نامعینی پارامتری

This paper presents a novel scheme for robust controller design for teleoperation system; there are parametric uncertainties in nonlinear model and varying time-delay in the communication channel, and robots are in contact with non-passive human operator and environment. First, the structure of nonlinear control law is designed for nominal system utilizing the Passivity Based Control (PBC) scheme. Then, using the Lyapunov-Krasovskii (LK) theorem, sufficient conditions are derived for robust asymptotic stability of system in terms of matrix inequalities to tune controller parameters. Also, by definition of an appropriate performance criterion, controller parameters are obtained to minimize the position tracking errors besides guaranteed robust stability. The contributions of the proposed method are twofold. First, the developed controller is fixed-structure which can be implemented easily in practice. Second, the asymptotic stability of system is assured without any requirement for existence of passive part in the dynamical model of non-passive interaction forces. Simulation results of 3-dof teleoperation system are compared to a rival method to demonstrate the advantages of the suggested method.

Spherical robots are the mobile robots with spherical shape equipped to internal drive mechanism that move on the ground due to their external shell rolling. In this research, after modeling of a pendulum type of the spherical robots, dynamic analysis of their model during planar motion on an inclined surface is performed. The motion equations of spherical robot are derived using Lagrange method. Also, a nonlinear controller based on feedback linearization methods is designed. In the following, considering non-confirm initial conditions on trajectory, parametric uncertainty and also disturbance torque on robot, the motion of robot is simulated. The results indicate that the designed controller has proper and resistant performance in tracking selected trajectory for sphere shell rotation during moving on specified inclined surface.

Industrial arms must be able to perform their tasks in environments with serious unplanned conditions and perturbations. In this paper, the aim is to control a robotic manipulator which is under parametric uncertainty and significant external perturbations. Fuzzy type 2 logic is considered as an appropriate choice in the face of uncertain conditions due to various reasons such as the use of fuzzy membership functions and footprint of uncertainty existence in the algorithm. The use of neural network can increase the robustness of controller in the face of uncertainties. Although the neural network does not necessarily need to build its fuzzy type 2 rules, the initial rules based on sliding surface of sliding mode scheme can improve system’s performance. More robustness of the novel algorithm in comparison with classic sliding mode controller is the main feature made in the presence of parametric uncertainty and external perturbations. In addition, the controller self-regulation feature, based on the existence of neural network in the central block of fuzzy type 2 controller, helps to increase the robustness of the method. Positive performance of novel scheme has been shown in simulation of two-link robotic arm with different significant perturbations.

Spherical robots are the mobile robots with spherical shapes equipped to an internal drive mechanism that moves on the ground due to their external shell rolling. In this research, first, a pendulum spherical robot is modeled, then using the Lagrange method, dynamic equations of plane motion of robot on the non-flat surface are derived. Considering the scarcity of the number of operators relative to the number of degrees of freedom of the spherical robot, designing of a non-linear controller is performed based on feedback linearization techniques. Therefore, regarding non-confirm initial conditions on the trajectory, parametric uncertainty and disturbance torque on the robot, the performance of the system has been investigated. By selecting the appropriate rotation trajectory, the robot motion is simulated in MATLAB software and in following the pendulum rotation angle and actuating torque are obtained. The results indicate that the designed controller has proper and resistant performance in tracking selected trajectory for sphere shell rotation during moving on a non-flat surface.

In this article, a robust model predictive control (RMPC) using linear matrix inequalities (LMIs) is proposed for vehicle suspension design with parameter uncertainties. Since, in vehicle suspension design, it is desired to improve ride comfort and road holding while satisfying suspension constraints such as suspension deflection and maximum of control input, model predictive control is proposed which is among the most common approaches in constrained optimization problems. On the other hand, to handle suspension constraints, linear matrix inequalities are utilized here. Stability of the designed suspension system is proved, if the proposed linear matrix inequalities are feasible. In addition, uncertain parameters in suspension system are inevitable. In this paper, model predictive control is extended to care for parameter uncertainties by proposing new LMIs. To evaluate the effectiveness of the proposed approach, the proposed control method is applied to quarter car suspension model with parameter uncertainty. Simulation results endorse that the designed controller shows a competitive robust performance while satisfying suspension constraints existing parameter uncertainties. Moreover, simulations with different road profiles, show that the proposed controller is independent from various road excitations.

In electromagnetic motors, increase in output torque leads to increase in rotor inertia. Various robotics applications, especially haptic interfaces, oblige convenient dynamic performances of electromagnetic motors which are strongly in turn influenced by the rotor’s inertia. In the present paper, a robust control method for a viscous hybrid actuator is developed which supplies a desired varying torque while maintaining a constant low inertia. This hybrid actuator includes two dc motors with the shafts coupled through a rotational damper using a viscous non-contact coupler. This coupling method is based on Eddy current to provide the required performances. The large far motor eliminates or reduces the inertial forces and external dynamics effects on the actuator. The small near motor provides the desired output torque. Since the system is essentially linear, the applied robust control method is based on Hꝏ and parametric uncertainties and physical constraints including motors’ voltages saturation, rotary damper’s speed saturation, fastest user’s speed and acceleration applied to the actuator and force sensor noise are considered in its design. Also the robust method of µ-synthesis for the system in presence of parameteric uncertainties and other physical constraints are studied. The implementation of the controller on a 1 dof haptic interface model validate the achievement of the desired performances.