Current Issue : October - December Volume : 2019 Issue Number : 4 Articles : 5 Articles
Several researchers have revealed the huge potentials of rescue robots in disaster zones. In addition to searching for victims, these\nintelligent machines are also effective in obtaining useful information from the zones. These functions help to optimize the search\nand rescue missions. However, the fact that rescue robots have to operate in risky and dangerous environments necessitates the\nneed for suchmachines to have an efficientmotion control system, which can help themto operate autonomously or with minimal\nhuman control. This paper reviews the use of reliable controllers in enhancing the sensing capabilities of rescue robots. Huge\npotential of sensorless sensing method in the rescue robots are highlighted. It is shown that the use of sensorless sensing method\nenables developer to create simple and cheaper robots for various complex situations. Thus, it is imperative to conduct further\nstudies on how to optimize the operations of robots that lack sensors....
A controller based on dynamic surface control and observer is proposed by using motor state feedback for trajectory tracking of\nflexible joint robot with uncertain link dynamic model. Considering the link state information cannot be obtained, an observer\nis designed to estimate the link state information, and a dynamic surface controller is proposed based on link state observer. The\ncontroller based on the observer compared to backstepping controller avoids the repeated differentiation problem.At the same time,\nthe dynamic surface method avoids theme asurement of high order signal.The simulation results show that the designed controller\nhas a good trajectory tracking effect, which effectively suppresses the residual vibration of the flexible joint robot. Moreover, the\nproposed controller and observer are robust to the uncertainty and external disturbance of the link dynamic model.The proposed\ncontroller can be directly applied in the flexible joint robot without installing additional sensors, which is very important for\nindustrial applications....
This paper proposed a fractional-order PID controller and active disturbance rejection control (ADRC) method for the current\ncompensation of active power filter (APF). The control method consists of two closed loops. One is a reference current tracking\nloop based on the ADRC controller, which can treat the internal and external uncertainties of the system as a whole.The other is the\nvoltage control loop with the fractional-order PID controller for more flexibility. Simulation results demonstrate that the proposed\ncontrol method has a stronger robustness and higher compensating precision comparing with the double-loop PID controlmethod....
In this contribution, a gain adaptation for sliding mode control (SMC) is proposed that\nuses both linear model predictive control (LMPC) and an estimator-based disturbance compensation.\nIts application is demonstrated with an electromagnetic actuator. The SMC is based on a second-order\nmodel of the electric actuator, a direct current (DC) drive, where the current dynamics and the\ndynamics of the motor angular velocity are addressed. The error dynamics of the SMC are stabilized\nby a moving horizon MPC and a Kalman filter (KF) that estimates a lumped disturbance variable.\nIn the application under consideration, this lumped disturbance variable accounts for nonlinear\nfriction as well as model uncertainty. Simulation results point out the benefits regarding a reduction\nof chattering and a high control accuracy....
It is a challenge to design a satisfactory controller for a complex multivariable industrial\nsystem with minimal offsetting and a slow response. An internal model control method is proposed\nfor rank-deficient systems with a time delay based on a damped pseudo-inverse. An internal model\ncontrol was designed to obtain the desired dynamic characteristics of the system by transforming the\ntime-delay system into a system without a time delay, following the Pade approximation approach.\nBy introducing a damping factor, the internal model controller was designed based on a damped\npseudo-inverse, since the inverse matrix of the rank-deficient system does not exist. Furthermore,\na singular value decomposition was used to analyze the steady-state performance of the system.\nThe selection of the damping factor was also presented, and a micro m analysis was made to evaluate the stability of the system. To demonstrate the effectiveness of the proposed method, a crude distillation\nprocess with five inputs and four outputs was considered as an example. The simulation results\nillustrate that not only can the proposed strategy guarantee the systemâ??s stability, but it also has a\nrelatively good dynamic performance....
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