Formal methods for resilient control

Many systems operate in uncertain, possibly adversarial environments, and their successful operation is contingent upon satisfying specific requirements, optimal performance, and ability to recover from unexpected situations. Examples are prevalent in many engineering disciplines such as transportation, robotics, energy, and biological systems. This thesis studies designing correct, resilient, and optimal controllers for discrete-time complex systems from elaborate, possibly vague, specifications. The first part of the contributions of this thesis is a framework for optimal control of non-deterministic hybrid systems from specifications described by signal temporal logic (STL), which can express a broad spectrum of interesting properties. The method is optimization-based and has several advantages over the existing techniques. When satisfying the specification is impossible, the degree of violation - characterized by STL quantitative semantics - is minimized. The computational limitations are discussed. The focus of second part is on specific types of systems and specifications for which controllers are synthesized efficiently. A class of monotone systems is introduced for which formal synthesis is scalable and almost complete. It is shown that hybrid macroscopic traffic models fall into this class. Novel techniques in modular verification and synthesis are employed for distributed optimal control, and their usefulness is shown for large-scale traffic management. Apart from monotone systems, a method is introduced for robust constrained control of networked linear systems with communication constraints. Case studies on longitudinal control of vehicular platoons are presented. The third part is about learning-based control with formal guarantees. Two approaches are studied. First, a formal perspective on adaptive control is provided in which the model is represented by a parametric transition system, and the specification is captured by an automaton. A correct-by-construction framework is developed such that the controller infers the actual parameters and plans accordingly for all possible future transitions and inferences. The second approach is based on hybrid model identification using input-output data. By assuming some limited knowledge of the range of system behaviors, theoretical performance guarantees are provided on implementing the controller designed for the identified model on the original unknown system

Adaptive optimal control design for stable vibration attenuation of active constrained layer damping beam structure

Vibration suppression using active constrained layer damping (ACLD) has proven to be an invaluable means for improving the performance of a wide variety of engineering systems. The ACLD creates the hybrid of active and passive damping, attaining favorably high damping characteristics, while at the same time, combines unattractive attributes of both treatments, such as stability sensitivity. Control efforts are needed to achieve an adequate performance of the structures treated with ACLD. The purpose of this research is to investigate theoretically and numerically the adaptive optimal controller of the constrained layer damped beam system, using the classical three-layered distributed-parameter model that utilizes Hamilton\u27s principle in the derivation. Particular emphasis is placed on controlling and stability analysis of the first bending mode of the response on the harmonic excitation using proportional control law. A new technique for prediction of optimal damping performance for fully treated beam/ACLD system using time-domain analysis of control is proposed. Comparison between analytical and numerical results, as well with experimental results found in the literature, showed that the proposed strategy is very simple and efficient in constructing the adaptive optimal control gains for amplitude attenuation of structural vibrations

State-space self-tuner for on-line adaptive control

Dynamic systems, such as flight vehicles, satellites and space stations, operating in real environments, constantly face parameter and/or structural variations owing to nonlinear behavior of actuators, failure of sensors, changes in operating conditions, disturbances acting on the system, etc. In the past three decades, adaptive control has been shown to be effective in dealing with dynamic systems in the presence of parameter uncertainties, structural perturbations, random disturbances and environmental variations. Among the existing adaptive control methodologies, the state-space self-tuning control methods, initially proposed by us, are shown to be effective in designing advanced adaptive controllers for multivariable systems. In our approaches, we have embedded the standard Kalman state-estimation algorithm into an online parameter estimation algorithm. Thus, the advanced state-feedback controllers can be easily established for digital adaptive control of continuous-time stochastic multivariable systems. A state-space self-tuner for a general multivariable stochastic system has been developed and successfully applied to the space station for on-line adaptive control. Also, a technique for multistage design of an optimal momentum management controller for the space station has been developed and reported in. Moreover, we have successfully developed various digital redesign techniques which can convert a continuous-time controller to an equivalent digital controller. As a result, the expensive and unreliable continuous-time controller can be implemented using low-cost and high performance microprocessors. Recently, we have developed a new hybrid state-space self tuner using a new dual-rate sampling scheme for on-line adaptive control of continuous-time uncertain systems

Optimization of adaptive filter control parameters for non-invasive fetal electrocardiogram extraction

This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters of different hybrid systems used for non-invasive fetal electrocardiogram (fECG) extraction. The tested hybrid systems consist of two different blocks, first for maternal component estimation and second, so-called adaptive block, for maternal component suppression by means of an adaptive algorithm (AA). Herein, we tested and optimized four different AAs: Adaptive Linear Neuron (ADALINE), Standard Least Mean Squares (LMS), Sign-Error LMS, Standard Recursive Least Squares (RLS), and Fast Transversal Filter (FTF). The main criterion for optimal parameter selection was the F1 parameter. We conducted experiments using real signals from publicly available databases and those acquired by our own measurements. Our optimization method enabled us to find the corresponding optimal settings for individual adaptive block of all tested hybrid systems which improves achieved results. These improvements in turn could lead to a more accurate fetal heart rate monitoring and detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to find optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing and analysis, opening new diagnostic possibilities of non-invasive fetal electrocardiography.Web of Science174art. no. e026680

Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference

User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the core of high rate data-oriented downlink schemes of the next-generation of cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users according to their channels vector directions and SINR levels. However, when scheduling is applied independently in each cell, the inter-cell interference (ICI) power at each user receiver is not known in advance since it changes at each new scheduling slot depending on the scheduling decisions of all interfering base stations. In order to cope with this uncertainty, we consider the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat reQuest (ARQ). We develop a game-theoretic framework for this problem and build on stochastic optimization techniques in order to find optimal scheduling and ARQ schemes. Particularizing our framework to the case of "outage service rates", we obtain a scheme based on adaptive variable-rate coding at the physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then, we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ) that is able to achieve a throughput performance arbitrarily close to the "genie-aided service rates", with no need for a genie that provides non-causally the ICI power levels. The novel HARQ scheme is both easier to implement and superior in performance with respect to the conventional combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small correction

Hybrid Systems of Soft Computing Technologies in Designing Team Decision for Supply Chain Management Systems of Organizations

Abstract—The main objective is development of hybrid systems for adaptive designing and supply chain management / strategizing of team decision “packages” for design work based on the use of soft computing technologies and system-creative thinking (SCT). An algorithm is proposed, and the results of case studies on predicting the effectiveness and optimal organization of team thinking, as well as designing team solutions using the technical package of social technologies are presented. They are exemplified by developing a system of products and marketing channels (points of contact) of an employer brand (EB) of an organization for individual stakeholder groups. An algorithm has been developed for using a system of hybrid “soft computing” technologies and system-creative thinking in supply chain process of project teamwork; practical calculations have been carried out using this algorithm. The algorithm and systems of models for using “soft computing” for supply chain developed allow us to obtain a synergistic effect from controlling a system of hybrid technologies at various stages of teamwork. The package includes a “basic” technology comprising “training teams”, and also the formation of a KPI system that characterize team work (units 1 and 2), “product” technologies comprising analysis of team organization thinking, forecasting team performance, team productivity management, as well as supply chain management of project (units 4, 5, 6), and also “closing” technology being a strategizing (adaptive management) of team work (dynamic control of the algorithm as a whole)

Огляд сучасних систем керування, які використовуються на безпілотних літальних апаратах

The aim of the work is to systematize the information on automatic control systems that are used on unmanned aerial vehicles for the selection and further use of combined control methods in the new automatic control system that can withstand unknown external disturbances with guaranteed accuracy.Adaptive, optimal and robust control systems are considered. Advantages and disadvantages of adaptive control systems with intelligent control, in particular, using the neural networks are investigated. The issues of eliminating drawbacks, inherent in this type of adaptive automatic control systems are considered. Hybrid control architecture is reviewed. The synthesis of optimal control systems is examined.Advantages and disadvantages of using optimal control systems in conditions of uncertain external disturbances are given in the paper. Robust automatic control systems with robust adaptation algorithms are considered. Using the game theory in automatic control systems is studied.Conclusions about the feasibility of using a set of adaptive, intelligent and robust control methods to create a control system with the guaranteed accuracy of observing the specified parameters in conditions of uncertain external perturbations are drawn.В статье проводится анализ существующих подходов к решению задачи выдерживания воздействий внешних возмущений системами автоматического управления беспилотными летательными аппаратами. Целью работы является систематизация информации о состоянии систем автоматического управления беспилотных летательных аппаратов. Рассматриваются нерешенные проблемы отрасли, в частности, проблема отсутствия системы автоматического управления гарантированной точности при неопределенных возмущениях.В статті проводиться аналіз існуючих підходів до вирішення задачі витримування впливів зовнішніх збурень системами автоматичного керування. Метою роботи є систематизація інформації про стан систем автоматичного керування безпілотними літальними апаратами. Розглядаються невирішені проблеми галузі, зокрема, проблема відсутності системи автоматичного керування гарантованої точності за умови невизначених збурень.

Огляд сучасних систем керування, які використовуються на безпілотних літальних апаратах

The aim of the work is to systematize the information on automatic control systems that are used on unmanned aerial vehicles for the selection and further use of combined control methods in the new automatic control system that can withstand unknown external disturbances with guaranteed accuracy.Adaptive, optimal and robust control systems are considered. Advantages and disadvantages of adaptive control systems with intelligent control, in particular, using the neural networks are investigated. The issues of eliminating drawbacks, inherent in this type of adaptive automatic control systems are considered. Hybrid control architecture is reviewed. The synthesis of optimal control systems is examined.Advantages and disadvantages of using optimal control systems in conditions of uncertain external disturbances are given in the paper. Robust automatic control systems with robust adaptation algorithms are considered. Using the game theory in automatic control systems is studied.Conclusions about the feasibility of using a set of adaptive, intelligent and robust control methods to create a control system with the guaranteed accuracy of observing the specified parameters in conditions of uncertain external perturbations are drawn.В статье проводится анализ существующих подходов к решению задачи выдерживания воздействий внешних возмущений системами автоматического управления беспилотными летательными аппаратами. Целью работы является систематизация информации о состоянии систем автоматического управления беспилотных летательных аппаратов. Рассматриваются нерешенные проблемы отрасли, в частности, проблема отсутствия системы автоматического управления гарантированной точности при неопределенных возмущениях.В статті проводиться аналіз існуючих підходів до вирішення задачі витримування впливів зовнішніх збурень системами автоматичного керування. Метою роботи є систематизація інформації про стан систем автоматичного керування безпілотними літальними апаратами. Розглядаються невирішені проблеми галузі, зокрема, проблема відсутності системи автоматичного керування гарантованої точності за умови невизначених збурень.

Intelligent Energy Management in Residential Building

Residential building has high consumption of energy especially electrical energy. This motivates researchers to work on how to improve residential building energy efficiency. However, the improvement of energy efficiency in a building is difficult to be done for the whole building at a time. Some of the difficulty is the inefficient of energy management system in the building, but the biggest contribution to the deficiency is that there is no optimal algorithm which is suitable to the facilities in the building. An intelligent energy management system has been proposed in this paper to address this problem which include the integrated optimal control system consists of an occupancy sensor network and adaptive dynamic programming algorithm. To increase accuracy and avoid faults in available sensor technology, multiple sensors are being used in this project including passive infra-red sensors, Ultrasonic sensors and Carbon Dioxide concentration sensors have been installed to set up a hybrid occupancy detection sensor network. It is very critical to control and optimization for complex systems such as the system constituted by all electromechanical systems in a building. It learns from environment of a building and generates a series of optimal control strategies to preserve human comfort and improve energy efficiency in low cost

Approximate Dynamic Programming for Constrained Piecewise Affine Systems with Stability and Safety Guarantees

Infinite-horizon optimal control of constrained piecewise affine (PWA) systems has been approximately addressed by hybrid model predictive control (MPC), which, however, has computational limitations, both in offline design and online implementation. In this paper, we consider an alternative approach based on approximate dynamic programming (ADP), an important class of methods in reinforcement learning. We accommodate non-convex union-of-polyhedra state constraints and linear input constraints into ADP by designing PWA penalty functions. PWA function approximation is used, which allows for a mixed-integer encoding to implement ADP. The main advantage of the proposed ADP method is its online computational efficiency. Particularly, we propose two control policies, which lead to solving a smaller-scale mixed-integer linear program than conventional hybrid MPC, or a single convex quadratic program, depending on whether the policy is implicitly determined online or explicitly computed offline. We characterize the stability and safety properties of the closed-loop systems, as well as the sub-optimality of the proposed policies, by quantifying the approximation errors of value functions and policies. We also develop an offline mixed-integer linear programming-based method to certify the reliability of the proposed method. Simulation results on an inverted pendulum with elastic walls and on an adaptive cruise control problem validate the control performance in terms of constraint satisfaction and CPU time