This paper presents a practical study on how to improve the ℋ∞ performance and meet input–output constraints of two-degrees-of-freedom (DOF) flexible-joint manipulator system (FJMS) with parameter uncertainties external disturbances. For this reason, robust constrained moving-horizon controller is designed while still satisfying uncertain system. First, controlled model two-DOF FJMS established...

In this paper, we propose an efficient zero-order algorithm that can be used to compute approximate solution robust optimal control problems (OCP) and robustified nonconvex programs in general. particular, focus on OCPs make use of ellipsoidal uncertainty sets show that, with the proposed method, efficiently obtain suboptimal, but robustly feasible solutions. The main idea lies leveraging inexa...

Control systems with digital communication between sensors, controllers and actuators are called as Networked Control Systems (NCSs). In general, NCSs encounter with some problems such as packet dropouts and network induced delays. When plant uncertainty is added to the aforementioned problems, the design of the robust controller that is able to guarantee the stability, becomes more complex. In...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

The continuous stirred-tank reactor with uncertain parameters was stabilized in the open-loop unstable steady state using the robust model predictive control. The gain matrices of the robust state-feedback controller were designed using the nominal system optimization and the quadratic parameter-dependent Lyapunov functions. The controller was verifi ed by simulations using the non-linear model...