There is a group of transmitter RFFE architectures whose signal output is constructed from two, or more, efficiently generated components. This signal construction in effect, means that such architectures use predictive, post-correction linearization. Their predictive nature enables distortion to be (in theory) completely eliminated, irrespective of the non-linear properties of the individual s...

Abstract: We propose the stabilization of nonlinear systems with singularities via switching piecewise bilinear (PB) control. The approximated model is fully parametric. Input-output (I/O) feedback linearization is applied to stabilize PB control systems. We construct piecewise Lyapunov-like function for each piecewise region and stabilize the state space using a hybrid control method. Examples...

The control system for a Doubly Fed Induction Generator (DFIG) supplied by grid-connected Current Source Converter (CSC) is presented in this paper. Nonlinear transformation of DFIG model to the multi-scalar form proposed. nonlinear strategy active and reactive power realized feedback linearization. In proposed scheme, CSI parameters are included. Two Proportional-Integral (PI) controllers dedi...

In this paper, an Output Feedback Model Predictive Control for nonlinear systems is presented. The proposed output feedback control consists of the well known robust controller NCGPC (Nonlinear Continuous Time Generalized Predictive Control) and an open loop observer (a simulated model in parallel) in order to estimate the output derivatives and a regulation filter used to account for plant/mod...

Widespread adoption of higher order modulation schemes, larger signal bandwidths and higher operating frequencies, to enable higher data throughput in communication links like 5G, places increasingly tough demands on the frontend. Signal fidelity is often enhanced with linearization. The greater number of RF chains and signal bandwidth in 5G Frontends mean that DPD (Digital PreDistortion) may n...

We propose a formulation for approximate constrained nonlinear output-feedback stochastic model predictive control. Starting from the ideal but intractable optimal control problem (OCP), which involves optimization over output-dependent policies, we use linearization with respect to uncertainty derive tractable approximation includes knowledge of output model. This allows us compute expected va...