Abstract: Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.
Abstract: This paper proposes a new technique to design a
fixed-structure robust loop shaping controller for the pneumatic
servosystem. In this paper, a new method based on a particle swarm
optimization (PSO) algorithm for tuning the weighting function
parameters to design an H∞ controller is presented. The PSO
algorithm is used to minimize the infinity norm of the transfer
function of the nominal closed loop system to obtain the optimal
parameters of the weighting functions. The optimal stability margin is
used as an objective in PSO for selecting the optimal weighting
parameters; it is shown that the proposed method can simplify the
design procedure of H∞ control to obtain optimal robust controller for
pneumatic servosystem. In addition, the order of the proposed
controller is much lower than that of the conventional robust loop
shaping controller, making it easy to implement in practical works.
Also two-degree-of-freedom (2DOF) control design procedure is
proposed to improve tracking performance in the face of noise and
disturbance. Result of simulations demonstrates the advantages of the
proposed controller in terms of simple structure and robustness
against plant perturbations and disturbances.
Abstract: This paper examines the problem of designing a robust H∞ filter for a class of uncertain fuzzy descriptor systems described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain nonlinear descriptor systems to have an H∞ performance are derived. To alleviate the ill-conditioning resulting from the interaction of slow and fast dynamic modes, solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation ε, when ε is sufficiently small. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard uncertain nonlinear descriptor systems. A numerical example is provided to illustrate the design developed in this paper.
Abstract: In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.
Abstract: In this paper a systematic method via H∞ control
design is proposed to select a sensor set that satisfies a number
of input criteria for a MAGLEV suspension system. The proposed
method recovers a number of optimised controllers for each possible
sensor set that satisfies the performance and constraint criteria using
evolutionary algorithms.
Abstract: In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.