Journal of Control
Year:2021 | Volume:15 | Issue:1|Papers Count:11

In this paper, a new approach is presented to design a gain-scheduled state-feedback controller for uncertain linear parameter-varying systems. It is supposed that the state-space matrices of them are the linear combination of the uncertain scheduling parameters. It is assumed that the existed uncertainties are of type of timeinvariant parametric uncertainties with specified intervals. Simultaneous presence of the concepts of the gainscheduling and the time-invariant uncertainties is a serious challenge. Because, the philosophy of the gainscheduling is variability with time. But, the time-invariant parametric uncertainties are constant and unknown. To obviate this challenge, a robust state-feedback law is proposed that is robust against the time-invariant uncertainties. In this method, the arbitrary values are selected for the uncertainties from the defined intervals. But, the selected values are not necessarily equal to the true ones. Hence, the new scheduling parameters are presented to calculate the proposed controller. Finally, the proof of the proposed scheme is presented based on Lyapunov concept. To show the effectiveness of the final controller, the proposed method is simulated to stabilize the roll rate of a typical missile. Also, the simulation results are compared with the experimental ones in the presence of the INS (Inertial Navigation System) module.

Human Immunodeficiency Virus (HIV) weakens the immune system in confronting various diseases by attacking to CD4+T cells. In modeling HIV behavior, the number of CD4+T cells is considered as the output. But, continuous-time measurement of these cells is not possible in practice, and the measurement is only available at variable intervals that are several times bigger than sampling time. In this paper, a state-dependent impulsive observer is designed for state estimation of HIV model. In order to model the HIV behavior, nonlinear time-delay differential equation is employed which considers the intracellular delay. The proposed observer is based on extended pseudo linearization technique. Even though, the number of CD4+T cells is available only in time-varying impulse intervals, this observer is capable of providing a continuous-time estimation of HIV states. It is also suitable for the continuous-time and impulsive control inputs. The asymptotic stability analysis of the suggested observer is guaranteed based on comparison principle and sector-bounded condition under some new theorems with well-defined sufficient conditions and less conservatism. Simulation and numerical results confirmed the efficiency of the proposed method despite the variable timedelays.

This paper proposes a distributed framework for formation control of USVs around a predefined target. This framework, according to the mission and problem conditions, includes three parts: determination of a desired path for each USV, preventing USVs entry to the target area and tracking the desired path of USVs under environmental disturbances. In the first part, a distributed approach is proposed to determine desired path for each USV and forming an aimed USVs arrangement around the target. In the second part, by modifying artificial potential function and smoothly redirecting USVs, the restriction of not entering the target’ s region is met. Finally, in the third section, a robust control algorithm for the USVs navigation in the presence of wind and sea current disturbances is developed based on the nonsingular terminal sliding mode control. The developed control algorithm firstly improves maneuverability of USVs using virtual velocity command planning, and secondly, provides a finite time trajectory tracking. Also, stability of the closed loop control is analyzed using Lyapunov stability theorem and the performance of the proposed control algorithm is compared with results of the conventional terminal sliding mode control. Simulation results demonstrate proper performance of the proposed framework in terms of improving tracking accuracy of the desired path and reaching a circular arrangement of USVs surrounding the target.

This paper presents a robust H∞ controller design, based on a generalized dynamic observer for uncertain singular systems in the presence of disturbance. The controller guarantee that the closed loop system be admissible. The main advantage of this method is that the uncertainty can be found in the system, the input and the output matrices. Also the generalized dynamic observer is used to estimate the states of system. This type of observer increases the steady state accuracy because of the integral term, and because of the dynamic term, it has a higher estimation speed than proportional-integral observers. First, the necessary condition for existence a generalized dynamic robust observer is presented and some coefficients matrices of observer are computed that the estimation error asymptotically converges to zero. The robust H∞ controller is then designed using state feedback in order to guarantee that the closed loop system is admissible. The existence conditions of the observer and the controller are given simultaneously using suitable Lyapunov function. Moreover, existing inequalities are transformed into linear matrix inequalities (LMI) using a set of algebraic relationships, and by solving these LMIs, the coefficients of the observer and the controller are obtained. Finally, by presenting an algorithm, the computational method will be expressed in a systematic way, and a numerical example demonstrates the efficiency of proposed method.

In designing the anti-lock braking system (ABS), some states and parameters of vehicle system such as road friction of coefficient and wheel slip should be estimated due to lack of cost effective and reliable sensors for direct measurement. Because of nonlinear characteristics of vehicle dynamics and tire forces, development of a nonlinear estimation algorithm is necessary. However, consideration of physical constraints can enhance the accuracy and reliability of estimation algorithm in real situations. In this paper, the extended Kalman filter (EKF) is applied for the ABS and its algorithm is modified in way that the physical limitations of road friction and wheel slip could be considered. The performance of the modified EKF in the constrained case is compared with the conventional EKF. At the rest of paper, a nonlinear predictive-based controller is analytically designed for the ABS and combined with the proposed constrained estimation algorithm. In order to decrease the effect of estimation errors on tracking performance, the integral feedback technique is combined with the control strategy. The simulation results indicate that not only the proposed algorithm improves the tracking accuracy in the presence of uncertainties, but also the control signal oscillations with high frequency will be prevented.

In this research paper, modeling of plasma vertical position (PVP) in Damavand tokamak is discussed. Due to complexity and nonlinearity of this machine, conventional linear methods of modeling and system identification cannot satisfy expected performance. In this research paper, the fractional order multiple model (FOMM) is proposed for modeling of plasma position in total operating regions of tokamak machine. By using the experimental data, several fractional order local simple models were constructed based on error criterion to cover all possible operating points. Then the obtained model bank is evaluated and validated using experimental data. The results of validation and comparison with previous models on the same machine show improvement of modeling performance.

In this paper, the trajectory tracking control problem for a team of nonholonomic tractor-trailer wheeled mobile robots has been investigated based on the leader-follower strategy in the presence of structural uncertainties and external disturbances. For this purpose, the kinematic and dynamic equations of the formation of tractor-trailer robots are presented and leader-follower's model is produced by defining the state error vector at first. Then, a nonlinear disturbance observer is designed by using the formation dynamic model to estimate and compensate the external disturbance and a new model of the system is obtained. In the following, a finite-time dynamic surface controller has been designed and presented by considering an observer-based model. The proposed scheme ensures closed-loop signals boundedness and fast convergence of tracking errors in a limited time. Furthermore, the parametric uncertainties are estimated by using a fuzzy adaptive estimator with a great accuracy. Finally, the finite time stability of the closed-loop control system is proved by Lyapunov theory and the effectiveness of proposed algorithm is shown by simulations.

Nowadays, the technology of digital systems is moving towards increasing the number of processing elements on a chip, which requires scalable and efficient communication infrastructure to achieve higher performance. Network-on-chip (NoC) is a high-performance solution for dealing with many on-chip communication challenges, such as the wiring complexity and the integration of a large number of transistors on a chip. In NoC, communication protocols, routing algorithms and topologies play important roles in the overall system performance. In this paper, a multicast adaptive routing algorithm with fuzzy-based load control for mesh-based NoCs is proposed. This algorithm, due to the non-uniform production and distribution of unicast and multicast packets, prevents dead-locks and live-locks dynamically by the fuzzy control system. The proposed algorithm leads to efficient congestion management, latency reduction and improvement in network throughput and reliability, and even reduction in power consumption. The results of evaluations and comparison with recent multicast routing algorithms demonstrate that the proposed algorithm provides higher reliability and better performance for both 2D and 3D NoCs with mesh topology, than the other works.

Alarm systems play an important role in ensuring safety, and preventing event occurrence in industrial plants. One of the most important steps in alarm system designing is estimation of the proper probability density function (pdf). Conventional methods in alarm system designing like, dead-band and delay timers cannot be more effective in case of alarm variable with mixture pdf. This paper presents a new method to design an univariate alarm system with mixture pdf in alarm variables. In this paper three alarm performance indecis are derived for variables with gussian pdf. In proposed method, rasing and clearing alarms are based on the probability values corresponding to the instantaneous alarm variable values in the normal and abnormal pdfs (normal and abnormal reference models). The effectiveness of the proposed method is shown during some simulation and industrial case studies and its performance compared with Reset scenario in delay timers. In one of the case studies, the performance of the proposed method in the DAMADICS benchmark actuators has been investigated.

In this paper autonomous modification of satellite attitude in its orbit is implemented for low earth orbit satellites using Model Predictive Control. MPC minimizes force which applying on the thrusters subject to hard constraints on the control input and output of the system. Here Clohessy-Wilshire equations are utilized by consideration of main disturbance of low orbits such as Atmospheric Drag and Non-Spherical earth disturbance for the design of MPC. The result of simulation proves that this MPC can amend the difference between the linear and non-linear mathematical models of the satellite. In addition, not only orbital disturbances are compensated but also the satellite maintained in orbit with high accuracy. For performance evaluation of this MPC method, A Linear Quadratic Regulator is realized for Orbit's autonomous control; the result of these two methods demonstrated that fuel consummation and control effort in MPC manner is considerably less than LQR method.

This paper investigates the fuzzy tracking control problem of a class of uncertain linear dynamical systems. The uncertainty of linear dynamical system is considered as fuzzy numbers. This kind of uncertain linear dynamical systems is called fuzzy linear dynamical systems which are expressed in the form of a fuzzy differential equations system. The relative-distance-measure fuzzy interval arithmetic approach and the concept of granular derivatively are utilized to deal with the fuzzy differential equations system. The main aim of designed fuzzy tracking control is to find a fuzzy control law by which the output of the system tracks the reference input. To this end, the fuzzy control law is presented in the form of a theorem. The presented control law is in the form of fuzzy state feedback with fuzzy gains and a fuzzy pre-compensator. Since the system’ s states always cannot be measured, a fuzzy observer must be designed to estimate the system’ s states. At the end, fuzzy tracking control of output of a two tanks in series system and control of airplane landing are presented to show the effectiveness of the proposed approach.