Decentralized reliable control for large-scale LTI systems

Reliable control concerns the ability of closed loop system to maintain stability and regulation properties during arbitrary sensor, controller, and actuator failure. Reliable control research has been an active research topic for more than 10 years. Recent approach for reliable control includes the H∞ method, the algebraic factorization design, and the robust servomechanism control. These methods have been surveyed and discussed in this thesis with the robust servomechanism control methodology serving as the basis of the research development of this work. In this thesis, the reliable control for large-scale, multi-input/output linear system is considered. Two concepts of reliable control are introduced in this work: (1) Decentralized Robust Servomechanism Problem with Complete Reliability (DRSPwCR) and (2) Block Decentralized Robust Servo Problem with Complete Reliability (BDRSPwCR). The DRSPwCR solves the reliable control problem by applying strict diagonal decentralized controller configurations. The BDRSPwCR solves the reliable control problem by applying block diagonal decentralized controller configurations. Research results of solving DRSPwCR for the class of minimum phase systems is first developed in this work. The problem is solved by applying strict decentralized PIDr control to an otherwise unreliable plant and thus significantly extending the class of processes that can be controlled reliably. Research results of solving BDRSPwCR is developed for plants which have a pre-imposed block diagonal structure or plants with non-minimum phase minors. The reliable control conditions for an arbitrary linear system is then analyzed, and a general controller synthesis for solving the reliable control problem for arbitrary linear system is given in this work. The DRSPwCR can be applied in many industry areas as well as in the transportation area. In this work, the reliable control results are applied in the urban vehicle traffic network. A traffic queue length model is developed, a control algorithm is synthesized, and simulations are made under different traffic subsystem failure modes such as non-functioning traffic lights, traffic accidents, and intersection blockage, etc. Finally, future research topics such as to relax the constraints of plants to achieve reliable control and to optimize the closed loop system dynamic performances, etc. are proposed

Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation

The influence of the DC infrastructure on the control of power-storage flow in micro- and smart grids has gained attention recently, particularly in dynamic vehicle-to-grid charging applications. Principal effects include the potential loss of the charge–discharge synchronization and the subsequent impact on the control stabilization, the increased degradation in batteries’ health/life, and resultant power- and energy-efficiency losses. This paper proposes and tests a candidate solution to compensate for the infrastructure effects in a DC microgrid with a varying number of heterogeneous battery storage systems in the context of a multiagent neighbor-to-neighbor control scheme. Specifically, the scheme regulates the balance of the batteries’ load-demand participation, with adaptive compensation for unknown and/or time-varying DC infrastructure influences. Simulation and hardware-in-the-loop studies in realistic conditions demonstrate the improved precision of the charge–discharge synchronization and the enhanced balance of the output voltage under 24 h excessively continuous variations in the load demand. In addition, immediate real-time compensation for the DC infrastructure influence can be attained with no need for initial estimates of key unknown parameters. The results provide both the validation and verification of the proposals under real operational conditions and expectations, including the dynamic switching of the heterogeneous batteries’ connection (plug-and-play) and the variable infrastructure influences of different dynamically switched branches. Key observed metrics include an average reduced convergence time (0.66–13.366%), enhanced output-voltage balance (2.637–3.24%), power-consumption reduction (3.569–4.93%), and power-flow-balance enhancement (2.755–6.468%), which can be achieved for the proposed scheme over a baseline for the experiments in question.</p

Voltage stabilization in DC microgrids: an approach based on line-independent plug-and-play controllers

We consider the problem of stabilizing voltages in DC microGrids (mGs) given by the interconnection of Distributed Generation Units (DGUs), power lines and loads. We propose a decentralized control architecture where the primary controller of each DGU can be designed in a Plug-and-Play (PnP) fashion, allowing the seamless addition of new DGUs. Differently from several other approaches to primary control, local design is independent of the parameters of power lines. Moreover, differently from the PnP control scheme in [1], the plug-in of a DGU does not require to update controllers of neighboring DGUs. Local control design is cast into a Linear Matrix Inequality (LMI) problem that, if unfeasible, allows one to deny plug-in requests that might be dangerous for mG stability. The proof of closed-loop stability of voltages exploits structured Lyapunov functions, the LaSalle invariance theorem and properties of graph Laplacians. Theoretical results are backed up by simulations in PSCAD

Fiscal Responsibility Framework: International Experience and Implications for Hungary

In an effort to correct worrisome trends in discretionary fiscal policy (deficit bias, procyclicality, and structural distortions), an increasing number of countries introduced a rules-based fiscal responsibility framework (FRF), characterized by fiscal policy rules, procedural rules, transparency standards, and a surveillance and enforcement mechanism. Preliminary evidence suggests that compliance with a well-designed FRF contributes to building policy credibility, to reducing risk premia, to boosting economic growth, and to lowering output volatility. Faced with large and persistent fiscal imbalances and a sharp buildup of public indebtedness, Hungary would benefit from exploring the adoption a FRF along the following lines. The FRF should encompass the entire public sector, fully accounting for contingent liabilities, and including prudent fiscal projections. Second, it is necessary to strengthen procedural rules, including implementation of the pay-go approach to budget legislation and preparat on of a rolling three-year budget program, setting annual limits on the nominal level of primary expenditures. Third, phasing in of a primary surplus rule, calibrated to the path of desired debt reduction, should be seriously considered. Fourth, a current balance rule should be adopted for local self-governments. Finally, compliance with the FRF would need to be monitored by an independent authority.public finances, macroeconomics.

Two-channel decentralized integral action controller design

Cataloged from PDF version of article.We propose a systematic controller design method that provides integral-action in linear time-invariant two-channel decentralized control systems. Each channel of the plant is single-input–single-output, with any number of poles at the origin but no other poles in the instability region. An explicit parametrization of all decentralized stabilizing controllers incorporating the integral-action requirement is provided for this special case of plants. The main result is a design methodology that constructs simple low-order controllers in the cascaded form of proportional-integral and first-order blocks

Gather-and-broadcast frequency control in power systems

We propose a novel frequency control approach in between centralized and distributed architectures, that is a continuous-time feedback control version of the dual decomposition optimization method. Specifically, a convex combination of the frequency measurements is centrally aggregated, followed by an integral control and a broadcast signal, which is then optimally allocated at local generation units. We show that our gather-and-broadcast control architecture comprises many previously proposed strategies as special cases. We prove local asymptotic stability of the closed-loop equilibria of the considered power system model, which is a nonlinear differential-algebraic system that includes traditional generators, frequency-responsive devices, as well as passive loads, where the sources are already equipped with primary droop control. Our feedback control is designed such that the closed-loop equilibria of the power system solve the optimal economic dispatch problem

Distributed predictive control of the 7-Machine CIGRÉ power system

Stable operation of the future electrical power system will require efficient techniques for supply-demand balancing, i.e., load-frequency control, due to liberalization of electrical energy production. Currently, there is a growing interest for asymptotically stabilizing the grid frequency via model predictive control (MPC). However, the centralized implementation of standard MPC is hampered by the scale and complexity of power networks. In this paper we therefore evaluate the suitability of a scalable, distributed Lyapunovbased MPC algorithm as an alternative to conventional balancing techniques. The approach is particularly suited for largescale power networks, as it employs only local information and limited communication between directly-coupled generator buses to provide a stabilizing control action. The effectiveness of the distributed control scheme is assessed by simulating it in closed-loop with the 7-machine CIGRE benchmark system

Characterization of Information Channels for Asymptotic Mean Stationarity and Stochastic Stability of Non-stationary/Unstable Linear Systems

Stabilization of non-stationary linear systems over noisy communication channels is considered. Stochastically stable sources, and unstable but noise-free or bounded-noise systems have been extensively studied in information theory and control theory literature since 1970s, with a renewed interest in the past decade. There have also been studies on non-causal and causal coding of unstable/non-stationary linear Gaussian sources. In this paper, tight necessary and sufficient conditions for stochastic stabilizability of unstable (non-stationary) possibly multi-dimensional linear systems driven by Gaussian noise over discrete channels (possibly with memory and feedback) are presented. Stochastic stability notions include recurrence, asymptotic mean stationarity and sample path ergodicity, and the existence of finite second moments. Our constructive proof uses random-time state-dependent stochastic drift criteria for stabilization of Markov chains. For asymptotic mean stationarity (and thus sample path ergodicity), it is sufficient that the capacity of a channel is (strictly) greater than the sum of the logarithms of the unstable pole magnitudes for memoryless channels and a class of channels with memory. This condition is also necessary under a mild technical condition. Sufficient conditions for the existence of finite average second moments for such systems driven by unbounded noise are provided.Comment: To appear in IEEE Transactions on Information Theor