State feedback predictive control for nonlinear hydro-turbine governing system

Abstract

The present work introduces a novel predictive control strategy for the analysis of the dynamic performance of hydro-turbine governing systems based on fuzzy logic. Firstly, a six-dimensional non-linear dynamic model of the system is defined. The defined model is applied to a realistic case-study, aiming to investigate the dynamic behavior of the system. In order to deal effectively with the non-linearity of the system under study, the T-S fuzzy approach is adopted. The results demonstrated through the use of the discrete Lyapunov function and Schur complements of matrices suggest that the closed-cycle control system can achieve a global asymptotic stability state. The second part focuses on the quantification of the impact of sudden changes in operating conditions on the overall performance. The numerical results indicate that proposed predictive control method can ensure the performance of the system to be reliable and robust to external inferences. In addition to this, the approach proposed has unquestionable advantages over the traditional PID and model predictive controllers with regard to non-linear systems applications.

Optimal Allocation of Inverter-Based WTGS Complying With Their DSTATCOM Functionality and PEV Requirements

“…3 which was determined based on (16). The initial SOC of every PEV can be calculated using (17)- (19).…”

“…A multi-objective probabilistic framework for planning WTGS and other RES types has been proposed in [18] for reducing costs and emissions whereas an augmented ϵ-constraint equipped with fuzzy roles have been utilized. In [19]- [21], a hydro-turbine governing system with actuator failures and disturbance have been investigated. Driven by the recent innovations in metaheuristic based optimizers, several variants This work is licensed under a Creative Commons Attribution 4.0 License.…”

Non‐linear model predictive control for visual servoing systems incorporating iterative linear quadratic Gaussian

“…Under this circumstance, non‐linear MPC (NMPC) is just suitable to deal with this problem. In [14], a state feedback predictive control was investigated for six‐dimensional non‐linear hydro‐turbine governing system. In [15], a distributed MPC approach was proposed to complete the formation control for multiple mobile robots with external disturbance and synchronisation constraints.…”

Nonlinear optimal control for synchronization of distributed hydropower generators

“…For instance, there is need to synchronize the individual hydropower generation units which are excited by the same water reserves stored in a dam and flow through different penstocks, or alternatively to synchronize hydropower generation units which are sequentially excited by the flow of the water of the same river going through successive dams. Hydro-power plants stand currently for the major source of renewable energy produced worldwide (Xu et al, 2018; Yi et al, 2017; Zhang et al, 2017) . Reliable functioning of distributed hydro-power units can be achieved through elaborated control methods (Camara et al, 2009; Jin et al, 2005; Zeng, 2013).…”