Data-Driven Inversion-Based Control (D-IBC) is a recently introduced control design method for uncertain nonlinear systems, relying on a two degree-of-freedom architecture, with a nonlinear controller and a linear controller running in parallel. In this paper, extending to the MIMO case a previous result holding for the SISO case, we derive a finite-gain stability sufficient condition for a clo...

This paper presents nonlinear model following control for a class of nonlinear systems using the fuzzy model-based control approach. We propose the construction method of augmented fuzzy control system for continuous-time nonlinear systems by differentiating the original nonlinear system. Moreover, we introduce the dynamic fuzzy controller which can make outputs of the nonlinear system converge...

An enhanced nonlinear PID (EN-PID) controller that exhibits the improved performance than the conventional linear fixed-gain PID controller is proposed in this paper, by incorporating a sector-bounded nonlinear gain in cascade with a conventional PID control architecture. To achieve the high robustness against noise, two nonlinear tracking differentiators are used to select high-quality differe...

in this paper, an intelligent controller is applied to control omni-directional robots motion. first, the dynamics of the three wheel robots, as a nonlinear plant with considerable uncertainties, is identified using an efficient algorithm of training, named lolimot. then, an intelligent controller based on brain emotional learning algorithm is applied to the identified model. this emotional lea...

In this paper a generic functional approximator in the form of a neural network is enabled as a generic nonlinear controller. This means such a nonlinear feedforward path controller structure can be used for any plants, in a similar way to a conventional linear controller. An evolutionary learning mechanism for training such controllers directly from open-loop plant response data is also presen...

In this paper, adaptive control of a class of nonlinear discrete time dynamical systems with boundedness of all signals is established by using a linear robust adaptive controller and a neural network based nonlinear adaptive controller, and switching between them by a suitably defined switching law. The linear controller, when used alone, assures boundedness of all the signals but not satisfac...

A nonlinear predictive controller is presented in the paper. The greatest advantage of predictive functional control (PFC) is very fast and easy calculation of control variable. Combined with the Takagi-Sugeno (TS) fuzzy model, the PFC becomes nonlinear and is called fuzzy PFC (FPFC). The controller was evaluated by simulation on the well-known process, the continuous stirred-tank reactor (CSTR...

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is sho...

Series connected DC motor is a common nonlinear device mostly used in rated values since its nonlinear modeling makes difficult the efficient velocity control. Local and approximate controllers have been previously applied. In this paper a global nonlinear controller is proposed based on port controlled Hamiltonian systems equivalence, i.e. a suitably defined feedback controller results the ove...

In this paper, a two-surfaces sliding mode controller (TSSMC) is proposed for the voltage tracking control of a two input DC-DC converter in application of electric vehicles (EVs). The imperialist competitive algorithm (ICA) is used for tuning TSSMC parameters. The proposed controller significantly improves the transient response and disturbance rejection of the two input converters while p...