Transient Performance Of System Research Articles

Observer-based formation tracking control for feedforward nonlinear multi-agent systems with dead-zone input

In this paper, the formation tracking control problem is addressed for feedforward nonlinear multi-agent systems with dead-zone input. For each follower, a dynamic observer is constructed by the output information of itself and its neighbours. Based on the observer, a distributed control protocol is designed with a bounded time-varying gain to achieve the formation tracking between each follower and the leader. It should be pointed out that the control protocol has fewer communication variables and simpler structure, while improving the convergence speed and transient performance of system. In addition, the results are extended to the feedback nonlinear multi-agent systems. Finally, a practical example is performed for nonlinear liquid level resonant circuit system to demonstrate the feasibility of the control protocol proposed.

A Blow-Up Function Approach to Global Event-Triggered Prescribed Tracking Output Feedback Control of Nonlinear Systems

In this paper, global event-triggered adaptive prescribed tracking output feedback control is investigated for a class of nonlinear uncertain systems with unknown control direction. Different from the existing works, the design of the tracking error-dependent normalized function and prescribed boundary is based on our uniformly defined blow-up function rather than a specific function, and the asymmetric constraint requirements on tracking error can be achieved by appropriately selecting the blow-up function. By utilizing the Kalman filter ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -filter) and dynamic gain technique, a new reduce-order observer is proposed, which can make the estimated error exponentially converge to zero. In addition, by introducing a dynamic signal into the trigger condition, a novel event-triggered mechanism is proposed, which can extend the trigger time interval and completely counteract the event-triggered errors in terms of asymptotic stability by sacrificing part of the system transient performance. Furthermore, an adaptive controller is designed based on the backstepping method, which ensures the boundedness of the state of the closed-loop system, while regulating the tracking error meets the global prescribed performance requirements and approaches to zero asymptotically. Two examples are given to illustrate the effectiveness of the proposed control scheme.

Asymptotic output tracking control with prescribed transient performance of nonlinear systems in the presence of unknown dynamics

AbstractIn this article, we address the problem of asymptotic output tracking control with prescribed transient performance for a class of nonlinear systems in the presence of unknown dynamics. By fusing the funnel control approach and the tool of barrier Lyapunov function, a smooth adaptive tracking control strategy is developed in a recursive manner. In the proposed design, a new barrier Lyapunov function is adopted to eliminate the effects of unknown nonlinear dynamics, ensuring the prescribed transient behavior of the output tracking. The distinctive characteristic of the proposed method is that the designed control algorithm can guarantee not only prescribed output tracking performance but also global asymptotic stability without incorporating any prior knowledge of nonlinear dynamics or even corresponding bounding functions. Three illustrative examples are provided to testify the effectiveness of the proposed method.

Compensating for part arrival uncertainties in two-processing-machine, one-buffer flow lines: Inventory flexibility design based on the system transient performances

• A structured Markov process model for the proposed flow lines;. • Transition equation derivation for the flow lines;. • The algorithms for factoring a class of states to derive closed-form expressions;. • System transient performance analysis of the flow lines system;. • Discrete event dynamic system simulation and verification. In one-of-a-kind production (OKP), a flow line with two distinct deterministic processing time machines and one “flexible” storage buffer is studied from the perspective of manufacturing system design and transient behaviour analysis. This manufacturing process is disrupted by part arrival uncertainties and is considered a discrete dynamic stochastic system. The dynamic behaviour of the flow line is structured as a transfer line with multi-state machines and finite-storage buffers by a discrete-time, discrete-state Markov chain for the transient performance analysis, optimal design and efficient production operation. To assess the dynamic disruptions and further limit the cascading effects on the flow line, in the presented analytical model, the studies quantify the evolution of a basic serial production process over time; and meanwhile, we evaluate and optimize the manufacturing system transient performance to determine the optimal design of inventory flexibility as a function of the time and states. By factoring out a class of appropriate transient states associated with an initial state at a certain time slot and deriving closed-form expressions using the transition equations, we sought to determine the transient probabilities of the manufacturing system states to establish relationships between the variable system parameters and the performance measures. By embedding these practical results with quantitative precision in an optimal design process of inventory flexibility, we consider setting the storage buffer level between two processing machines for refined production optimization and control when the part arrival uncertainties and lack of synchronization constantly occur in this serial manufacturing system.

Adaptive Event-Triggered Control of Uncertain Nonlinear Systems Using Intermittent Output Only

Although rich collection of research results on event-triggered control exist, no effort has ever been made in integrating state/output triggering and controller triggering simultaneously with backstepping control design. The primary objective of this article is, by using intermittent output signal only, to build a backstepping adaptive event-triggered feedback control for a class of uncertain nonlinear systems. To do so, we need to tackle three technical obstacles. First, the nature of the event triggering makes the transmitted output signal discontinuous, rendering the regular recursive backstepping design method inapplicable as the repetitive differentiation of virtual control signals is literally undefined. Second, the effects arisen from the event-triggering action must be properly accommodated, but the current compensating method only works for systems in normal form, thus a new method needs to be developed in order to handle nonnormal form systems. Third, as only intermittent output signal is available, and at the same time, the impacts of certain terms containing unknown parameters (arising from event triggering) need to be compensated, it is rather challenging to design a suitable state observer. To circumvent these difficulties, we employ the dynamic filtering technique to avoid the differentiation of virtual control signals in the backstepping design, construct a new compensation scheme to deal with the effects of output triggering, and build a new form of state observer to facilitate the development of output feedback control. It is shown that, with the derived adaptive backstepping output-triggered control, all the closed-loop signals are ensured bounded and the transient system performance in the mean square error sense can be adjusted by appropriately adjusting design parameters. The benefits and effectiveness of the proposed scheme are also validated by numerical simulation.

Impedance Control of Space Robot On-Orbit Insertion and Extraction Based on Prescribed Performance Method

Aiming at the force position control problem of the on-orbit insertion and extraction operation of the free-floating space robot, the system dynamics model is established. According to the interaction between the end of manipulator and the environment, the second-order impedance model is established. In order to improves the calculation efficiency, the above models are reconstructed to avoid the use of acceleration signal by introducing filtering operation. This is also conducive to the application of robot actual control. Then, an estimator requiring only the system inertia matrix is designed to compensate the modeling uncertainty, external bounded disturbance and impact effect in the process of inserting and extracting. Its structure is simple and reliable. Only one control parameter needs to be adjusted, which greatly reduces the amount of calculation. Considering that the on-orbit operation of insertion and extraction is a kind of precision operation, its control system needs to have a high-quality control performance. By introducing the prescribed performance method, the tracking error is constrained within the given range and to ensure the transient performance and steady-state performance of the control system is ensured. Finally, three simulation conditions are designed, and the results are presented to verify that the proposed algorithm has a faster convergence speed compared with traditional sliding mode controller. It can achieve vertically inserting and accurate force tracking of the manipulator end.

Predictor-Based Neural Dynamic Surface Control for Bipartite Tracking of a Class of Nonlinear Multiagent Systems.

This article is concerned with bipartite tracking for a class of nonlinear multiagent systems under a signed directed graph, where the followers are with unknown virtual control gains. In the predictor-based neural dynamic surface control (NDSC) framework, a bipartite tracking control strategy is proposed by the introduction of predictors and the minimal number of learning parameters (MNLPs) technology along with the graph theory. Different from the traditional NDSC, the predictor-based NDSC utilizes prediction errors to update the neural network for improving system transient performance. The MNLPs technology is employed to avoid the problem of "explosion of learning parameters". It is proved that all closed-loop signals steered by the proposed control strategy are bounded, and the system achieves bipartite consensus. Simulation results verify the efficiency and effectiveness of the strategy.

Optimal controller design for non-affine nonlinear power systems with static var compensators for hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator (SVC) or State Var System (SVS) for hybrid Unmanned Aerial Vehicles (UAVs). The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function. Combining the inverse system method and the Linear Quadratic Regulation (LQR), an optimized SVC controller is designed. The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

Event-triggered adaptive fuzzy control for automated vehicle steer-by-wire system with prescribed performance: Theoretical design and experiment implementation

Steer-by-wire (SbW) systems substitute the typical mechanical linkage between the steering wheel and the front wheel with electromechanical actuators, resulting in that the steering performance of SbW systems depends on the control of electromechanical actuators. To guarantee the transient and steady-state performance of SbW systems, this paper proposes an event-triggered adaptive fuzzy control for the SbW system subject to the unavailable steering angular velocity, the time-varying disturbance, and the limited communication resources. First, to solve the problem of uncertainty modeling and external interference, an interval type-2 fuzzy logic system (IT2 FLS) and a disturbance observer are used to approximate the unknown SbW system dynamics and disturbance, respectively. Second, considering the angular velocity of the front wheels is difficult to measure, an adaptive observer is developed to estimate the steering angular velocity. The observation error is proved by the Lyapunov theory to converge in finite time. Third, to guarantee the transient and steady-state performance of the SbW system, this paper develops an output feedback controller for the automated vehicles based on event-triggered control (ETC) and prescribed performance control (PPC). Theoretical analysis proves that the tracking error can converge to a preset range within the set time, and the communication data between the controller and the actuator is reduced. Finally, simulation and experiment verify the effectiveness and superiority of the proposed method. From the analysis of the estimation performance, the designed observer has strong adaptability, which can ensure better observation accuracy even if the system has uncertainty. From the analysis of control performance, the proposed controller can guarantee the output trajectory tracking performance attributes (maximum overshoot, convergence time, maximum steady-state error). More specifically, in the experiment, the tracking error can converge to within 0.075 rad in 5 s. Additionally, the RMSE of the experimental results of the designed method is 44.7% higher than that of the output-feedback adaptive neural controller. From the perspective of communication data, the control signal transmitted to the motor driver is effectively saved by 19.3 %.

Energy and exergy analysis of the transient performance of a qanat-source heat pump using TRNSYS-MATLAB co-simulator

In this study, the transient performance of a qanat source heat pump is investigated using a TRNSYS-MATLAB co-simulator. The water/ethylene glycol-to-air compression heat pump and the helical coil heat exchanger, which is used to inject heat to or to extract heat from the qanat water, are mathematically modeled in matrix laboratory (MATLAB), and then, coupled to transient systems simulation (TRNSYS) model to evaluate the system transient performance and calculate the heating and cooling loads of the case study building. Comparison of the performance of the qanat source heat pump with an air source heat pump showed that the coefficient of performance of the qanat source heat pump is at least 5% and at most 34% higher than that of the air source heat pump. By increasing the flow rate of the working fluid in the helical coil heat exchanger from 2 L/min to 8 L/min, the coefficient of performance of the qanat source heat pump increases at least 12% and at most 34.1%. The maximum increase in energy efficiency ratio and free energy ratio of the system by the similar increase in the flow rate is 46.4% and 24.8%, respectively. The exergy analysis of the qanat source heat pump reveals that the minimum and maximum exergy efficiency of the system is 32% and 85.5%, respectively. The findings also indicate that the most exergy destruction occurs in the condenser in heating mode and in the evaporator in cooling mode.

The Influence of MPPT Algorithms in the Lifespan of the Capacitor Across the PV Array

PV systems efficiency highly depends on the MPPT strategy to be implemented in the PV converter. Many MPPT methods on the literature are focused on improving the steady state and transient system performance extracting the maximum energy from the sun. In this paper, the impact of the MPPT methods in the PV converter is analyzed focusing the study on the capacitor across the PV array lifespan. The obtained results demonstrate that the low frequency PV voltage oscillations that are present in many MPPT methods have a large negative impact on this capacitor lifespan. Experimental and simulation results are presented in order to show that advanced MPPT methods, which avoid these low frequency oscillations, achieve higher capacitor lifespan values compared with the values obtained by applying well-known MPPT methods such as the perturb and observe or incremental conductance strategies.

High frequency modeling and experimental verification of distribution transformers using transfer function approach

High frequency transformer model represents a mandatory requirement to study transient performance of distribution systems under lightning strokes. In Finland, the distribution systems are frequently subjected to these strokes. In this paper, an accurate and simple model is introduced for the distribution transformers concerning two-port network implemented using transfer functions. Compromising between simplicity and accuracy facilitates the high frequency modeling of transformer for complicated networks. The study is done using two distribution transformers used in Finland, DYN5 (100 kVA) and DYN11 (500 kVA). The proposed model parameters of the two-port network are experimentally extracted for each transformer under the impulse tests. System identification of the impedance parameter is done using the denoised experimental signals for primary and secondary voltages and currents. The model is verified using experimental results under unloaded and loaded conditions. The evaluation is accomplished concerning time domain and frequency responses. Also, the proposed model is compared with published accurate model for loaded, unloaded, and medium voltage spark-gap (MVSG) operation of the first transformer, 100 kVA. The proposed model achieves simple implementation and accurate results for unloaded and loaded transformers as well as under MVSG operation. The simulated results are carried out using the MATLAB and ATPDraw programs.

Oscillation analysis of doubly-fed unit considering wind speed variation

Tower shadow effect and wind shear may cause power oscillation of the unit. In order to study the influence of tower shadow effect and wind shear on the output power of wind turbine, a doubly-fed turbine was taken as an example. Firstly, the influence of tower shadow effect and wind shear was considered to study the periodic power fluctuation characteristics of wind turbines. Then, according to the dynamic model of mechanical transmission mechanism, the influences of the inertia constants of generator, fan and the stiffness coefficient of the shaft system on the transient performance of the wind power generation system were considered respectively. Finally, a single machine infinite bus system model including wind speed model is built on PSCAD/EMTDC platform for simulation. The results show that the tower shadow effect and wind shear component can cause the power fluctuation of the turbine. When the power fluctuation frequency of the turbine is equal to the natural oscillation frequency of the wind turbine shafting, the resonance of the turbine occurs, and the amplitude of oscillation is the largest. Changing the transmission parameters will affect the power fluctuation amplitude and speed response speed of the unit.

A novel reset control approach to leader-following consensus of second-order nonlinear multi-agent systems

This paper investigates the leader-following consensus problem of second-order nonlinear multi-agent systems with directed graph. A novel reset control approach is proposed for the aim of improving transient consensus performance, e.g., settling time. By introducing consensus error into reset conditions, the output of reset integrator will keep the same sign with the consensus error, thus, the desired states can be compensated preferentially and the system transient performance is improved accordingly. To appropriately describe the closed-loop system with reset-induced jump dynamics, a hybrid system model consisting of both flow dynamics and jump dynamics is constructed. Based on this model, and combined with backstepping method, Lyapunov-based consensus analysis is presented under hybrid system framework. Finally, a numerical example is provided to show the effectiveness of the obtained results.

Enhancement of power system transient stability and voltage regulation performance with decentralized synergetic TCSC controller

In this paper, a new nonlinear control approach for thyristor-controlled series capacitors (TCSCs) has been proposed to schedule TCSC line active power transfer, improving transient stability, and obtain acceptable voltage regulation performance of the power system. This control method for the TSCS has been presented based on synergetic control theory. According to the control targets, a linear combination of the TCSC voltage variation, generator rotor speed, TCSC active power, and TCSC reactance is chosen to design a decentralized synergetic TCSC controller (DSTC). A dynamic parameter adaption approach is also presented for updating the DSTC parameters to satisfy control objectives under different power system operating conditions. In the studied system, each generator is equipped with a decentralized improved synergetic excitation controller (ISEC). Dynamic characteristic of the presented DSTC is studied in a single machine infinitive bus and a WSCC-type 3-machine 9-bus power system. A restructured improved synergetic excitation controller (RISEC) has also been formulated to investigate the impact of ISEC on the multi-machine system. Simulation results show that the proposed controller can provide better transient stability, active power flow of the TCSC line, and voltage regulation performance than the ISEC with or without conventional TCSC controller and conventional power system stabilizer without any TCSC controller.

Nonlinear backstepping controller design for bridge‐type fault current limiter to enhance the transient performance of hybrid power systems

Nonlinear backstepping controller design for <scp>bridge‐type</scp> fault current limiter to enhance the transient performance of hybrid power systems

Transient heat pipe failure accident analysis of a megawatt heat pipe cooled reactor

Heat pipe cooled reactors, which use heat pipes rather than fluid flow for passive cooling, are an excellent candidate for micro nuclear power sources. Heat pipes provide excellent built-in redundancy and safety margin. However, a heat pipe failure is quite likely over the reactor lifetime, which is one of the essential design basis accidents in the reactor design. This work analyzes heat pipe failure accidents to investigate the system transient performance and the response of a heat pipe cooled reactor. Single heat pipe failure and cascading heat pipe failure are simulated and analyzed by establishing a transient analysis code, including a point reactor kinetics model, a core thermal-mechanical model, and a heat pipe model. The simulation shows that in the single heat pipe failure accident, the peak monolith temperature at the failed channel increases and is only 8 K lower than the fuel center temperature. In the cascading heat pipe failure accident, the temperatures in each channel suddenly increase over a short period and rise to the maximum at 22,900 s as the heat losses increase and the core power decreases. The sensitivity of the external convection for residual heat removal is also analyzed. For small external convection coefficients less than 100 W/m2K, increasing the external convection coefficient significantly reduces the maximum temperatures. By contrast, for external convection coefficient greater than 500 W/m2K, increasing external convection coefficient still reduces the core peak temperature, but the effect is weak.

Reset Control for Consensus of Multiagent Systems With Asynchronous Sampling

This article investigates the consensus problem of multiagent systems (MASs) with the reset control approach. Reset control has been shown to possess great potential to improve transient system performance, but reset-induced state jump dynamics bring difficulties for consensus analysis, especially under the network environment. In this article, a novel reset element is developed, and time regularization is utilized to exclude Zeno behavior. The case with continuous communication is first considered, a distributed proportional integral + reset consensus protocol is proposed, which consists of the proportional-integral controller and the reset mechanism. The results are further generalized to the case with asynchronous sampling, which relaxes the requirement for continuous communication and clock synchronization. A hybrid model of the MAS is constructed to describe the system dynamics, and a hybrid systems approach is proposed to handle the reset- and sampling-induced jump dynamics in a unified framework. Moreover, a novel Lyapunov function is proposed and LMI-based stability conditions are given. Finally, an example is provided to show the effectiveness of the proposed methods.

Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

This paper proposes a novel model predictive current control scheme for two-stage matrix converter. The switching frequency is kept constant by fixing the switching instant. The control strategy achieves to control source reactive power in the input side and output currents in the output side. In addition, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, a zero-current switching sequence is proposed and implemented to insure zero-current switching operations and reduce the switching losses. Furthermore, in order to suppress the input filter resonance, which is easier to be inspired by the model predictive control, compared with traditional control strategies, an innovative active damping technique is proposed and implemented. Finally, both simulation and experiment are implemented to verify the performance of the proposed strategy. The results demonstrate that the control system features both good steady and transient performance.

A Novel Predictive Control Method with Optimal Switching Sequence and Filter Resonance Suppression for Two-Stage Matrix Converter

This paper proposes a vector modulation-based model predictive current control strategy for a two-stage matrix converter. The switching frequency is kept constant by fixing the switching instantly. The control scheme controls the source reactive power on the input side and output currents on the output side. Besides, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, to ensure zero-current switching operations and reduce the switching losses, an optimal switching sequence is proposed and implemented. Furthermore, considering that the input filter resonance is easier to be inspired by the model predictive control, compared with conventional linear control strategies, an innovative active damping technique is proposed to suppress the input filter resonance. To assess the performance of the proposed method, simulation and experimental results are demonstrated, showing that the control system features both good steady-state and transient performance.