Controller Design Parameters Research Articles

Dynamic performances of ultra-high-performance fiber-reinforced concrete–strengthened concrete columns subjected to blast impacts

Normal functionality of common concrete structures such as bridges and buildings relies heavily on the structural resistance under accidental or anthropogenic blast events. As one of the widely used structural types, reinforced concrete columns need to be highly considered when blast events occur to avoid severe socio-economic losses. To improve the blast–impact resistance of conventional reinforced concrete columns, this article makes the following contributions: (1) proposes to adopt the advanced ultra-high-performance fiber-reinforced concrete to strengthen the columns as a protective layer; (2) validates the superiority of ultra-high-performance fiber-reinforced concrete–strengthened columns through comparative study and specifies the controlling design parameters through sensitivity analysis; (3) implements and compares various ultra-high-performance fiber-reinforced concrete reinforcement methods; and (4) develops a numerical formula to predict the residual capacity of ultra-high-performance fiber-reinforced concrete–strengthened columns under blast impacts as a suitable alternate of the complicated and time-consuming finite element simulations.

Generalization of the FOPDT Model for Identification and Control Purposes

This paper proposes a theoretical framework for generalization of the well established first order plus dead time (FOPDT) model for linear systems. The FOPDT model has been broadly used in practice to capture essential dynamic response of real life processes for the purpose of control design systems. Recently, the model has been revisited towards a generalization of its orders, i.e., non-integer Laplace order and fractional order delay. This paper investigates the stability margins as they vary with each generalization step. The relevance of this generalization has great implications in both the identification of dynamic processes as well as in the controller parameter design of dynamic feedback closed loops. The discussion section addresses in detail each of this aspect and points the reader towards the potential unlocked by this contribution.

Robust Multi-Objective Singular Optimal Control Ofpenicillin Fermentation Process

The determination of optimal feeding profile of fed-batch fermentation requires the solution of a singular optimal control problem. The complexity in obtaining the solution to this singular problem is due to the nonlinear dynamics of the system model, the presence of control variables in linear form and the existence of constraints in both the state and control variables. Traditionally, during the optimization process, uncertainties associated with design variables, control parameters and mathematical model are not considered. In this contribution, a systematic methodology to evaluate uncertainties during the resolution of a singular optimal control problem is proposed. This approach consists of the Multi-objective Optimization Differential Evolution algorithm associated with Effective Mean Concept. The proposed methodology is applied to determine the feed substrate concentration in fed-batch penicillin fermentation process. The robust multi- objective singular optimal control problem consists of maximizing the productivity and minimizing the operation total time.

Robust evaluation of stability regions of oil-well drilling systems with uncertain bit-rock nonlinear interaction

Torsional vibrations due to stick-slip phenomena may yield large variations in the drilling angular velocity which in turn may cause failures in the drilling process such as damage in drill pipes, due to large torsional deformation, and in drill bits, due to large angular velocities. It has been shown that standard linear proportional-integral (PI) control laws, in which the control torque is proportional to the differences between actual and reference drive table angular velocity and displacement, may lead to an oscillating angular velocity at the drill-bit due to stick-slip phenomenon. Aiming at reducing this effect through properly designed control gains, stability regions were defined for these parameters, and for a given drilling condition, using as a criteria the average deviation from expected/target angular velocity. This is done using a finite element model for the drilling system together with a dry friction model for a simplified representation of the interaction between drill-bit and rock formation. In order to provide robustness for the analysis, given the complexity of actual bit-rock interaction, it is proposed to consider uncertain parameters for the dry friction model. This is done using a stochastic model for the bit-rock interaction torque followed by a Monte Carlo simulation, which then leads to stochastic results for the angular velocity response, when subject to a linear PI control, and, thus, for the angular velocity deviation stability regions. Confidence intervals for the control gains, performance and stability regions are presented. Results suggest the use of a more robust criteria for the design of control parameters leading to a substantial increase in the performance robustness while not affecting much the nominal performance.

A Robust Adaptive CMAC Neural Network-Based Multisliding Mode Control Method for Unmatched Uncertain Nonlinear Systems

This paper proposes a new robust adaptive cerebellar model articulation controller (CMAC) neural network-based multisliding mode control strategy for a class of unmatched uncertain nonlinear systems. Specifically, by employing a stepwise recursion-based multisliding mode method, such a proposed strategy is able to obtain the virtual variables and the actual control inputs of each order first, and then it reduces the conservativeness for controller parameter design by adopting the CMAC neural network to learn both system uncertainties and virtual control variable derivatives of each order online. Meanwhile, with the hyperbolic tangent function being chosen to replace the sign function in the variable structured control components, the proposed strategy is able to avoid the chattering effects caused by the discontinuous inputs. The stability analysis shows that the proposed control strategy ensures that both the system tracking errors and the sliding modes of each order could converge exponentially to any saturated layer being set. The control strategy was also applied onto a passive electrohydraulic servo loading system for verifications, and simulation results show that such a proposed control strategy is robust against all system nonlinearities and external disturbances with much higher control accuracy being achieved.

Fixed-time control design for nonlinear uncertain systems via adaptive method

This article addresses a fixed-time tracking problem of uncertain nonlinear system. Firstly, a sufficient condition for practical fixed-time stability is given. Secondly, on the basis of the sufficient condition, a novel adaptive control strategy is proposed. The designed parameter adaptive law is expressed as a nonlinear differential equation, which is different from the existing adaptive design method. Under the proposed adaptive control scheme, the system performance can be guaranteed in a fixed time, and the upper bound of the settling time is merely affected by the control design parameters, which is independent on the initial states of system. Then, based on the new established inequalities, the fixed-time stability of the closed-loop system is proved. Finally, an example is provided to illustrate the effectiveness of the main result.

Control Conflict Suppressing and Stability Improving for an MMC Distributed Control System

Compared with traditional centralized control strategies, the distributed control systems significantly improve the flexibility and expandability of an modular multilevel converter (MMC). However, the stability issue in the MMC distributed control system with the presence of control loop coupling interactions is rarely discussed in existing research works. This article is to improve the stability of an MMC distributed control system by inhibiting the control conflict due to the coupling interactions among control loops with incomplete control information. By modeling the MMC distributed control system, the control loop coupling interactions are analyzed and the essential cause of control conflict is revealed. Accordingly, a control parameter design principle is proposed to effectively suppress the disturbances from the targeted control conflict and improve the MMC system stability. The rationality of the theoretical analysis and the effectiveness of the control parameter design principle are confirmed by simulation and experimental results.

Development of a Novel Optimal Backstepping Control Algorithm of Magnetic Impeller-Bearing System for Artificial Heart Ventricle Pump

In this work, a new backstepping control algorithm is developed for accurate suspension of the rotating impeller in the artificial heart based on supported magnetic suspension system. The magnet suspension system of the artificial heart ventricle consists mainly of the proposed controller and magnetic coils. The controller is used to actuate the magnetic coils with required currents to establish the magnetic field necessary for suspending the impeller at accurate position. Two pairs of magnetic coils at each end of the rotor are responsible for suspension in both vertical and horizontal planes such as three-dimension suspension control is achieved. The backstepping control algorithm is developed using the stability analysis based on the Lyapunov theory. The design parameters of backstepping controller have direct impact on the performance of controlled system. The present work suggested Particle Swarm Optimization technique for tuning these design parameters toward better performance of proposed controller. The effectiveness of the optimized backstepping controller is verified via computer simulation within MATLAB/SIMULINK environment.

Speed Control of DC Motor Using PID and Arduino

This paper is aim to research the Proportional Integral Differential (PID) controller design and selection of various Proportional, Integral and Differential control parameters. MATLAB is allows matrix manipulations, plotting of functions and data, implementation of algorithms. An additional package, Simulink, adds graphical multi-domain simulation and model-based design for dynamic and embedded systems. MATLAB is used to implement the Proportional Integral Differential (PID) controller, it is used to control the speed of DC motor and bring it at the desired speed. PID parameters Kp , Ki and Kd are finely tuned to optimal values. And then a ARDUINO UNO microcontroller is programmed by adding the finely tuned PID algorithm to control the speed of DC motor.

Droop‐free hierarchical control strategy for inverter‐based AC microgrids

Hierarchical schemes are widely used for the designing of the inverter-based AC microgrids control strategies. To ensure reliable operation, hierarchical control must consider together all the functionalities that allow the regulation of key variables and guarantee a safe transition between operation modes. Conventionally, in the literature are proposed three-layer schemes which present relevant drawbacks: they include limited functionalities and they use droop method for the primary layer which, despite its decentralised nature, suffers from issues that have motivated the development of alternative strategies. Considering this, the contribution of this study is two-fold. First, a droop-free hierarchical control strategy that satisfies a proper operation of AC microgrids is proposed. Control objectives such as power-sharing, frequency regulation, optimal power dispatch and voltage regulation are considered. Second, a closed-loop small-signal model, which facilitates the control parameters design and fills a gap in the literature is presented. Differences between the proposal and previous controls are discussed. Selected tests are carried out in a laboratory microgrid under different conditions, including normal operation and the response to failures in the central controller and to communication impairments. The experimental results show a good performance of the proposal even in adverse conditions.

Imbalance recovery performance analysis and improvement for MMC‐HVDC systems considering DC current dynamics

This study presents the imbalance recovery performance analysis of modular multilevel converter high voltage direct current (MMC-HVDC) systems considering dc current dynamics, and proposes an enhanced control to improve the system's internal stability response. The numerical expressions of the imbalance recovery speed and overshoot amplitude response of dc current components in upper and lower arms of the MMC phase unit are firstly derived analytically, which reveal that the system can be prone to poor imbalance recovery performance after sudden disturbance impacts with no auxiliary control. According to the analysis results, an improved control based on the adaptive virtual resistance method is proposed for the MMC-HVDC systems to reduce the recovery time regarding different system operating states. The key control parameter design of the adaptive virtual resistance is also simplified since a wider adjustment range of the parameters is allowed in the proposed method. In addition, the dc current components rebalance controller consisting of a low-pass compensator is proposed to further reduce the overshoot amplitude of system internal response. With the implementation of the proposed control schemes, improved stability recovery performance of MMC-HVDC systems can be achieved. Simulation results verify the effectiveness of the proposed control.

Parameter closed-loop optimization for pure electric vehicles: unified design of power system and control parameters

Parameter closed-loop optimization for pure electric vehicles: unified design of power system and control parameters

Nonlinear Model and Dynamic Behavior of Photovoltaic Grid-Connected Inverter

A photovoltaic grid-connected inverter is a strongly nonlinear system. A model predictive control method can improve control accuracy and dynamic performance. Methods to accurately model and optimize control parameters are key to ensuring the stable operation of a photovoltaic grid-connected inverter. Based on the nonlinear characteristics of photovoltaic arrays and switching devices, we established a nonlinear model of photovoltaic grid-connected inverters using the state space method and solved its model predictive controller. Then, using the phase diagram, folded diagram, and bifurcation diagram methods, we studied the nonlinear dynamic behavior under the influence of control parameters on both fast and slow scales. Finally, we investigated the methods of parameter selection based on the characteristics of nonlinear dynamic behavior. Our research shows that the predictive controller parameters are closely related to the bifurcation and chaos behaviors of the grid-connected photovoltaic inverter. The three-dimensional bifurcation diagram can be used to observe the periodic motion region of the control parameters. After selecting the optimization target, the bifurcation diagram can be used to guide the selection of control parameters for inverter design. The research results can be used to guide the modeling, stability analysis, and optimization design of photovoltaic grid-connected inverters.

Improved Model-Based Phase-Shift Control for Fast Dynamic Response of Dual-Active-Bridge DC/DC Converters

Fast dynamic response of the output voltage is an essential requirement for dual-active-bridge (DAB) dc/dc converters under the operation of the voltage source. This article proposes an improved model-based phase-shift control (MPSC) strategy that combines model-based control with the design of feedback regulators and load current feedforward (LCFF) regulators. The improved MPSC strategy can ensure that the DAB has high-bandwidth control performance over the entire transmission power range without changing the controller parameters online. The design of controller parameters is simple and has the same model parameter as sensitive as MPSC. Its utility and effectiveness are verified by simulations and experiments.

Optimization method and stability analysis of MMC grid-connect control system based on virtual synchronous generator technology

Aiming at the issue of how to design controller parameters and analyze system stability when modular multilevel converter (MMC) adopts virtual synchronous generator (VSG) control technology. Firstly, this paper derives the parameter correspondence between the grid-connected MMC system and the synchronous generator (SG) system, and obtains the relationship between the virtual inertia parameter and damping parameter with specific structural parameters of MMC, then the optimization method of key parameters in the main controller of MMC grid-connected system is determined. That is to add the optimized inertia parameters and damping parameters to the active-frequency controller, the flux linkage feedback loop and the reactive differential compensation link to the reactive-voltage controller, the stability of MMC grid-connected system was analyzed by adjusting key parameters, and the optimal inertia parameters and damping parameters of the MMC grid-connected system during stable operation was analyzed. Finally, using MATLAB/Simulink to build a simulation model of MMC grid-connected system based on VSG control, the feasibility and correctness of the proposed optimization method for key parameters were verified, and the stability of the system was analyzed. The results showed that the key parameters of the main controller combined with the MMC unique structure were more suitable for the MMC grid-connected control system, which improved the stability of the system.

Robust iterative learning control for iteration- and time-varying disturbance rejection

ABSTRACTIterative learning control (ILC) is an effective strategy to deal with repetitive tasks and has been widely applied in industrial systems. Many methods have been proposed to improving the performance of ILC system against iteration-invariant disturbances. While iteration-varying disturbances, which has more practical meaning, do not get enough researches. An observer is designed to estimate the system states and the total disturbances which include the system uncertainties and external disturbances. Furthermore, an iterative algorithm is given to estimate separately the disturbances from input and non-input channels. Then robust D-type ILC with disturbances compensation is proposed to improve the performance of systems with iteration-varying and time-varying disturbances. The convergence of proposed robust ILC system is proved, and the control parameters design is guided. Finally, simulation and comparison with other method are carried out to demonstrate the efficiency of the proposed method.

Study on the Handling Qualities Enhancement of Fixed-wing Aircraft Using Adaptive Neural Network

This paper intends to propose the integrated design framework of a model-following controller (MFC) combined with both an adaptive neural network (ANN) and a linear observer to enhance the handling qualities (HQ) of a fixed-wing aircraft. To achieve this objective, the HQ requirements (HQRs) applicable to a light sports aircraft and the controller structure have been defined. And, the controller design parameters are optimized to meet HQRs using the CONDUIT®. Thereby, the integrated design environment can determine the control gains and ANN’s tuning parameters in an optimum manner and the level of HQ achievable with the designed parameters can be automatically evaluated. The paper tries to clarify the effect of the ANN with the linear observer on the HQ enhancement. To achieve this, the control laws in the attitude command response types have been designed and their tracking performances are investigated with and without ANN elements to identify the improved HQ with the ANN. In addition, a series of comparative simulation studies on the effects of external disturbances on the attitude tracking performance are carried out to show the enhanced robustness with the proposed controller structure. The results show that the ANN control can dramatically improve the level of HQ and provide the favorable robustness to external disturbances. Therefore, the results of the present study can provide the efficient ways of the HQ enhancement by adopting the ANN in the conventional MFC structure and by designing the controller parameters with the integrated design processes of CONDUIT®.

Robust adaptive attitude control for non-rigid spacecraft with quantized control input

In this paper, an adaptive backstepping control scheme is proposed for attitude tracking of non-rigid spacecraft in the presence of input quantization, inertial uncertainty and external disturbance. The control signal for each actuator is quantized by sector-bounded quantizers, including the logarithmic quantizer and the hysteresis quantizer. By describing the impact of quantization in a new affine model and introducing a smooth function and a novel form of the control signal, the influence caused by input quantization and external disturbance is properly compensated for. Moreover, with the aid of the adaptive control technique, our approach can achieve attitude tracking without the explicit knowledge of inertial parameters. Unlike existing attitude control schemes for spacecraft, in this paper, the quantization parameters can be unknown, and the bounds of inertial parameters and disturbance are also not needed. In addition to proving the stability of the closed-loop system, the relationship between the control performance and design parameters is analyzed. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Small-Signal Modeling and Parameter Optimization Design for Photovoltaic Virtual Synchronous Generator

With the continuous proliferation of renewable energy generation, distributed photovoltaic inverters operating at a maximum power point reduce the inertia of power systems, degrading system frequency stability and potentially causing severe oscillations in systems after being disturbed. The virtual synchronous generator (VSG) control method, which causes photovoltaic inverters to possess inertia and damping, now plays an important role in the field of distributed generation. However, while introducing the advantages of synchronous machines, problems with oscillations are also introduced and the stochastic fluctuation characteristic of photovoltaics results in the stochastic drifting of the operating point. This paper presents an adaptive controller parameter design method for a photovoltaic-VSG (PV-VSG) integrated power system. Firstly, a small-signal model of the PV-VSG is built and a state space model is deduced. Then, the small-signal stability and low frequency oscillation characteristics of the photovoltaic power generation system are analyzed. Finally, considering the limitations of system oscillations and the stochastic drifting of the operating point, a global optimization design method for controller parameters used to improve system stability is proposed. The time domain simulation shows that an optimized PV-VSG could provide sufficient damping in the case of photovoltaic power output changes across a wider range.

A Synchronization Method for the Modular Series-Connected Inverters

The series-connected system is widely used in the medium or high voltage applications. For the series-connected inverter system, the phase angle synchronization should be guaranteed to ensure the total output voltage. Usually, a centralized controller is used to send the same voltage command to each module downstream. In order to improve the flexibility and scalability of the modular system, a decentralized synchronization method is proposed in this letter. The synchronization principle, control strategy, and control parameter design guidance are introduced step by step. Finally, the performance of the proposed strategy is verified by a series-connected three-module inverters system.