Safe and Efficient Switching Controller Design for Partially Observed Linear-Gaussian Systems

Switching control strategies that unite a potentially high-performance but uncertified controller and a stabilizing albeit conservative controller are shown to be able to balance safety with efficiency, but have been less studied under partial observation of state. To address this gap, we propose a switching control strategy for partially observed linear-Gaussian systems with provable performance guarantees. We show that the proposed switching strategy is both safe and efficient, in the sense that: (1) the linear-quadratic cost of the system is always bounded even if the original uncertified controller is destabilizing; (2) in the case when the uncertified controller is stabilizing, the performance loss induced by the conservativeness of switching converges super-exponentially to zero. The effectiveness of the switching strategy is also demonstrated via numerical simulation on the Tennessee Eastman Process

Optimal Economic Schedule for a Network of Microgrids With Hybrid Energy Storage System Using Distributed Model Predictive Control

Artículo Open Access en el sitio web el editor. Pago por publicar en abierto.In this paper, an optimal procedure for the economic schedule of a network of interconnected microgrids with hybrid energy storage system is carried out through a control algorithm based on distributed model predictive control (DMPC). The algorithm is specifically designed according to the criterion of improving the cost function of each microgrid acting as a single system through the network mode operation. The algorithm allows maximum economical benefit of the microgrids, minimizing the degradation causes of each storage system, and fulfilling the different system constraints. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled with the framework of mixed logic dynamic. The DMPC problem is solved with the use of mixed integer linear programming using a piecewise formulation, in order to linearize a mixed integer quadratic programming problem.Ministerio de Economía, Industria y Competitivadad DPI2016-78338-RComisión Europea 0076-AGERAR-6-

FCS-MPC-Based Current Control of a Five-Phase Induction Motor and its Comparison with PI-PWM Control

This paper presents an investigation of the finite-control-set model predictive control (FCS-MPC) of a five-phase induction motor drive. Specifically, performance with regard to different selections of inverter switching states is investigated. The motor is operated under rotor flux orientation, and both flux/torque producing (d-q) and nonflux/torque producing (x-y) currents are included into the quadratic cost function. The performance is evaluated on the basis of the primary plane, secondary plane, and phase (average) current ripples, across the full inverter's linear operating region under constant flux-torque operation. A secondary plane current ripple weighting factor is added in the cost function, and its impact on all the studied schemes is evaluated. Guidelines for the best switching state set and weighting factor selections are thus established. All the considerations are accompanied with both simulation and experimental results, which are further compared with the steady-state and transient performance of a proportional-integral pulsewidth modulation (PI-PWM)-based current control scheme. While a better transient performance is obtained with FCS-MPC, steady-state performance is always superior with PI-PWM control. It is argued that this is inevitable in multiphase drives in general, due to the existence of nonflux/torque producing current components. © 1982-2012 IEEE

Constrained stochastic LQ control with regime switching and application to portfolio selection

This paper is concerned with a stochastic linear-quadratic optimal control problem with regime switching, random coefficients, and cone control constraint. The randomness of the coefficients comes from two aspects: the Brownian motion and the Markov chain. Using It\^{o}'s lemma for Markov chain, we obtain the optimal state feedback control and optimal cost value explicitly via two new systems of extended stochastic Riccati equations (ESREs). We prove the existence and uniqueness of the two ESREs using tools including multidimensional comparison theorem, truncation function technique, log transformation and the John-Nirenberg inequality. These results are then applied to study mean-variance portfolio selection problems with and without short-selling prohibition with random parameters depending on both the Brownian motion and the Markov chain. Finally, the efficient portfolios and efficient frontiers are presented in closed forms

LQR CONTROL APPROACH APPLIED TO UNINTERRUPTIBLE POWER SUPPLY (UPS)

This paper presents a control strategy applied to high power uninterruptible power supplies with a low switching frequency. In the controller design, the gains are determined by minimizing a cost function, which reduces the tracking error and smoothes the control signal. A recursive least square estimator identifies the parameters model at different load conditions. Then the linear quadratic controller gains are adapted periodically. The output voltage is the only state variable measured.The other state variables are obtained by estimation process. Simulation results show that the proposed control strategy offers good performances for either linear and non-linear loads with low total harmonic distortions (THD) even at low frequencies making it very useful for high power applications

LQR CONTROL APPROACH APPLIED TO UNINTERRUPTIBLE POWER SUPPLY (UPS)

This paper presents a control strategy applied to high power uninterruptible power supplies with a low switching frequency. In the controller design, the gains are determined by minimizing a cost function, which reduces the tracking error and smoothes the control signal. A recursive least square estimator identifies the parameters model at different load conditions. Then the linear quadratic controller gains are adapted periodically. The output voltage is the only state variable measured.The other state variables are obtained by estimation process. Simulation results show that the proposed control strategy offers good performances for either linear and non-linear loads with low total harmonic distortions (THD) even at low frequencies making it very useful for high power applications.