Design Method Of Control System Research Articles

Control Strategy of Three-Phase Inverter with Isolation Transformer

In order to improve the control performance of a train auxiliary inverter and satisfy the requirements of power quality, harmonics, and unbalanced factor, this paper proposed a design method of a double closed-loop control system based on a complex state variable structure. The method simplifies the design process and takes full account of the effects of coupling and discretization. In the current closed-loop process, this paper analyzed the limitations of the proportional integral (PI) controller and simplified to P controller. In the voltage closed-loop, the paper employed the PI controller plus the resonant controller, designed the parameters of the PI controller. and analyzed the optimal discretization method of the resonant controller under dq axis coupling. Finally, experiments and simulations were conducted to show that the proposed method can achieve the above improvements.

Design of LPV fault-tolerant controller for hypersonic vehicle based on state observer

<p style='text-indent:20px;'>Considering the parameter uncertainty and actuator failure of hypersonic vehicle during maneuvering, this paper proposes a state observer-based hypersonic vehicle fault-tolerant control (FTC) system design method. Because hypersonic vehicles are prone to failure during maneuvering, the state quantity cannot be measured. First, a state observer-based FTC control method is designed for the linear parameter-varying (LPV) model with parameter uncertainty and partial failure of the actuator. Then, the Lyapunov function is used to demonstrate the asymptotic stability of the closed-loop system. The performance index function proved that the system has robust stability under the disturbance condition. Subsequently, the linear matrix inequality (LMI) was used to solve the observer parameters and the corresponding gain matrix in the control system. The simulation results indicated that the designed controller can track the flight command signal stably and has strong robustness, which verified the effectiveness of the design controller.

Generalized Iterative Learning Control Using Successive Projection: Algorithm, Convergence, and Experimental Verification

Iterative learning control (ILC) is a high-performance control design method for systems working in a repetitive manner. ILC has traditionally focused on tracking a reference defined at all points over a finite-time interval; recent developments have begun to exploit the design freedom unlocked by tracking only a finite number of distinct time instants driven by the needs of, e.g., robotic pick-and-place tasks. This paper proposes a generalized ILC paradigm, which extends and unifies the scope of existing design frameworks by amalgamating previous task descriptions and embedding system constraints on the input and output. A novel solution is then derived using a successive projection method, which provides well-defined convergence properties. The proposed design framework is illustrated by applying it to a spatial reference tracking problem with experimental results on a gantry robot testing platform demonstrating its effectiveness.

Modularized Control System Design of Underwater Vehicle for Submarine Cable Inspection

Zhang, S.; Sun, L.; Fan, L.; Song, S., and Li, Z., 2018. Modularized control system design of underwater vehicle for submarine cable inspection. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 579–584. Coconut Creek (Florida), ISSN 0749-0208.At present, the control system of underwater vehicle does not take into account the influence of nonlinear hydrodynamic factors, but mainly collects the state information from the central controller and generates control signals. The control function of the system is concentrated, which leads to poor system flow resistance and slower speed. In view of this problem, combined with the actual application requirements of underwater vehicle for submarine cable inspection, in this paper, a method of control system design based on modular thinking is proposed. Considering the nonlinear hydrodynamic factors, the four degree of freedom motion modeling method of vehicle is presented. The hardware part of the vehicle control system is decomposed into a series of standard modules according to the function. By using the method of modularization, the control system design of underwater vehicle for submarine cable inspection is designed. Experimental results show that the system has better anti-flow capability and faster speed.

A New Adaptive Control System Design Method Based on Neural Network Prediction

A New Adaptive Control System Design Method Based on Neural Network Prediction

A Preliminary Study on the Relationship Between Iterative Learning Control and Reinforcement Learning

Iterative learning control is a control system design method that is able to achieve high tracking performance by repeatedly executing a task and learning the best input from previous attempts of performing the task. Reinforcement learning is a machine learning method that determines the best action such that some utility function (reward) is maximised by repeatedly interacting with the environment (system) and learning the best action policy based on the reward received from such interactions. These two methods belong to different subject disciplines but share a number of similarities. The relationship between these two design approaches, however, has not been investigated in detail. This paper presents a preliminary study on the relationship between iterative learning control and reinforcement learning, hopefully shedding some light on how these two areas can benefit each other in future research.

H&lt;sub&gt;∞&lt;/sub&gt; disturbance attenuation of nonlinear networked control systems via Takagi-Sugeno fuzzy model

H∞ disturbance attenuation of nonlinear networked systems which are described by the Takagi-Sugeno fuzzy time-delay systems is concerned. In the networked control system, the control signal is delayed and the closed-loop system with the controller can be modeled as a fuzzy system with time-varying delays in sensor and actuator nodes. The system often encounters the external noises that disturb its behaviors. For such a nonlinear system with delays, the H∞ disturbance attenuation problem is considered. Multiple Lyapunov-Krasovskii function with multiple integral functions allows us to obtain less conservative conditions for a networked control system to satisfy the disturbance attenuation criterion. Based on this approach, a novel control design method for a networked control system is proposed. An illustrative example is given to show the effectiveness of the proposed method.

Development a Myoelectric Prosthetic Hand for Partial Hand Amputees to Use Successfully Remaining Finger -Proposal of the Design Method for Mechanical System and Control System and Prototype -

Development a Myoelectric Prosthetic Hand for Partial Hand Amputees to Use Successfully Remaining Finger -Proposal of the Design Method for Mechanical System and Control System and Prototype -

Survey and tutorial on multiple model methodologies in modelling, identification and control

Multiple model methodology is an important approach in modelling, identification and control of complicated systems with large uncertainties (parameter uncertainty or even model structure uncertainties). It agrees with the idea of 'divide and conquer' in solving engineering problems. There are two representative strategies with scheduling the multiple models, i.e., switching strategy and weighting strategy. Theses two strategies can be alternatively viewed as 'identification' of correct model/controller. Consequently, any reasonable control system design methods can be incorporated with switching or weighting methodology to formulate robust and adaptive control schemes. This survey paper gives a brief historical review of the development of multiple model adaptive estimation (MMAE) and multiple model adaptive control (MMAC), then moves focus onto the new progress of weighted MMAC (WMMAC) that has emerged in recent years including the weighting algorithm and stability analysis of WMMAC systems, based on virtual equivalent system (VES) theory.

Optimal Design of Hybrid Control System for the Wind and Earthquake Excited Buildings

An optimal design method for a hybrid control system is proposed in this study. Unlike conventional design approach, passive and active control systems are realized as a combined system and they are simultaneously optimized considering multi-hazard excitations. From the initial design stage, a state space equation is developed including the dynamic characteristics of the both systems and multiple loading conditions. A simultaneous optimization problem is formulated by introducing a preference model and the genetic algorithm is employed in order to find the optimal distribution and capacities of the control devices. An example design for a 30-story building with an active tuned mass damper and viscous damping devices is taken into account and numerical simulations are performed. The comparative results demonstrate the effectiveness and validity of the proposed method.

A Control Structure for Unilateral System with Communication Rate Constraint

This study proposes a design method for unilateral control systems with communication rate constraints. In the case where it is necessary to control under a communication rate constraint, the effec...

An Operator-based Nonlinear Vibration Control System Using a Flexible Arm with Shape Memory Alloy

In the past, arms used in the fields of industry and robotics have been designed not to vibrate by increasing their mass and stiffness. The weight of arms has tended to be reduced to improve speed of operation, and decrease the cost of their production. Since the weight saving makes the arms lose their stiffness and therefore vibrate more easily, the vibration suppression control is needed for realizing the above purpose. Incidentally, the use of various smart materials in actuators has grown. In particular, a shape memory alloy (SMA) is applied widely and has several advantages: light weight, large displacement by temperature change, and large force to mass ratio. However, the SMA actuators possess hysteresis nonlinearity between their own temperature and displacement obtained by the temperature. The hysteretic behavior of the SMA actuators affects their control performance. In previous research, an operator-based control system including a hysteresis compensator has been proposed. The vibration of a flexible arm is dealt with as the controlled object; one end of the arm is clamped and the other end is free. The effectiveness of the hysteresis compensator has been confirmed by simulations and experiments. Nevertheless, the feedback signal of the previous designed system has increased exponentially. It is difficult to use the system in the long-term because of the phenomenon. Additionally, the SMA actuator generates and radiates heat because electric current passing through the SMA actuator provides heat, and strain on the SMA actuator is generated. With long-time use of the SMA actuator, the environmental temperature around the SMA actuator varies through radiation of the heat. There exists a risk that the ambient temperature change dealt with as disturbance affects the temperature and strain of the SMA actuator. In this research, a design method of the operator-based control system is proposed considering the long-term use of the system. In the method, the hysteresis characteristics of the SMA actuator and the temperature change around the actuator are considered. The effectiveness of the proposed method is verified by simulations and experiments.

Point-to-Point Iterative Learning Control With Optimal Tracking Time Allocation

Iterative learning control (ILC) is a high-performance tracking control design method for systems operating in a repetitive manner. This paper proposes a novel design methodology that extends the recently developed point-to-point ILC framework to allow automatic via-point time allocation within a given point-to-point tracking task, leading to significant performance improvements, e.g., energy reduction. The problem is formulated into an optimization framework with via-point temporal constraints and a reference tracking requirement, for which a two-stage design approach is developed. This yields an algorithmic solution, which minimizes input energy based on norm optimal ILC and gradient minimization. The algorithm is further expanded to incorporate system constraints into the design, prior to experimental validation on a gantry robot test platform to confirm its feasibility in practical applications.

Self-repairing Adaptive PID Control for Plants with Sensor Failures

This paper presents a new design method for a self-repairing adaptive PID control system. The control system has the adaptive adjusting mechanisms for the PID gains, and also can detect the sensor failure by self-test using the integrator in the PID controller. Hence, for plants with unknown parameters, self-repairing control can be successfully attained. Furthermore, in this paper, the control performances are theoretically analyzed.

DESIGN OF THE CONTROL SYSTEM BY MOVEMENT OF ROBOTS MOBILE GROUP IN CONDITIONS OF UNCERTAINTY

Many controlled plants, in particular mobile robots, solve various tasks in a priori uncertain conditions. In this connection their mathematical models necessary for creation of qualitative control systems are unknown. Therefore development of design methods of adaptive control systems is actuality. The big uncertainty of this control problem makes application of adaptive systems with identification by the most expedient. In article the new analytical design method of adaptive control systems by movement of mobile robots group in the uncertainty conditions is offered. This method is focused on the decision of a task of identification of the current mathematical models of robots with the subsequent design of a control system by movement of each robot. The suggested method can be realized automatically as required. It is developed on a basis of the markov method of identification, the method of analytical design of systems with control on output and impacts, and also the standard normalized transfer functions are used. As a whole this method allows to design of the adaptive control systems with desirable qualitative properties. Trial step functions of the small intensity and the original method of digital processing of the information are used at identification. Property of system invariancy of the markov parameters and their direct connection with factors of the discrete dynamic systems transfer functions are a basis of the method of digital processing of the information. It is supposed, that the mobile robots are full or can be stabilized at all possible values of their order and parameters. The suggested method can be used for creation of control systems by the various technical plants functioning in conditions of uncertainty.

Design of Two-Channel Bilateral Control Systems by a Transfer-Function-Based Approach

In this paper, we propose a design method of a two-channel bilateral control system using an approach based on transfer function. The configuration of such a control system can be realized by designing a complementary sensitivity function. Compared with the conventional four-channel bilateral control, our system has better control performance and requires fewer communication channels. The proposed scheme can be extended to micro/macro bilateral control that changes the scaling ratio of the master to slave systems. The proposed bilateral control can be realized simply by using a simple controller. In order to compare performances of the proposed method and the conventional four-channel bilateral control, ordinary bilateral control and micro/macro bilateral control are performed by a simple experimental machine with a one-degree-of-freedom mechanism. We discuss the features of each method by comparing the transparency and operability of both methods.

Singularity-Free Model Predictive Spacecraft Attitude Regulation Using a Variable-Speed Control Moment Gyroscope Model

This paper discusses spacecraft control using variable-speed CMGs. A new operational concept for VSCMGs is proposed. This new concept makes it possible to approximate the complex nonlinear system by a linear time-varying system (LTV). As a result, an effective control system design method, Model Predictive Control (MPC) using robust pole assignment, can be used to design the spacecraft control system using VSCMGs. A nice feature of this design is that the control system does not have any singular point. A design example is provided. The simulation result shows the effectiveness of the proposed method.

MOGA-Based Structural Design Method for Diagrid Structural Control System Subjected to Wind and Earthquake Loads

An integrated optimal structural design method for a diagrid structure and control device was developed. A multi-objective genetic algorithm was used and a 60-story diagrid building structure was developed as an example structure. Artificial wind and earthquake loads were generated to assess the wind-induced and seismic responses. A smart tuned mass damper (TMD) was used as a structural control system and an MR (magnetorheological) damper was employed to develop a smart TMD (STMD). The multi-objective genetic algorithm used five objectives including a reduction of the dynamic responses, additional stiffness and damping, mass of STMD, capacity of the MR damper for the integrated optimization of a diagrid structure and a STMD. From the proposed method, integrated optimal designs for the diagrid structure and STMD were obtained. The numerical simulation also showed that the STMD provided good control performance for reducing the wind-induced and seismic responses of a tall diagrid building structure.

Adaptive PID control system with assigned robust stability

This paper presents a proportional‐integral‐derivative (PID) control system design method for discrete‐time first‐order plus dead‐time plants. Because the relation between the tracking performance and the robust stability is the trade‐off, the PID parameters of the PID control system are decided such that the tracking performance is optimized subject to the assigned robust stability, where the reference or disturbance response is selected as the tracking performance. In the proposed method, the PID parameters decision method is designed using a neural network with an extreme learning machine. Hence, the optimal PID parameters are obtained based on the trade‐off between the tracking performance and the robust stability. Furthermore, the proposed design method is extended as the adaptive control, and hence an unknown or time‐varying plant, is well controlled using the proposed method. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley &amp; Sons, Inc.

Robust Control Design for Quad Tilt-Wing UAV

This paper describes the design method of a flight control system of a Quad Tilt-Wing (QTW) Unmanned Aerial Vehicle (UAV). A QTW-UAV is necessary to design a controller considering its nonlinear dynamics because of the appearance of the nonlinearity during transition flight between hovering and level flight. A design method of a flight control system using Dynamic Inversion (DI) that is one of linearization method has been proposed for the UAV. However, the design method based on an accurate model has a possibility of deterioration of control performance and system stability. Therefore, we propose a flight control system that considers uncertainties such as modeling error and disturbances by applying an H-infinity controller to the linearized system. The validity of the proposed control system is verified through numerical simulation and experiment.