parameters. In addition, the stability verification approach of the closed‐loop system and the empirical rule to select the interval particle width are given. Simulation results for typical examples demonstrate that the designed interval controller not only performs optimally but also can robustly stabilize the interval system.

General-purpose Feedforward Control Design for Heating Process System

In this paper, general-purpose feedforward control design for heating process systems is described. The feedforward control function should be implemented to a local PID temperature controller. The controller is supplied to the heating process equipment manufacturer. In composition of the business, the adequacy of the relations between companies of the control technology is an important issue.

The multi-point hydraulic control method for advanced controller design of the open canal irrigation systems

Abstract Most studies about the automatic control of open canal irrigation systems only focus on the distant downstream water level, which ignores the fact that the offtakes may be located anywhere along the canal. Such a simplified control strategy is likely to result in uncontrollable and inefficient water delivery. Therefore, a multi-point hydraulic control method is proposed, in which a simplified Saint-Venant model is formulated to describe the hydraulic states of multiple controlled points. Then, it is underlined that the controlled points with and without the offtakes may have different control objectives. It is suggested to implement soft constraints to the downstream end when there is no offtake, meaning that moderate water level fluctuations are acceptable. By comparing with the common model predictive control (MPC) controller, where the Integrator Delay model and hard constraint are used for distant downstream water level control, the proposed MPC controller successfully improved the water level control stability before the offtakes and the water supply reliability by 91 and 69.5% under the conventional condition and by 54.9 and 27.1% under the water-deficient condition. Accordingly, the proposed multi-point hydraulic control method shows great potential for the precision irrigation of large irrigation districts.

An LMI framework for contraction-based nonlinear control design by derivatives of Gaussian process regression

Contraction theory formulates the analysis of nonlinear systems in terms of Jacobian matrices. Although this provides the potential to develop a linear matrix inequality (LMI) framework for nonlinear control design, conditions are imposed not on controllers but on their partial derivatives, which makes control design challenging. In this paper, we illustrate this so-called integrability problem can be solved by a non-standard use of Gaussian process regression (GPR) for parameterizing controllers and then establish an LMI framework of contraction-based control design for nonlinear discrete-time systems, as an easy-to-implement tool. Later on, we consider the case where the drift vector fields are unknown and employ GPR for functional fitting as its standard use. GPR describes learning errors in terms of probability, and thus we further discuss how to incorporate stochastic learning errors into the proposed LMI framework.