Performance Of Closed-loop Control System Research Articles

Multi-Vehicle Navigation Using Cooperative Localization

This paper assesses the effectiveness of cooperative localization for improving the performance of closed-loop control systems for networks for autonomous multi-vehicle navigation. Nonlinear dynamic models of two- and three-dimensional vehicles are presented along with their linearized forms. A nonlinear control algorithm is then presented based on the dynamic model. Relative position measurement equations and their linearized forms are introduced. The state and measurement equations are then employed for the propagation and update steps of an EKF-based cooperative localization algorithm. Initially, a series of experiments with networks of quadcopters and mobile robots are presented to validate the performance of cooperative localization for state estimation with the continuous or intermittent presence of absolute measurements or their complete absence. Finally, the performance of the control algorithm is evaluated with and without cooperative localization to demonstrate its effectiveness for improving performance.

Predictor-Based Neural Dynamic Surface Control for Strict-Feedback Nonlinear Systems With Unknown Control Gains.

Neural dynamic surface control (NDSC) is an effective technique for the tracking control of nonlinear systems. The objective of this article is to improve closed-loop transient performance and reduce the number of learning parameters for a strict-feedback nonlinear system with unknown control gains. For this purpose, a predictor-based NDSC (PNDSC) approach is presented. It introduces Nussbaum functions and predictors into the traditional NDSC for nonlinear systems with unknown control gains. Unlike NDSC that uses surface errors to update the learning parameters of neural networks (NNs), the PNDSC employs prediction errors for the same purpose, leading to improved transient performance of closed-loop control systems. To reduce the number of learning parameters, the PNDSC is further embedded with the technique of the minimal number of learning parameters (MNLPs). This avoids the problem of the ``explosion of learning parameters'' as the order of the system increases. A Lyapunov-based stability analysis shows that all signals are bounded in the closed-loop systems under PNDSC embedded with MNLPs. Simulations are conducted to demonstrate the effectiveness of the PNDSC approach presented in this article.

Communication Times Reconstruction in a Telecontrolled Client–Server Scheme: An Approach by Kalman Filter Applied to a Proprietary Real-Time Operating System and TCP/IP Protocol

Nowadays, various systems were developed in the telecommunications field which make use of technologies for the transmission and reception of information. One of these technologies is the Internet, which was developed in tandem with scientific growth. Therefore, its application in the control of various industrial processes has a notable influence. In this context, there are industrial processes that, due to the potential danger they represent to human beings, must be controlled by means of a remote control system. Such systems can be implemented through client–server communication schemes, which form a network of computers to exchange information. In the exchange of information, delay times are generated. These inactivity times have a close relationship with the latency in the communication network and have a negative impact on the performance of closed-loop control systems. In this sense, for physical implementation, it is essential to measure and mathematically characterize their magnitudes in order to know their variability and thus be able to design control strategies that compensate for their effects. Hence, this research paper presents the reconstruction of the communication times measured from a telecontrol system, where it is assumed that only one subsystem acts as the controller and the other one acts as the controlled. In other words, this paper addresses a control scheme type of single-input-single-output system (SISO). This reconstruction is based on the Kalman filter, which estimates the communication times that are measured on an experimental test bench with a client–server communication scheme. Communication times are characterized as stochastic processes. So, in order to validate the reconstruction presented, the level of dependence between the random processes is evaluated by analyzing their moments of probability as well as their covariance moments. Finally, an analysis based on the mean square error is presented, through which it can be concluded that the reconstruction technique used allows one to know the dynamics of the communication times generated by the remote control process presented in this research.

Optimal adaptive interval type-2 fuzzy fractional-order backstepping sliding mode control method for some classes of nonlinear systems

In this research, a novel adaptive interval type-2 fuzzy fractional-order backstepping sliding mode control (AIT2FFOBSMC) method is presented for some classes of nonlinear fully-actuated and under-actuated mechanical systems with uncertainty. The AIT2FFOBSMC method exploits the advantages of backstepping and sliding mode methods to improve the performance of closed-loop control systems by lowering the tracking error and increasing robustness. To mitigate chattering and the tracking error, a fractional sliding surface is designed. In addition to the fractional sliding surface, an adaptive interval type-2 fuzzy compensator is used to estimate the uncertainty and perturbation of the nonlinear system in order to further reduce chattering caused by switching term as well as to enhance the perturbation rejection. In order to achieve an optimal performance, the multi-tracker optimization algorithm (MTOA) is used. Finally, a number of simulations and experimental tests are carried out to examine the performance of the AIT2FFOBSMC method.

INTELLIGENT FRACTIONAL ORDER ITERATIVE LEARNING CONTROL USING FEEDBACK LINEARIZATION FOR A SINGLE-LINK ROBOT

In this paper, iterative learning control (ILC) is combined with an optimal fractional order derivative (BBO-Da-type ILC) and optimal fractional and proportional-derivative (BBO-PDa-type ILC). In the update law of Arimoto's derivative iterative learning control, a first order derivative of tracking error signal is used. In the proposed method, fractional order derivative of the error signal is stated in term of 'sa' where  to update iterative learning control law. Two types of fractional order iterative learning control namely PDa-type ILC and Da-type ILC are gained for different value of a. In order to improve the performance of closed-loop control system, coefficients of both  and  learning law i.e. proportional , derivative  and  are optimized using Biogeography-Based optimization algorithm (BBO). Outcome of the simulation results are compared with those of the conventional fractional order iterative learning control to verify effectiveness of BBO-Da-type ILC and BBO-PDa-type ILC

Active Disturbance Rejection Station-Keeping Control of Unstable Orbits around Collinear Libration Points

An active disturbance rejection station-keeping control scheme is derived and analyzed for station-keeping missions of spacecraft along a class of unstable periodic orbits near collinear libration points of the Sun-Earth system. It is an error driven, rather than model-based control law, essentially accounting for the independence of model accuracy and linearization. An extended state observer is designed to estimate the states in real time by setting an extended state, that is, the sum of unmodeled dynamic and external disturbance. This total disturbance is compensated by a nonlinear state error feedback controller based on the extended state observer. A nonlinear tracking differentiator is designed to obtain the velocity of the spacecraft since only position signals are available. In addition, the system contradiction between rapid response and overshoot can be effectively solved via arranging the transient process in tracking differentiator. Simulation results illustrate that the proposed method is adequate for station-keeping of unstable Halo orbits in the presence of system uncertainties, initial injection errors, solar radiation pressure, and perturbations of the eccentric nature of the Earth's orbit. It is also shown that the closed-loop control system performance is improved significantly using our method comparing with the general LQR method.

Fuzzy controllers gains tuning: a constrained nonlinear optimization approach

This paper presents a methodology for tuning the gains of fuzzy proportional-integral controllers where the concept of closed-loop control system performance is explicitly taken into account. The fuzzy controller gains are found by solving a nonlinear constrained optimization problem considering the system’s dynamics described by a nonlinear model and a set of constraints on the controller gains, control actions and outputs. Experimental results collected on a test-bed show the pertinence of using the proposed tuning technique.

Real-time random delay compensation with prediction-based digital redesign

Today’s technological demands require challenging control solutions such as real-time applications of Networked Control System (NCS). However, due to communication protocol and shared data bus, NCS experiences uncertain and unpredictable time delays in both input and output channels. These delays cause asynchronization between the controller and the plant thereby degrading the performance of closed-loop control systems. To address this problem, this paper proposes to utilize digital redesign technique to provide real-time random delay compensation.

Maximum Sensitivity Based Robust Tuning for Two-Degree-of-Freedom Proportional−Integral Controllers

A tuning method for two-degree-of-freedom (2-DoF) proportional−integral (PI) controllers for first-order-plus-dead-time (FOPDT) models is presented. It allows the designer to deal with the closed-loop control system performance−robustness trade-off specifying the lowest robustness level allowed by selecting a maximum sensitivity in the 1.4−2.0 range. In addition, a smooth performance is obtained by forcing the regulatory and servo-control closed-loop transfer functions to perform as close as possible to a target nonoscillatory dynamics. Controller tuning rules are provided for FOPDT models with normalized dead-times from 0.1 to 2.0. Comparative examples show the effectiveness of the proposed tuning method.

Self-Triggered Feedback Control Systems With Finite-Gain ${\cal L}_{2}$ Stability

This paper examines a class of real-time control systems in which each control task triggers its next release based on the value of the last sampled state. Prior work used simulations to demonstrate that self-triggered control systems can be remarkably robust to task delay. This paper derives bounds on a task's sampling period and deadline to quantify how robust the control system's performance will be to variations in these parameters. In particular we establish inequality constraints on a control task's period and deadline whose satisfaction ensures that the closed-loop system's induced L 2 gain lies below a specified performance threshold. The results apply to linear time-invariant systems driven by external disturbances whose magnitude is bounded by a linear function of the system state's norm. The plant is regulated by a full-information H infin controller. These results can serve as the basis for the design of soft real-time systems that guarantee closed-loop control system performance at levels traditionally seen in hard real-time systems.

Controlling across complex networks – Emerging links between networks and control

This paper discusses the interplay between networks and control systems. As we gain more understanding about the structure and dynamics of physical networks, their effects on the performance of closed-loop control systems, as well as the ability to control such networks, provide fertile areas of research. The paper reviews such research with special emphasis on the connectivity and delays in the information transfer across networks.

State Based Self-triggered Feedback Control Systems with ℒ2 Stability

This paper examines a class of real-time control systems in which each control task triggers its next release based on the value of the last sampled state. Prior work by Lemmon et al. (2007) used simulations to demonstrate that self-triggered control systems can be remarkably robust to task delay. This paper derives bounds on a task's sampling period and deadline to quantify how robust the control system's performance will be to variations in these parameters. In particular we establish inequality constraints on a control task's period and deadline whose satisfaction ensures that the closed loop system's induced ℒ2 gain lies below a specified performance threshold. The results apply to linear time-invariant systems driven by external disturbances whose magnitude is bounded by a linear function of the system state's norm. The plant is regulated by a full-information H∞ controller. These results can serve as the basis for the design of soft real-time systems that guarantee closed-loop control system performance at levels traditionally seen in hard real-time systems.

Singularly perturbed feedback linearization with linear attitude deviation dynamics realization

A new approach for feedback linearization of attitude dynamics for rigid gas jet-actuated spacecraft control is introduced. The approach is aimed at providing global feedback linearization of the spacecraft dynamics while realizing a prescribed linear attitude deviation dynamics. The methodology is based on nonuniqueness representation of underdetermined linear algebraic equations solution via nullspace parametrization using generalized inversion. The procedure is to prespecify a stable second-order linear time-invariant differential equation in a norm measure of the spacecraft attitude variables deviations from their desired values. The evaluation of this equation along the trajectories defined by the spacecraft equations of motion yields a linear relation in the control variables. These control variables can be solved by utilizing the Moore–Penrose generalized inverse of the involved controls coefficient row vector. The resulting control law consists of auxiliary and particular parts, residing in the nullspace of the controls coefficient and the range space of its generalized inverse, respectively. The free null-control vector in the auxiliary part is projected onto the controls coefficient nullspace by a nullprojection matrix, and is designed to yield exponentially stable spacecraft internal dynamics, and singularly perturbed feedback linearization of the spacecraft attitude dynamics. The feedback control design utilizes the concept of damped generalized inverse to limit the growth of the Moore–Penrose generalized inverse, in addition to the concepts of singularly perturbed controls coefficient nullprojection and damped controls coefficient nullprojection to disencumber the nullprojection matrix from its rank deficiency, and to enhance the closed loop control system performance. The methodology yields desired linear attitude deviation dynamics realization with globally uniformly ultimately bounded trajectory tracking errors, and reveals a tradeoff between trajectory tracking accuracy and damped generalized inverse stability. The paper bridges a gap between the nonlinear control problem applied to spacecraft dynamics and some of the basic generalized inversion-related analytical dynamics principles.

An Analysis of Automatic Closed-Loop Control of Rotary Drive Engines

With this automatic control system for use on rigs equipped with a mechanically driven rotary table, it is possible to eliminate rotary speed variation caused by torque in the drill pipe. When closed-loop control is used, low-frequency variations in rotary speed can be completely eliminated, and high-frequency variations can be significantly damped, depending upon the power available. Introduction In applying technology to a drilling operation, rotary speed is of prime importance. For example, the d exponent, formation drillability, roller-bit-bearing and tooth wear, as well as many other drilling relationships are functions of rotary speed. If rotary speed is to be used in any equations related to these, it must be measurable and fairly constant over the time interval of interest. The conventional method of controlling rotary speed on a rig with an independent and mechanically driven rotary table is to use a pneumatic regulator at the drawworks. The regulator pneumatic regulator at the drawworks. The regulator supplies air pressure to a diaphragm, which mechanically positions the engine throttle. This method does not positions the engine throttle. This method does not provide a constant rotary speed. Variations in rotary provide a constant rotary speed. Variations in rotary torque present a constantly changing load to the engine. Consequently, if the throttle is held constant, the angular speed of the rotary table will vary considerably. This effect is illustrated in Fig. 1 which is an actual recording of torque and rotary speed on a rig where the rotary speed was controlled in the manner described above. Note that the average value of rotary speed varied inversely with torque until the driller finally changed the throttle setting to bring the rotary speed back to its initial value. To keep rotary speed constant, the throttle would have to be continuously repositioned to compensate for the load changes. An automatic closed-loop control system can perform this operation. Such a control system has been designed and successfully used on several rigs to control rotary speed remotely. Our purpose is to describe that closed-loop control system and the results of simulation and field testing. Basic Control Theory A closed-loop control system is one that controls a variable by measuring it, comparing it with a desired value and correcting it if it is not equal to the desired value. It follows then that the system must perform two equally important functions: measurement and control. A simple illustration of this would be a man controlling the temperature of an oven by looking at a thermometer, noting that it reads lower than the desired temperature. and throwing a switch that causes an increase in heat flow to the oven. In the system to be discussed here the control is automatic. There are many theories on how to study the performance of closed-loop control systems. The most performance of closed-loop control systems. The most common method, and the one that will be discussed here, uses simplified block diagrams and mathematical models. Terms that will be used throughout the paper are defined here: Input A signal in engineering units, going into the control loop or any of its components. Output A signal in engineering units, coming outof the control loop or any of its components. JPT p. 1305