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In the DC distribution networks, DC bus voltage is maintained by the grid-connected converter; the controllability and reliability of the grid-connected converter significantly affect the bus voltage characteristic. To address the problem of limited stability and frequent oscillations, this paper proposes a state feedback control method for the AC/DC converter. Conventional AC/DC converter adopts the voltage-current double-closed-loop control structure with the proportional-integral (PI) controllers, which is the equivalent of the typical type II control system, but the typical type II control system cannot fully settle the stability and immunity problems. In contrast, the state feedback control strategy not only achieves the control objectives of the traditional double-closed-loop control but also reduces the AC/DC converter system model to a typical Type I system, which improves stability and thus enhances the oscillation suppression capability of the bus voltage. By selecting multiple state variables and designing the converter pole configuration range, the proposed single-loop state feedback control method manages to optimize both the dynamic and steady-state performances of the grid-connected AC/DC converter. Finally, the effectiveness of the proposed single-loop state feedback control strategy is verified through MATLAB (2018b)/Simulink software simulation and experiments on a DC distribution network platform. [ABSTRACT FROM AUTHOR]

This study focuses on a model reference adaptive control method that ensures identical orientation outputs for different prototypes of a two‐axis gimbal produced in mass production. In this method, unlike traditional MRAC structures, an MRAC structure is used in conjunction with state feedback control. First, the reasons for the need for an adaptation mechanism in gimbals and why Model Reference Adaptive Control (MRAC) alone won't be sufficient have been discussed. In the first section, various applications of MRAC have also been mentioned. Then, the mathematical foundation of the model reference adaptive controller used in this study is elaborately explained, followed by stability analyses. In the next step, an ideal reference model exhibiting desired behavior and a real system model with different dynamics are created in a simulation environment. This allows a comparison of the adaptation capabilities of only MRAC and MRAC+State Feedback controllers. Based on the information gathered in this section, the recommended approach in the article is tested on a real gimbal system, and the results are shared. The obtained results demonstrate that the MRAC+State Feedback control structure significantly reduces the error in the gimbal's orientation response compared to the reference model. [ABSTRACT FROM AUTHOR]

ABSTRACT Series active filter (SAF) is generally utilized in compensating harmonic voltage source‐type loads. In this paper, a combined action of controller and observer is proposed for SAF. Full state feedback (SFB) and linear quadratic regulator (LQR) controllers are posited in order to estimate states, and fault. SFB utilizes the pole placement method, whereas LQR utilizes the tuning of matrices by Bryson's rule. Luenberger observer (LO), proportional–integral observer (PIO), and unknown input observer (UIO) were also designed. The efficacy of this scheme is illustrated through the simulations, in the presence of faults. The state dynamics of SFB‐ and LQR‐based control of SAF with LO, PIO, and UIO in different faulty cases are compared. It can be clearly seen through simulations that the state dynamic response of LQR‐based control of SAF is faster when compared to SFB‐based control of SAF in both cases. Further, LO and PIO established a steady‐state error between the actual state and its estimate, with reference to desired input, in the presence of a fault. UIO perfectly tracked the desired input, even in the presence of various unknown fault, when compared to LO and PIO. Furthermore, UIO also estimates the unknown faults better when compared to PIO. Finally, in a dynamic operating scenario, the effectiveness of the suggested control strategy has been assessed and verified using MATLAB/SIMULINK and the output of a real‐time simulator (OPAL‐RT OP4510). [ABSTRACT FROM AUTHOR]

In this paper, the approximate synchronization of leader-follower multiagent systems (MASs) over finite fields is studied in regard to local and global synchronization. First, the approximately synchronous state set (ASSS) is obtained. Second, combined with ASSS and transient periods, some criteria for the local and global approximate synchronization of systems are given. Moreover, the algorithms for calculating the maximum approximately synchronous basin (MASB) and the maximum control invariant set (MCIS) are presented. Third, the global approximate synchronization of the system is achieved by designing the state feedback control, and a design algorithm of the controller using the truth matrix method is proposed. Moreover, the results of approximate synchronization are degenerated to complete synchronization. Last, two examples are shown to demonstrate the results of this paper. [ABSTRACT FROM AUTHOR]

In several applications, the accuracy and robust performance of the control method for the speed of permanent magnet synchronous motors (PMSMs) is critical. Model uncertainties, caused by inaccurate model identification, decrease the accuracy of PMSM control. To solve this problem, this paper presents a super robust control structure for the speed control of PMSMs. In the proposed method, the model uncertainties with Lipschitz condition together with disturbances are considered during the PMSM modeling, and their effects are handled using a robust state feedback control. To be more specific, the Lyapunov stability proof is performed in such a way that the model uncertainty effects are eliminated. Before that, the Lyapunov stability criteria have been selected in such a way that the Hꝏ conditions are considered and guaranteed. This issue helps to eliminate the effects of the disturbances. In addition, this paper considers another option to make the whole control structure robust against sudden load changes. To solve this problem, a fuzzy adaptive sliding mode observer (FASMO) is presented to determine the load torque and use it in the control signal generation. In this observer, the switched gain of the sliding mode observer (SMO) is adapted using a fuzzy system to eliminate the chattering phenomena and increase the estimation accuracy. In fact, the proposed method is called super robust because it resists model uncertainties, disturbances, and sudden load changes during three stages by robust state feedback control, Hꝏ criterion, and load estimator, respectively. The performance of the proposed approach is validated through a set of laboratory tests, and its superiority is shown compared to other methods. [ABSTRACT FROM AUTHOR]

This paper presents a novel zero-power controller applied to a four-unit magnetic levitation system, aimed at addressing the challenge of maintaining stability under disturbance loads. The zero-power controller, designed based on a state feedback controller integrated with a position servo integrator, is primarily employed to control the balance of the magnetic levitation (Maglev) unit and eliminate steady-state errors. Subsequently, the zero-power controller operates after the state feedback controller to adjust the Maglev unit to a new equilibrium point, primarily utilizing permanent magnetic force to suspend against gravitational input. When loads change or disturbances occur, the system generates current to maintain balance. All designs have passed validation. Experimental results demonstrate the improved zero-power performance and disturbance rejection capabilities of the proposed Maglev system. During synchronous operation, dynamic characteristics have shown significant improvement, which has been experimentally confirmed. [ABSTRACT FROM AUTHOR]

This article aims at designing a robust wide-area damping controller (WADC) to address the problems associated with communication failures. The proposed controller is a state feedback-based controller, which uses generators' states as the controller inputs. The structure of the proposed controller's feedback gain matrix is a combination of two feedback gain matrices to achieve adequate robust performance over different disturbances and communication losses. These two feedback gain matrices are; full-scale feedback gain matrix and decentralized scale feedback gain matrix. Both models are designed by considering all generators' states are available at the controller input side. However, both matrices' structures are different from each other. The conventional LQR state feedback control technique is used to design the full-scale matrix. On the other hand, the decentralized scale matrix is computed using a structurally constrained H 2 -norm optimization technique to acquire the required structure. The full-scale model gives robust performance under different faults. Whereas, the decentralized scale matrix will result robust performance against communication failures. Therefore, to achieve superior performance under all conditions, the proposed controller can be used. To show the efficacy of the proposed controller, it is compared with different existing controllers and the results are illustrated. Simulation studies are conducted on well-known IEEE 39-bus and 68-bus test systems to validate the robustness of the proposed controller considering different faults and communication failures. [ABSTRACT FROM AUTHOR]

In this paper, a two-neuron reaction–diffusion neural network with discrete and distributed delays is proposed, and the state feedback control strategy is adopted to achieve control of its spatiotemporal dynamical behaviours. Adding two virtual neurons, the original system is transformed into a neural network only containing the discrete delay. The conditions under which Hopf bifurcation and Turing instability arise are determined through analysis of the characteristic equation. Additionally, the amplitude equations are derived with the aid of weakly nonlinear analysis, and the selection of the Turing patterns is determined. The simulation results demonstrate that the state feedback controller can delay the onset of Hopf bifurcation and suppress the generation of Turing patterns. [ABSTRACT FROM AUTHOR]

This research tries to stabilise a three degree-of-freedom series-type double inverted pendulum system by employing an adaptive state feedback control approach optimised by a particle swarm optimisation (PSO) algorithm. To this end, the dynamical equations are derived via Lagrangian method and linearised by utilising approximation approaches. Then, the state feedback scheme is implemented to control the system states, that is, the angle and angular velocity of the first and second poles as well as the position and velocity of the cart. In order to timely regulate the control gains, the adaptation rules based on the gradient descent method and sliding surface relations are applied. The particle swarm optimisation algorithm is implemented to optimally tune the design parameters of the controller based on a proper objective function defined as summation of integrals of absolute values of the system errors. The time responses of the angles of the poles and the position of the cart clearly depict the feasibility and efficiency of the introduced control strategy to stabilise the system from different initial conditions to the final desired values. [ABSTRACT FROM AUTHOR]

A new method for the design of event-triggered stabilizing state feedback controllers for nonlinear fractional-order interconnected systems is proposed in this paper. A new condition for the existence of state feedback controllers ensuring the closed-loop system is asymptotically stable is established based on fundamental mathematical transformations and linear matrix inequalities. Two numerical examples with simulation results are provided to demonstrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper proposes a systematic control design for a single-phase LCfiltered inverter considering uncertain system parameters. One major difficulty in controlling single-phase power converters is the lack of a direct conversion method for transforming single-phase signals into dq-frame signals. By employing an all-pass filter in this proposed approach, it is possible to control the output voltage in terms of DC quantity or the dqrotating frame. Furthermore, voltage stability and harmonic distortion (THD) minimization of the uninterruptible power supply (UPS) are major concerns in inverter design. Therefore, this controller uses integral action to get rid of steady-state errors and stabilize the closed-loop system by the state feedback control. In order to enlarge and guarantee the stability range in the presence of potential parameter fluctuations, an uncertainty model is being considered. In this context, the uncertainty models refer to the potential model with variations in the filter's inductance and capacitance caused by operating temperature, aging, and various external factors. The efficacy of the control approach is assessed through simulations and experiments, with the objective of comparing its results with those of the PI control using a control board featuring a TMS320F28335 digital signal processor. Consequently, the proposed approach offers lower THD at every load step with lesser afford in performance tuning in comparison to the PI method. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a new control system by integrating integral state feedback control and sliding mode control to eliminate the influences from the reference input change, external load, and parameter variations. For most control systems, integral action is used to overcome the reference input change and external load. However, its control performance cannot be guaranteed. State feedback control is used to dominate the pole location of the closed-loop control system. However, the system parameters determine their pole locations and may change due to uncertainties. Thus, the characteristics of the closed-loop control system are changed. Sliding mode control is used to compensate for the effect of the parameter variations and make the system invariant. The resulting system combines linear state feedback and sliding mode control to guarantee the desired performance. This shows that the proposed system can be easily applied and designed. A servo control system is used to demonstrate the performance, and simulations and experiments are carried out to evaluate the newly defined structure. They show that the strategies and control design can reach robust performance even with uncertainties or external load, and the chattering of the sliding mode control can be minimized. [ABSTRACT FROM AUTHOR]

This work mainly addresses the state feedback control with D-admissible assurance for descriptor systems subjected to perturbed derivative and systems’ matrices simultaneously. By the linear matrix inequality (LMI) and matrix algebra manipulation, extended admissible and D-admissible analysis criteria are first presented for the regarded systems. The distinct results introduce a set of slack matrices for reducing the conservatism of the analyzing criteria, and a numerical example is given for demonstration. By involving the state feedback control, the controller design scheme can be performed for admissible and D-admissible assurance of the closed system. Since all the conditions can be formed in terms of the strict LMIs, existing LMI tools are proper for evaluation. Finally, two design examples, a numerical example and an extended RLC circuit paradigm, illustrate the validation and feasibility of the results.

In several applications, the accuracy and robust performance of the control method for the speed of permanent magnet synchronous motors (PMSMs) is critical. Model uncertainties, caused by inaccurate model identification, decrease the accuracy of PMSM control. To solve this problem, this paper presents a super robust control structure for the speed control of PMSMs. In the proposed method, the model uncertainties with Lipschitz condition together with disturbances are considered during the PMSM modeling, and their effects are handled using a robust state feedback control. To be more specific, the Lyapunov stability proof is performed in such a way that the model uncertainty effects are eliminated. Before that, the Lyapunov stability criteria have been selected in such a way that the Hꝏ conditions are considered and guaranteed. This issue helps to eliminate the effects of the disturbances. In addition, this paper considers another option to make the whole control structure robust against sudden load changes. To solve this problem, a fuzzy adaptive sliding mode observer (FASMO) is presented to determine the load torque and use it in the control signal generation. In this observer, the switched gain of the sliding mode observer (SMO) is adapted using a fuzzy system to eliminate the chattering phenomena and increase the estimation accuracy. In fact, the proposed method is called super robust because it resists model uncertainties, disturbances, and sudden load changes during three stages by robust state feedback control, Hꝏ criterion, and load estimator, respectively. The performance of the proposed approach is validated through a set of laboratory tests, and its superiority is shown compared to other methods.

This paper investigates an improved fixed-time stability theory together with a state feedback controller for a class of nonlinear stochastic systems. First, a delicate transformation is performed, and next, a Gamma function is utilized to directly derive the value of the integral function, which ultimately yields a fixed-time stabilization theorem with a higher precision upper bound for the settling time. Unlike the existing estimation process of amplifying twice, we only performed one amplification, which weakens the effect of amplification. Then, a state feedback controller is constructed for stochastic systems by the method of adding a power integrator. Utilizing the proposed stochastic fixed-time stability theory, simulations show that the intended controller ensures that the trivial solution of the suggested system is fixed-time stable in probability. The results of the simulation demonstrate that the suggested control scheme is meaningful. [ABSTRACT FROM AUTHOR]

In this paper, the control problem for a novel walking assistance training robot is considered where the main objective is utilizing the robot to control the tilt angle and the position of a user. First, the novel walking assistance training robot together with a user is modeled as a nonlinear dynamical system in state space form with control input where the control input includes two elements standing for pulling forces on two straps which attach to the chest and back, respectively, of the user. Then, based on the nonlinear dynamical system and some results proposed in this paper, a feedback control system is developed, and a nonlinear state feedback control algorithm is designed where the control input includes two parts, namely, a dynamical part and a constant part. By doing this, it is ensured that the feedback control system is stable, and achieves the main objective under some limits for the control input. A simulation example is given to illustrate the effectiveness and performance of the proposed nonlinear state feedback control algorithm. [ABSTRACT FROM AUTHOR]

This paper studies the problems of both state estimation and observer-based control for a class of switched linear systems with stable and unstable subsystems. By combining slow switching and fast switching mechanism, the observer design and observer-based controller are presented. Firstly, a state observer is developed to estimate the states of switched system by designing admissible edge-dependent switching signal, and a multiple discontinuous Lyapunov function is also constructed to obtain the existence condition of observer. Secondly, based on the stability characteristics of subsystem and the estimated state information, an observer-based feedback controller is proposed. The stability of the closed-loop system is also guaranteed by Lyapunov stability theory. Finally, the feasibility of the proposed method is verified by simulation. [ABSTRACT FROM AUTHOR]

Controlling a PWM rectifier can be challenging due to the bilinear nature of its averaged model. This paper introduces the use of the Butterworth approach to design and control an LCL-filter-based PWM rectifier with power quality functions. By leveraging the linear part of the system, this approach reduces the number of variables involved in the control scheme. The rectifier is designed and controlled in a concatenated manner to ensure proper performance even during demanding power-quality events. The uniqueness of this approach lies in the fact that a fourth-order model can be regulated by using solely three-state variables and linear techniques founded on Butterworth polynomial synthesis. This approach differs from previous methods in that it does not employ nonlinear controllers, dq transformations, or double control loops. Hence, this divergent approach contributes to the simplification of power converter design and control through the application of the same polynomial synthesis, besides enhancing system operation in demanding scenarios. Extensive SIL simulations of a 1 kW, 220 Vrms PWM rectifier using the OPAL-RT-1400 platform were conducted to demonstrate the feasibility of the proposed controller. The selected tests reveal the validity of this proposal even when the PWM rectifier faces multiple power quality events simultaneously. [ABSTRACT FROM AUTHOR]

In recent years, servo proportional valves have been widely used in the industry owing to the advantages of high stability and low cost. However, the nonlinearity and parameter uncertainty present in the servo proportional valves make it difficult to control the spool position. This paper proposes a state feedback control with integral compensation for the spool displacement control of the servo proportional valve, which aims to solve the problem that state feedback is difficult to overcome system nonlinearity and parameter uncertainty. The key to this control method is the addition of an outer loop negative feedback and an integral element. At the same time, the control method can realize pole configuration, convenient control parameter adjustment, low hardware requirements, and easy engineering application. Experimental and simulation results show that the integral element can compensate for the system's nonlinearities and uncertain parameters, and eliminate the steady-state error of displacement tracking. The state feedback with integral compensation can improve the frequency response of the servo proportional valve compared to traditional PID control. [ABSTRACT FROM AUTHOR]

This paper presents the experimental magnetic levitation control development of Sanki Engineering airport luggage conveyor carts which have four magnetic levitation units working synchronously. With the PID controller, the state feedback controller and the zero-power controller refined by PID controller were implemented in the one magnetic levitation unit system and four-unit magnetic levitation system, and the displacement and the current were verified in a real-time system. The magnetic levitation unit had a fast response, and the control algorithms were easily implemented. The change of current and displacement were compared. In the one-unit system, the PID and state feedback controller react to the disturbance at the same speed and have similar power consumptions. For a disturbance on the zero-power controller, the system generates a transient current to deal with the load disturbance and finally settles to 0 A. The PID control for four magnetic levitation units of the conveyor cart has a better stable performance during synchronous operation. Under the control of state feedback controller, they can keep the cart statically stable with some oscillation. These characteristics are experimentally confirmed. [ABSTRACT FROM AUTHOR]

Three-wheeled electric city vehicles are becoming popular because they have lower cost and enable motorcycle driving feeling with electric powertrain performance. These vehicles need a driver assistant system, also known as an active tilting stability controller, to provide a safe cornering manoeuvre. Active tilt control methods are direct tilt control (DTC), steering tilt control (STC) and a combination of these methods. In this study, DTC system design with a servo motor actuator with simulation and experimental results are presented. State feedback control with pole placement design has been improved with disturbance compensation control. This novel controller structure enhances the response of DTC and enables a faster-tilting response. Simulation results are given up to 10 m/s speed. Experimental results of the developed method are given up to 3.05 m/s (11 km/h) speed on a three-wheeled electric vehicle. The speed control loop of the servo motor drive unit (SMDU) stabilizes the DTC system. In the state of the art, a proportional derivative controller is commonly used as a tilt controller. By including the speed control loop of SMDU in the tilt control system, the use of the derivative term can be eliminated. The stability effect of the speed control loop is shown by MATLAB analysis, simulations in Simulink and experimental step response test as well. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the finite-time boundedness problems for large-scale continuous-time networked dynamical systems constituted by lots of subsystems. The interactions among these subsystems are arbitrary, and every subsystem has different dynamics. The linear time-varying and time-invariant cases are discussed respectively. Sufficient conditions for the design of finite-time boundedness state feedback controller are derived, which efficiently utilize the characteristic of system structure with the block-diagonal structure of system parameter matrices and the sparseness of the system topology. Sufficient conditions depending only on parameter matrices of the individual subsystem are also provided. Furthermore, sufficient conditions are provided for the design of the distributed output feedback controller with finite-time boundedness. Several numerical simulations have been used to show the validity of the derived conditions in the analysis of a large-scale networked system.

The paper presents applications of homomorphic cryptographic schemes in process control. Homomorphic encryption is a particular type of encryption that allows performing mathematical operations over encrypted data. Therefore the user can use third-party services as controllers without revealing any vulnerable information, like process data. Homomorphic properties make it possible to perform data aggregation or evaluate control actions without having any knowledge about the process data. Our paper explores two fully homomorphic cryptographic schemes, namely Brakerski/Fan-Vercauteren (BFV) and Cheon-Kim-Kim-Song (CKKS) cryptosystems. Each scheme is briefly described with its advantages and drawbacks, conditions, and applications. We present a case study involving hl linear-quadratic (LQ) control strategy implemented in an encrypted setup. This serves for comparison and a step-by-step guide for implementing encrypted process control.

Signal sensing periods typically vary depending on the sensor used and may differ even within a single control system that involves multiple sensors. Likewise, input periods can vary based on the actuator used. This paper discusses the design of observer-based feedback controllers for linear, time-invariant, discrete-time systems operating in a multi-rate sensing and actuating environment. The observation and control periods of the sensors and actuators in the plant are assumed to have mutually rational ratios. First, we reduce the multi-rate system to a periodically time-varying system and provide a linear matrix inequality (LMI) condition for analyzing the $l_{2}$ performance using cyclic reformulation, which is a type of time-invariant reformulation for periodic systems. Next, we extend the analysis method to design an observer-based feedback controller for the multi-rate system. This allows us to obtain multi-rate observer gains and feedback gains based on the $l_{2}$ -induced norm from disturbances to outputs. Finally, we present numerical results to demonstrate the effectiveness of the observer-based feedback system in the multi-rate environment.

Virtual sensor, which is one of the applications of the digital twin, is effective for estimating physical quantities that are difficult to measure. This paper deals with estimation of real-time tool edge temperature by virtual sensor. The tool edge temperature is estimated by inputting the temperature data of the endmill shank obtained from the pyrometer installed in the machine tool to the simulation model created in cyber space. The simulation performed in cyberspace is an unsteady heat transfer analysis, and a state space model with a reduced order of the finite element model using Krylov subspace method is adopted as the simulation model in order to allow real-time simulation. In addition, unknown heat input to the cutting edge was calculated by state feedback control using the temperature data obtained from the pyrometer and the simulation model. The tool edge temperature during cutting was estimated in real time using the developed virtual sensor with the heat transfer analysis block and the input estimation block. The estimated tool edge temperature changed significantly in response to changes such as chipping of the tool edge. The estimated temperature and the measured temperature by the thermocouple method generally matched.

In this paper, we consider the finite-time boundedness (FTB) and finite-time stabilization boundedness (FTSB) problems for a class of nonlinear interconnected systems with Atangana–Baleanu–Caputo (ABC) fractional derivative. By employing the FTB theory and some properties of ABC fractional derivative, and some basic mathematical transformations, we derive new conditions for the FTB and FTSB problems of ABC fractional-order nonlinear interconnected systems. These conditions are formed in linear matrix inequalities (LMIs), which can be effectively solved using the MATLAB LMI Control Toolbox. Finally, two numerical examples with simulations are provided to illustrate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper we investigate the problem of a finite-time contractive control method for a spacecraft rendezvous control system. The dynamic model of relative motion is formulated by the C-W equations. To improve the convergent performance of the spacecraft rendezvous control system, a finite-time contractive control law is introduced. Lyapunov's direct method is employed to obtain the existence condition of the desired controllers. The controller parameter can be obtained with the help of the cone complementary linearization algorithm. A numerical example verifies the effectiveness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

The robust finite-time H 2 / H ∞ control problems for linear discrete-time stochastic Markovian jump systems (MJSs) with external disturbance are investigated. Firstly, the definitions of robust finite-time boundedness, and robust finite-time H 2 / H ∞ boundedness are presented. Subsequently, by using the stochastic Lyapunov–Krasovskii functional method and linear matrix inequality technique, sufficient conditions for the existence of a robust finite-time H 2 / H ∞ controller are provided for stochastic MJSs. A state feedback controller is designed. Furthermore, the finite-time guaranteed cost bounds are given. More specifically, the designed controller not only ensures the finite-time H ∞ bounded but also makes the H 2 cost function less than the bound given by the performance index of the systems. Finally, two examples are given to illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

• The state space model of NSSS of HPR1000 is established. • A state feedback controller based on the dominant pole is designed. • A new coolant average temperature control system is designed. • The particle swarm optimization (PSO) is used to optimize the relevant parameters. • The control system designed in this paper has better control performance. Control of nuclear power plant is still based on the traditional PID control system, which is difficult to obtain high control quality in the process of a wide range of load changes. To effectively use the measurable information of the system and consider the constraints, state feedback control based on the dominant pole method is proposed for the average coolant temperature control of HPR1000. The control system is divided into two parts: one part is a feedback branch, which realizes the state feedback by using the measurable system state quantity including the core inlet temperature, the core outlet temperature and the reactor power, and at the same time introduces the integral link to reduce the steady-state error; the other part is a feedforward branch, which uses the nominal load change to make feedforward compensation to improve the control performance of load tracking. At the same time, Particle Swarm Optimization (PSO) method is used to optimize the controller parameters, and the dominant pole meeting the requirements is obtained. The control performance under different working conditions is verified on the HPR1000 model. The test results show that the state feedback control can effectively improve the setpoint tracking ability and anti-disturbance ability. [ABSTRACT FROM AUTHOR]

This paper proposes a new control system by integrating integral state feedback control and sliding mode control to eliminate the influences from the reference input change, external load, and parameter variations. For most control systems, integral action is used to overcome the reference input change and external load. However, its control performance cannot be guaranteed. State feedback control is used to dominate the pole location of the closed-loop control system. However, the system parameters determine their pole locations and may change due to uncertainties. Thus, the characteristics of the closed-loop control system are changed. Sliding mode control is used to compensate for the effect of the parameter variations and make the system invariant. The resulting system combines linear state feedback and sliding mode control to guarantee the desired performance. This shows that the proposed system can be easily applied and designed. A servo control system is used to demonstrate the performance, and simulations and experiments are carried out to evaluate the newly defined structure. They show that the strategies and control design can reach robust performance even with uncertainties or external load, and the chattering of the sliding mode control can be minimized.

This paper investigates an improved fixed-time stability theory together with a state feedback controller for a class of nonlinear stochastic systems. First, a delicate transformation is performed, and next, a Gamma function is utilized to directly derive the value of the integral function, which ultimately yields a fixed-time stabilization theorem with a higher precision upper bound for the settling time. Unlike the existing estimation process of amplifying twice, we only performed one amplification, which weakens the effect of amplification. Then, a state feedback controller is constructed for stochastic systems by the method of adding a power integrator. Utilizing the proposed stochastic fixed-time stability theory, simulations show that the intended controller ensures that the trivial solution of the suggested system is fixed-time stable in probability. The results of the simulation demonstrate that the suggested control scheme is meaningful.

The control of the open loop unstable systems with nonlinear structure is challenging work. In this paper, for the first time, we present a sand cat swarm optimization (SCSO) algorithm-based state feedback controller design for open-loop unstable systems. The SCSO algorithm is a newly proposed metaheuristic algorithm with an easy-to-implement structure that can efficiently find the optimal solution for optimization problems. The proposed SCSO-based state feedback controller can successfully optimize the control parameters with efficient convergence curve speed. In order to show the performance of the proposed method, three different nonlinear control systems such as an Inverted pendulum, a Furuta pendulum, and an Acrobat robot arm are considered. The control and optimization performances of the proposed SCSO algorithm are compared with well-known metaheuristic algorithms. The simulation results show that the proposed control method can either outperform the compared metaheuristic-based algorithms or have competitive results.

To address the difficulty of controlling the dynamic stability of the system after time-varying delay of the plate thickness detection at the final stand of the hot strip finishing mill. Firstly, a T-S fuzzy model based on rolling force and thickness state is established for the final stand of the hot strip finishing mill, and the maximum time delay for plate thickness detection is divided into several time delay intervals to establish a linear constant state space model of the time delay subintervals. Secondly, a distributed state feedback controller satisfying sufficient conditions for stability is solved by using the parallel distribution compensation (PDC) principle combined with Lyapunov stability theory and linear matrix inequality (LMI) methods. Simulation comparisons with current M-AGC and Smith prediction M-AGC system (Smith-AGC) show that our method can effectively reduce overshoot and oscillations in the dynamic response of the exit plate thickness when the operating conditions change and the system time delay parameters are mismatched, so that the system has better stability and dynamic performance. [ABSTRACT FROM AUTHOR]

Pertaining to the connectivity issues in wind power plants with grids, this study introduces an efficient mechanism based on a state feedback control structure to establish a fast and stable grid connection for a wind-driven doubly-fed induction generator (DFIG). Owing to a direct link through stator windings, a DFIG is significantly vulnerable to grid disturbances and experiences sizable inrush currents when connected to the power grid. The proposed control structure is designed based on a linear matrix inequality stabilization criterion, which is framed using a suitable Lyapunov candidate function. The control objective is to ensure that the stator voltage can exponentially converge to the grid voltage, accounting for balanced and unbalanced grid conditions. This is achieved by generating appropriate rotor voltage references for rotor-side converter control. This study also explores the capability of the proposed control structure to enhance the system’s robustness to external disturbances and uncertain parametric variations. Simulations confirmed the effectiveness and suitability of the developed structure in mitigating the adverse effects of the rapid onset of the grid voltage at the stator terminals of the DFIG under various grid conditions; the proposed structure could thus establish a reliable connection with negligible effects on the DFIG and the grid.

This paper presents the experimental magnetic levitation control development of Sanki Engineering airport luggage conveyor carts which have four magnetic levitation units working synchronously. With the PID controller, the state feedback controller and the zero-power controller refined by PID controller were implemented in the one magnetic levitation unit system and four-unit magnetic levitation system, and the displacement and the current were verified in a real-time system. The magnetic levitation unit had a fast response, and the control algorithms were easily implemented. The change of current and displacement were compared. In the one-unit system, the PID and state feedback controller react to the disturbance at the same speed and have similar power consumptions. For a disturbance on the zero-power controller, the system generates a transient current to deal with the load disturbance and finally settles to 0 A. The PID control for four magnetic levitation units of the conveyor cart has a better stable performance during synchronous operation. Under the control of state feedback controller, they can keep the cart statically stable with some oscillation. These characteristics are experimentally confirmed.

This paper deals with the issue of stochastic admissibility and robust extended dissipative control for uncertain delayed hybrid descriptor systems (DHDSs) under a unified framework. Belonging to a convex bounded domain, the parameter uncertainties are time-invariant and appear in the state matrix, input matrix and disturbance matrix. Firstly, a stochastic Lyapunov–Krasovskii functional is proposed to reflect the information of time-varying delays and Markovian jump modes, and singular value decomposition technique is utilized to derive novel criteria that ensure the stochastic admissibility and robust extended dissipativity of DHDSs. Then, under a unified framework, the desired robustly stabilizing state feedback controller is realized in terms of linear matrix inequalities. Finally, two examples including a numerical example and an oil catalytic cracking process are applied to corroborate the effectiveness of the derived synthesis scheme. [ABSTRACT FROM AUTHOR]