Types Of Control Strategies Research Articles

Event-Based Sampled-Data Average Consensus

This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.

Development and Motion Control of Biomimetic Underwater Robots: A Survey

Biomimetic underwater robots have attracted considerable research attention globally, owing to their quieter actuations, higher propulsion efficiency, and stronger maneuverability when compared with conventional underwater vehicles equipped with axial propellers. This article provides a comprehensive survey of current research in this field. First, we review the development status of biomimetic underwater robots in both body/caudal fin (BCF), median/paired fin (MPF), and their hybrid propulsion modes. Then, we outline the motion control methods employed in biomimetic underwater robots, including open-loop swimming control and typical closed-loop control strategies. In particular, we detail our latest studies on the RobCutt series underwater robots. On this basis, some critical issues and future directions are summarized. We predict that biomimetic underwater robots will have excellent prospects in underwater environment exploration and resource utilization.

Design, Analysis and Experimental Validation of a Fractional Order Terminal Sliding Mode Controller on Active Suspension System

ABSTRACT The vibrations in the vehicles are one of the discomforts to the passengers. The reduction of vibrations is a challenging task in the suspension system of the vehicle. The researchers are proposing different types of control strategies in the active suspension system to reduce the vibration and increase the ride comfort of the passengers. In this paper, Fractional Order Terminal Sliding Mode Controller (FOTSMC) is proposed to reduce the vibration and it is implemented with the Quanser experimental active suspension system (EASS). To validate the performance of the proposed controllers, its performances are compared with FOTSMC, terminal sliding mode controller and sliding mode controller. The designed controllers are tested with four types of road inputs with the Quanser EASS. Furthermore, the ride comfort is analyzed as per the ISO 2631–1 standard and the stability of the Quanser EASS with the designed controllers is tested. The power spectrum density is plotted to test the performance of the deigned controllers in the human-sensitive frequencies. The proposed FOTSMC outperforms other controllers in all aspects of the analysis considered in this paper.

Nonlinear Control Design of a Half-Car Model Using Feedback Linearization and an LQR Controller

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. The nonlinearities tend to degrade the performance of active suspension systems; these introduce harshness to the ride quality and reduce off-road mobility. Typical control strategies rely on linear models of the suspension dynamics. While these models are convenient, nominally accurate, and controllable due to the abundance of linear control techniques, they neglect the nonlinearities present in real suspension systems. The techniques already implemented and methods used to cope with problem of Half-Car model were studied. Every method and technique had some drawbacks in terms of complexity, cost-effectiveness, and ease of real time implementation. In this paper, an improved control method for Half-Car model was proposed. First, input/output feedback linearization was performed to convert the nonlinear system of Half-Car model into an equivalent linear system. This was followed by a Linear Quadratic Regulator (LQR) controller. This controller had minimized the effects of road disturbances by designing a gain matrix with optimal robustness properties. The proposed control technique was applied in the presence of the deterministic road disturbance. The results were verified using the Matlab/Simulink toolbox.

Dynamics of Unilateral and Bilateral Control Systems with State Feedback for Renewable Resource Management

In this paper, mathematical models for the management of biological resources based on a given predator-prey relationship are proposed, and two types of control strategies, unilateral and bilateral control with impulsive state feedback, are studied. The existence of the order-1 homoclinic orbit, order-1 periodic solution, and bifurcation of homoclinic of the unilateral control system are obtained, and the attraction region of this system is also discussed. Besides, sufficient conditions for the existence and stability of the order-1 and order-2 periodic solutions of the bilateral control system are also gained. A series of numerical simulations including bifurcation diagrams of periodic solution are performed, which not only verify the theoretical results we get but also reveal some peculiar dynamical phenomena, such as the appearance of high-order periodic solutions and existence of parameter intervals with drastic order change of periodic solution. By comparing the two management strategies, our study encourages bilateral control rather than unilateral control for the risk of predator extinction.

Fuzzy logic rate adjustment controls using a circuit breaker for persistent congestion in wireless sensor networks

Congestion control is necessary for enhancing the quality of service in wireless sensor networks (WSNs). With advances in sensing technology, a substantial amount of data traversing a WSN can easily cause congestion, especially given limited resources. As a consequence, network throughput decreases due to significant packet loss and increased delays. Moreover, congestion not only adversely affects the data traffic and transmission success rate but also excessively dissipates energy, which in turn reduces the sensor node and, hence, network lifespans. A typical congestion control strategy was designed to address congestion due to transient events. However, on many occasions, congestion was caused by repeated anomalies and, as a consequence, persisted for an extended period. This paper thus proposes a congestion control strategy that can eliminate both types of congestion. The study adopted a fuzzy logic algorithm for resolving congestion in three key areas: optimal path selection, traffic rate adjustment that incorporates a momentum indicator, and an optimal timeout setting for a circuit breaker to limit persistent congestion. With fuzzy logic, decisions can be made efficiently based on probabilistic weights derived from fitness functions of congestion-relevant parameters. The simulation and experimental results reported herein demonstrate that the proposed strategy outperforms state-of-the-art strategies in terms of the traffic rate, transmission delay, queue utilization, and energy efficiency.

PI and Hysteresis Current Controller for Grid-Connected Dynamic State Configuration Model of Solid Oxide Fuel Cell SOFC

As the surrounding problems of the states and the requirement to meet out the increasing energy demand are increasing gradually generation of distributed nature system based various types of clean power systems are being erected increasingly to manage the load side energy requirements and reduce the environmental issues. Fuel cell is the latest technology that can use as DG system and solve the above mention issues. In this research work, a grid-connected dynamic state of solid oxide fuel cell (SOFC) system is represented. The fuel cell stack DC voltage needs to be converted and stepped-up to match the load side grid. So, a DC-AC voltage source converter is utilized to for interfacing the fuel cells with the load side grid, and the transformer is installed for increasing the potential level to match the voltage grid. Two types of control strategies are presented (PI and hysteresis current controller) to control and shape the inverter output voltage, hence provides decoupled real and reactive energy. The entire work is modeled in MATLAB/Simulink.

Optimal Control of Joint Multi-Virus Infection and Information Spreading

Nowadays, epidemic models provide an appropriate tool to describe the propagation of biological viruses in human or animal populations, rumors and misinformation in social networks, and malware in both computer and ad hoc networks. It is common that there are multiple types of malware infecting a network of computing devices, and different messages can spread over the social network. Information spreading and virus propagation are interdependent processes. To capture their independencies, we integrate two epidemic models into one holistic framework, known as the modified Susceptible-Warned-Infected-Recovered-Susceptible (SWIRS) model. The first epidemic model describes the information spreading regarding the risk of malware attacks and possible preventive procedures. The second one describes the propagation of multiple viruses over the network of devices. To minimize the impact of the virus spreading and improve the protection of the networks, we consider an optimal control problem with two types of control strategies: information spreading among healthy nodes and the treatment of infected nodes. We obtain the structure of optimal control strategies and study the condition of epidemic outbreaks. The main results are extended to the case of the network of two connected clusters. Numerical examples are used to corroborate the theoretical findings.

Extensively used conventional and selected advanced maximum power point tracking techniques for solar photovoltaic applications: An overview

The lower output efficiency of the solar PV panel is due to the deviation of its operating point from the maximum power operation. And the change in the maximum power point (MPP) with the change in uncontrolled environmental conditions such as temperature and isolation make it difficult to withstand the MPP operation of the system. Different techniques and maximum power point tracking algorithms have been developed to address the issue. This paper presents a critical overview of widely used maximum power tracking techniques for photovoltaic system applications. Conventional, as well as advanced developed methods, which are less complex, robust and reliable, are discussed. However, some complexity occurs while selecting the appropriate MPPT method for a particular application. One of the contributions of this review article is to provide an outline for the selection of appropriate technique suitable for a particular application. Comparative analysis and classification of the selected MPPT methods based on various features such as type of control strategies, control variables, a converter circuit, and practical/commercial applications are presented. This review article is envisioned to serve as a useful reference for future MPPT users and PV system design engineers.

A critical study on optimal auxiliary frequency control of wind turbine generator and coordination with synchronous generator

Auxiliary frequency control of a wind turbine generator (WTG) has been widely used to enhance the frequency security of power systems with high penetration of renewable energy. Previous studies recommend two types of control schemes, including frequency droop control and emulated inertia control, which simulate the response characteristics of the synchronous generator (SG). This paper plans to further explore the optimal auxiliary frequency control of the wind turbine based on previous research. First, it is determined that the virtual inertia control has little effect on the maximum rate of change of frequency (Max-ROCOF) if the time delay of the control link of WTG is taken into consideration. Secondly, if a WTG operates in maximum power point tracking (MPPT) mode and uses the rotor deceleration for frequency modulation, its optimal auxiliary frequency control will contain only droop control. Furthermore, if the droop control is properly delayed, better system frequency response (SFR) will be obtained. The reason is that coordination between the WTG and SG is important for SFR when the frequency modulation capability of the WTG is limited. The frequency modulation capability of the WTG is required to be released more properly. Therefore, when designing optimal auxiliary frequency control for the WTG, a better control scheme is worth further study.

Effects of quantization and saturation on performance in bilateral teleoperator

SummaryQuantization caused by communication channel and saturation caused by manipulator actuator can influence the synchronized motion of bilateral teleoperation system. The primary contribution of this paper is the consideration of quantization phenomenon when designing control law for teleoperator. Two types of control schemes are considered: position error feedback and slave torque feedback. We demonstrate that asymptotic stability is possible if a suitable relationship holds among the parameters of quantizer, controller, and saturation level. The secondary contribution of the paper is the estimation for the domain of attraction of teleoperator. Linear matrix inequality–based optimization conditions are established to guarantee the stability. The calculated region provides a basis when selecting the initial states. Finally, to further demonstrate validity of the proposed method, simulation and experiment are performed on a pair of robots, which have limited actuation capacity and communication channel.

Project Stratagems for a Nonlinear Vector Controller Fed BLDC Motor

Brushless DC (BLDC) motors are becoming an engaging alternative to DC and Induction motors. Various types of control strategies like direct vector control and indirect vector controls are illustrated for variable speed Alternating current drives. When those control strategies are applied to the proposed drive, there are certain drawbacks like instability, sensitive to parameter variations, etc. In this work, in order to get rid of the above difficulties, a design methodology is proposed in the closed loop control of BLDC drive, in which there is an instinctive flexibility to produce the required torque for various possible set of currents. Using this methodology we can attain better control over the drive. A suitable nonlinear and a robust controller makes the drive robust, which in turn makes the system insensitive to the parameter variations and increases the degree of stability. Robust control is a technique, which can precisely deals with uncertainty. These control techniques are used to accomplish robust performance and stability in the existence of bounded modeling errors. This paper gives more information regarding the design features of BLDC motor using MATLAB software.

Design and Analysis of Closed Loop Control of Multilevel SVPWM Inverter Fed PMSM Drive

Permanent magnet synchronous machines have been universally used over induction machines in variable speed drives. For present trends and future developments, power electronics technology gives the extensive research of multilevel inverters that brings high safety voltages with low harmonic content in comparison with two-level inverter strategies. Multi level inverters implementation can be done by raising the number of power semi conductor controlled switching devices per phase to increase the number of inverter output voltage levels. By increasing the levels, power controlled switching devices and other components are increased, which makes the inverter complex and overpriced. From the above aspects, three-phase three-level inverter strategy is used for high performance and high voltage A.C drives. Multilevel inverter using a space vector pulse width modulation (SVPWM) strategy gives great advantages in high performance A.C drive applications. Various types of control strategies have been recommended for voltage source inverter fed A.C drives. In the proposed work, a PI controller is designed for the outer loop and non-linear controller using a state feedback linearization technique is designed for the inner loop. The closed loop control system for three-level inverter fed Permanent magnet synchronous motor drive employing SVPWM is extensively simulated using MATLAB.

Almost Output Regulation for Switched Positive Systems With Different Coordinates Transformations and its Application to a Positive Circuit Model

In this article, the issue of almost output regulation for continuous-time switched positive systems is investigated. We take into consideration the different coordinates transformations in which the subsystems are switched corresponding to the individual coordinate system. A new design scheme is firstly proposed in this manner. Furthermore, each group of the regulator equations has its own solution. Two types of control strategies, including a state feedback law and an error feedback law, are adopted. In contrast to the nominal output regulation problem, we consider the case where an unknown external disturbance affects the systems and the exogenous systems. Therefore, a concept of the almost output regulation for the considered systems is proposed. Then, all tractable conditions guaranteeing the solvability of the addressed problem are presented in terms of linear matrix equalities as well as linear vector inequalities by means of the constructed multiple linear copositive Lyapunov functions. A positive circuit is finally used to illustrate the applicability and availability of the developed theoretical findings.

Performance Evaluation of Fractional Order Pid and Sliding Mode Control with Optimization Tuning Access

The statistical analyses in the past showing the important properties of the electrohydraulic actuator (EHA) system, especially in the growth of the world economy. Dealing with the existing drawback in the EHA system, various types of control schemes have been introduced in the past. In this paper, to produce a more insightful view of the performance and the capabilities of the controller, three different types of controllers have been designed and compared. The favourite controller in the industry field, which is the proportional-integral-derivative (PID) controller will be first introduced. Follow by the improved PID controller, named Fractional Order (FO-PID) controller will be designed. Then, the prominent robust controller in the control field, called sliding mode controller (SMC) will be established. Instead of obtaining the controller’s parameters without any appropriate technique, the well-known tuning technique in computer science, named particle swarm optimization (PSO) will be utilized. Referring to the performances produced by these controllers, it can be concluded that the SMC is capable to generate most desired control performance that produced the highest accuracy with the smallest error in the analyses.

A data-driven hybrid control framework to improve transit performance

This paper presents a data-driven hybrid control (DDHC) framework that can arrange adaptive control strategies for vehicles to effectively improve the transit performance of the public transport system. The framework depicts a powerful combination of a data-driven control method that is used to imitate the control behaviour of dispatchers and a mathematical optimization method. Three components comprise the DDHC framework: a data-driven control module, a performance module, and an optimization module. The data-driven control module contains a random forest model which is adopted to justify whether to intervene in the operation of a bus line, and if so, which vehicles should be controlled and what type of control strategy should be taken – an acceleration strategy or deceleration strategy. The performance module including vehicle operation state models is used to describe the system evolution. The last component optimizes the specific control actions – which type of acceleration or deceleration strategy should be adopted – by minimizing total passenger travel time. The effectiveness of the proposed DDHC framework is evaluated with the data of a transit route in Urumqi, China. The results show that the DDHC framework with reasonable parameters can suit the needs of real-time control in complex traffic environments.

Analysis and optimization of frequency modulation strategy for hydropower units

Analysis the deficiencies of typical control strategies for AGC regulation and primary frequency regulation on conventional hydropower units. The logical relationship between primary frequency regulation and AGC is optimized. A new regulation method is proposed and applied in a hydropower plant. Practice shows that the method can avoid contradiction between AGC load adjustment and primary frequency modulation, and improve the frequency modulation performance of the unit. The optimization finally satisfy the requirements of power grid assessment.

Soft Rehabilitation and Nursing-Care Robots: A Review and Future Outlook

Rehabilitation and nursing-care robots have become one of the prevalent methods for assistant treatment of motor disorder patients in the field of medical rehabilitation. Traditional rehabilitation robots are mostly made of rigid materials, which significantly limits their application for medical rehabilitation and nursing-care. Soft robots show great potential in the field of rehabilitation robots because of their inherent compliance and safety when they interact with humans. In this paper, we conduct a systematic summary and discussion on the soft rehabilitation and nursing-care robots. This study reviews typical mechanical structures, modeling methods, and control strategies of soft rehabilitation and nursing-care robots in recent years. We classify soft rehabilitation and nursing-care robots into two categories according to their actuation technology, one is based on tendon-driven actuation and the other is based on soft intelligent material actuation. Finally, we analyze and discuss the future directions and work about soft rehabilitation and nursing-care robots, which can provide useful guidance and help on the development of advanced soft rehabilitation and nursing-care robots.

Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typical Control Strategies for Rural Electrification in Myanmar

Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typical Control Strategies for Rural Electrification in Myanmar

Evolutionary dynamics of cooperation in the public goods game with pool exclusion strategies

Social exclusion is widely used as a control mechanism to promote cooperative behavior in human societies. However, it remains unclear how such control strategies actually influence the evolutionary dynamics of cooperation. In this paper, we introduce two types of control strategies into a population of agents that play the public goods game, namely prosocial pool exclusion and antisocial pool exclusion, and we use the replicator equation to study the resulting evolutionary dynamics for infinite well-mixed populations. We show that the introduction of prosocial pool exclusion can stabilize the coexistence of cooperators and defectors by means of periodic oscillations, but only in the absence of second-order prosocial pool exclusion. When considering also antisocial pool exclusion, we show that the population exhibits a heteroclinic circle, where cooperators can coexist with other strategists. Moreover, when second-order exclusion is taken into account, we find that prosocial pool exclusion is the dominant strategy, regardless of whether the second-order exclusion is prosocial or antisocial. In comparison with punishment, we conclude that prosocial pool exclusion is a more effective control mechanism to curb free-riding.