Transactions of the Institute of Measurement and Control

Amrr, Syed Muhammad; Nabi, M

doi: 10.1177/0142331219860651pmid: N/A

This paper proposes a robust event-driven control for attitude regulation in flexible spacecraft affected by inertial parametric uncertainties and external disturbances. The bandwidth constraint of the communication channel between controller and system requires an event-based control design. Under the action of proposed control law, the system trajectories are ensured to be uniformly ultimately bounded (UUB) in a small vicinity of their equilibrium points. Apart from the boundedness of states, the proposed event-triggered controller also satisfies bandwidth restrictions by achieving a substantially low control usage. The results obtained from numerical simulations are indeed encouraging. It demonstrates the proposed controller as a potential alternative to the periodically sampled data controllers. Moreover, the proposed control strategy successfully eludes the unwanted unwinding phenomenon encountered in quaternion based attitude control of the spacecraft.

Shen, Shaobo; Song, Aiguo; Li, Tao; Li, Huijun

doi: 10.1177/0142331219860928pmid: N/A

This paper addresses the time delay compensation problem for nonlinear teleoperation system. A novel motion prediction approach is proposed based on a state observer with a cascade structure. The actual positions of master robot are estimated on the slave side by using delayed information of measurements. The prediction errors remain bounded under an appropriate set of assumptions for the system uncertainties. Moreover, an essential theorem for slave controller design is proposed to demonstrate performance recovery of the closed-loop system with cascade observer. By using the predictions, the forward time delay is effectively compensated when we design the controller of slave robot. Simulations are performed to verify the effectiveness of proposed method. The prediction results are highlighted through comparing with other two kinds of cascade predictors.

Han, Yu-Qun; Zhu, Shan-Liang; Duan, De-Yu; Chu, Lei; Yang, Shu-Guo

doi: 10.1177/0142331219861189pmid: N/A

In this paper, an adaptive decentralized control approach is proposed for a class of large-scale nonlinear systems with unknown dead-zone inputs using neural network. Firstly, the dead-zone outputs are firstly represented as simple linear systems with a static time-varying gain and bounded disturbance by introducing characteristic function. Secondly, in the controller design, neural networks are utilized to approximate the unknown nonlinear functions. Thirdly, an adaptive decentralized tracking control approach is constructed via backstepping design technique. It is shown that the proposed control approach can assure that all the signals of the closed-loop system semi-globally uniformly ultimately bounded and the tracking errors finally converge to a small domain around the origin. The proposed method can get precise tracking results with low computational cost, and have a good real-time performance and convergence. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme.

Jiang, Yan; Zhai, Junyong

doi: 10.1177/0142331219862976pmid: N/A

This paper aims at addressing the sampled-data output feedback control problem for a class of uncertain switched stochastic nonlinear systems, whose control input is quantized by a logarithmic quantizer and the output gain cannot be precisely known. We design a compensator with the quantized information. With the help of the feedback domination approach and the backstepping design method, a sampled-data output feedback controller is constructed with appropriate design parameters and a maximum sampling period to guarantee the global exponential stability in mean square of the closed-loop system under arbitrary switching. Finally, a numerical example is given to illustrate the effectiveness of the proposed scheme.

Feliu-Batlle, Vicente; Rivas-Perez, Raul

doi: 10.1177/0142331219862978pmid: N/A

In this paper, a new strategy for robust control of temperature in a steel slab reheating furnace with large time delay uncertainty based on fractional-order controllers combined with a Smith predictor is proposed. A time delay model of the preheating zone of this process is used, obtained from an identification procedure applied in a real industrial furnace. It is shown that this process experiences very large time delay changes. A fractional-order integral controller embedded in a Smith predictor structure (FI-SP) is designed, which is robust to changes in such time delay. Simulated results of a standard Proportinal Integral Derivative (PID) controller, a PID controller embedded in a Smith predictor and the proposed FI-SP controller are compared. Six performance indexes have been used in this comparison. The analysis of these indexes shows that the designed FI-SP controller exhibits the most robust behavior (lowest indexes averaged in all the range of time delay variation) for ranges that include large time delays. Then the robustness features of the FI-SP controller outperform the other integer order controllers in the time responses both to set-point changes and to step disturbances. Therefore, this controller guarantees the best accuracy of temperature control. The designed FI-SP guarantees system stability and robust performance for a high range of plant time delay uncertainties.

Torres, Felipe-de-Jesús; Guerrero, Gerardo-Vicente; García, Carlos-Daniel; Núñez, Diego-Alfredo; Mota, Juan

doi: 10.1177/0142331219862975pmid: N/A

This paper presents a design of synchronization of robot manipulators driven by induction motors in the case where the flux, velocity and currents are estimated. The synchronization is developed in both the joint space and workspace. The d−q field oriented frame model of the induction motor is used to design the synchronization control approach. An observer based on the α−β frame model is proposed to estimate the flux, velocity and currents variables, then they are converted to the variables of the d−q field-oriented model, and finally the remaining variables are estimated by means of an observer based on the d−q frame model. Stability is proved via a Lyapunov analysis. Simulations show the proposed controllers yield synchronization errors asymptotically stables in the closed-loop response.

Altork, Basim; Yazici, Hakan

doi: 10.1177/0142331219863875pmid: N/A

In this paper, a three-degree-of freedom (3 DOF) integrated vehicle lateral, yaw, roll dynamics model with optimal control design have been proposed to improve the bus lateral stability and handling performance. First, a 3 DOF vehicle model for a passenger bus is introduced. The 3 DOF model dynamics include the vehicle steering wheel angle, forward speed, yaw motion, sideslip angle, lateral acceleration and the rolling motion. Then, the presented 3 DOF model is used to design the robust static output feedback H∞ controller for both nominal system and uncertain system. The proposed controller is designed to improve the bus lateral stability and handling performance by controlling the yaw rate during normal driving and maneuvers. For the robust static output feedback H∞ controller, the norm bounded uncertainty is considered to simulate the variation of vehicle forward velocity uncertainty. The robust controller is designed to check the lateral stability of the bus at different forward velocity and at different velocity uncertainty. The controllers are synthesized within the H∞ control approach and the controllers’ design conditions are given within the Linear Matrix Inequalities (LMIs) framework. Numerical simulations have been carried out to demonstrate the effectiveness of the proposed controllers. The obtained simulation results show that the designed nominal and robust controllers enhance the lateral stability of the bus by reducing the amplitude of the yaw rate, lateral acceleration and rolling motion. Hence, the improvements in bus lateral stability and handling performance are achieved.

Moetamedzadeh, Hamid Reza; Khanmirza, Esmaeel; Pourfard, Ali; Madoliat, Reza

doi: 10.1177/0142331219864190pmid: N/A

In gas pipeline networks, the set-points should be carefully tuned to minimize the fuel consumption of compressor stations and meet the network requirements. In practice, the real demand has some variations over the forecasted one and consequently utilizing an appropriate controller to minimize the fuel consumption and manage the network variations is inevitable. The model predictive control is a great choice for systems with long delay such as gas networks. In this paper, an intelligent nonlinear model predictive control of a gas pipeline plant is proposed. It models the plant in fully transient state by a multi-layer perceptron neural network. The prediction power of the neural network is used to predict the plant output over a receding horizon. Initially, the network is trained offline and is then paralyzed with the real plant for online training. The proposed strategy consists of two main stages. In the first stage, the compressor set-points are optimized in the open loop condition considering the forecasted demand over a receding horizon and the resulting output pressures are chosen as the reference trajectories for the closed loop system. In the second stage, the controller is applied to compensate the demand variations. The optimization task is carried out using particle swarm optimization gravitation search algorithm (PSOGSA). Numerical results confirm the accuracy and robustness of the proposed controller in the presence of demand variations, noise and uncertainties.

Tan, Fei; Zhou, Lili

doi: 10.1177/0142331219863885pmid: N/A

This paper investigates the problem of synchronization for complex networks with time delays and stochastic uncertainties. Based on Lyapunov-Krasovskii functional theory, some sufficient conditions are derived. To deal with random uncertainties in networks, some suitable nonlinear adaptive controllers are designed, and some updating laws are used to deal with the feedback factor. The designed nonlinear adaptive controller can be used not only for synchronization of networks with delayed nodes, but also for the synchronization of networks with delayed random noises and delayed nodes. Finally, numerical examples illustrating the effectiveness of the proposed theoretical results are provided.

Hajji, Soufien; Ayadi, Assil; Agerbi Zorgani, Youssef; Maatoug, Tarak; Farza, Mondher; M’Saad, Mohamed

doi: 10.1177/0142331219864188pmid: N/A

This paper addresses the control of induction motor (IM) drives. In this work, we propose a new consideration of backstepping control. However, this control provides a systematic method to carry out the controller design while guaranteeing the stability of the controller-process couple. Furthermore, the incorporation of an integral action in the synthesis of the control system with state feedback presents a robust rejection of echelon-level disturbances. A detailed analytic study and simulation results are given showing the operation of the IM drives control. The results prove the accuracy and robustness of the proposed control scheme. Also, comparison results with another study dealing with control prove that the proposed method shows excellent transient and steady-state speed and a great estimation of flux and load torque.