Hybrid Control System Research Articles

A New Numerical Method for Optimal Control of a Class of Hybrid Systems

Optimal control of uncertain hybrid systems is a major concern in control engineering. For optimal control of hybrid systems, there are a variety of direct methods, including parametric control and state-based parametric control. A reason that indirect methods are less used for optimal control of hybrid systems is difficulty in working with it and its primary valuing. The present study develops a new numerical method for optimal control of hybrid systems which decreases special restrictions of optimal control functions of hybrid systems per provided solution by a Bellman inequality. The obtained results show that an optimal control problem can be easily solved by converting it to an optimization problem. In addition, the used method obtained more accurate numerical value of the performance index. The results showed that the proposed method leads to greater convergence of the algorithm used in optimal control problems. The efficiency and performance of the proposed method was tested by an application example. Keywords: Bellman Inequality, Hybrid Systems, Optimal Control, Optimization Problems

A New Numerical Method for Optimal Control of a Class of Hybrid Systems

Optimal control of uncertain hybrid systems is a major concern in control engineering. For optimal control of hybrid systems, there are a variety of direct methods, including parametric control and state-based parametric control. A reason that indirect methods are less used for optimal control of hybrid systems is difficulty in working with it and its primary valuing. The present study develops a new numerical method for optimal control of hybrid systems which decreases special restrictions of optimal control functions of hybrid systems per provided solution by a Bellman inequality. The obtained results show that an optimal control problem can be easily solved by converting it to an optimization problem. In addition, the used method obtained more accurate numerical value of the performance index. The results showed that the proposed method leads to greater convergence of the algorithm used in optimal control problems. The efficiency and performance of the proposed method was tested by an application example.

Hybrid Systems Control Based on Smart Space Technology

The paper presents an approach to hybrid systems control based on smart space technology. The approach proposed bears two primary distinctive features: first, hybrid system control is decentralized and various control functions are implemented in separate services, communicating via ontology-based smart space; second, the services are represented by a hybrid automata formalism allowing to employ a model-driven development for hybrid control systems. The approach is illustrated by practical communication scenario of several physical devices in the context of smart home environment.

English

This paper presents the simplified control of hybrid system (wind -hydro) system connected to two back-to-back converters in which one is connected to hydro turbine and the other is connected to wind turbine system through squirrel cage induction generators (SCIG) feeding three phase four wire loads in isolated locations. The main objective of this work is to provide a better control algorithm for the VSC and to achieve maximum power tracking (M.P.T) through rotor speed control of the wind turbine driven S.C.I.G under varying speeds at the machine side and to control the magnitude and frequency of the voltage at load side. The system mainly ensures in sending the power generated by SCIGw is supplied to the load through the load-side converter and remaining power is stored in ESBS. And at the same time if the required active power of the load is more than the total power generated by SCIGw and SCIGh. Then the deficit power is supplied by the ESBS. Simulation models of the proposed hybrid system and the simulation results are obtained in MATLAB using Simulink and Sim Power System set toolboxes, with different load condition at different wind conditions

A Design of Position Closed-Loop Control System for Hybrid Stepping Motors Based on Mechanical-Sensorless Rotor Position Detection

In a stepping motor, the flux linkage with a phase winding is a function of rotor position and phase current. Employing inductance saliency to detect rotor position is suitable for hybrid stepping motor (HSM) for its saturation feature. This paper will introduce a position closed-loop control system for HSM with rotor position detection by monitoring chopping characteristics, and present simulation results based on Matlab/Simulink.

Monotone Numerical Schemes and Feedback Construction for Hybrid Control Systems

Hybrid systems are a general framework which can model a large class of control systems arising whenever a set of continuous and discrete dynamics are mixed in a single system. In this paper, we study the convergence of monotone numerical approximations of value functions associated to control problems governed by hybrid systems. We discuss also the feedback reconstruction and derive a convergence result for the approximate feedback control law. Some numerical examples are given to show the robustness of the monotone approximation schemes.

Control of Seismic Response of a Building Frame by Using Hybrid System with Magnetorheological Dampers and Isolators

The traditional isolation approach can suppress the seismic responses of upper structure and at the same time induce substantial deformation of isolation layer. Excessive base drift may cause the degradation and even the damage of the isolation system. Therefore, supplemental control devices can be implemented in the common base isolation system to construct hybrid control system and reduce the base drifts of structures. The seismic mitigation of a building frame with hybrid control system is carried out in this study. The mechanical model of magnetorheological (MR) damper is presented by involving the effects of brace stiffness of the damper. The equation of motion of a frame structure with stiffness eccentricity incorporated with intelligent hybrid control system disturbed by seismic excitations is established by considering the effects of both isolators and MR dampers. A clipped-optimal strategy based on fuzzy control principle is proposed for MR dampers. A building frame is taken as the example to examine the feasibility and reliability of the proposed intelligent control approach. The efficacy of the hybrid control approach is compared with the base isolation approach. An extensive parametric study is carried out to find the optimal parameters of MR dampers, by which the maximum reduction of seismic responses may be achieved, and to assess the effects of earthquake intensity and brace stiffness on damper performance. The work on example buildings showed that the installation of the smart dampers with proper parameters and proper control strategy could significantly reduce seismic responses of structures, and the performance of the smart damper is better than that of the common base isolation system. The optimal parameters of the MR dampers could be identified through a parametric study.

Modeling, Analysis and Synthesis of Hybrid System: A Review

This paper proposes a framework of modeling, analyzing, and controlling systems represented by interdependent physical laws, logic rules, and operating constraints, denoted as hybrid system. Based on the basic concept and characteristics of hybrid system, we classify the conventional models including hybrid automaton, hybrid Petri nets, mixed logic dynamics, et al. We introduce the method of stability analysis, and point out the main difficulties in optimization and control of hybrid systems. Finally, the further research directions are prospected.

Embedded optimization for mixed logical dynamical systems

Predictive control of hybrid systems is currently considered prohibitive using embedded computing platforms. To overcome this limitation for mixed logical dynamical systems of small to medium size, we propose to use (1) a standard branch-and-bound approach combined with a fast embedded interior point solver, (2) pre-processing heuristics, run once and offline, to significantly reduce the number of subproblems to be solved, and (3) relaxations of the original MPC problem that allow a trade off between computation time and closed-loop performance. A problem-specific ANSI C implementation of the proposed method can be automatically generated, and has a fixed memory footprint and a code size that is insignificantly larger than that of the subproblem solver. Two extensive numerical studies are presented, where problems with up to 60 binary variables are solved in less than 0.2s with a performance deterioration of below 2% when compared to an optimal MPC scheme.

Stabilizing the unstable periodic orbits of a hybrid chaotic system using optimal control

In this paper, we are interested in the control of a chaotic hybrid system with an application to Chua’s system. It is known that chaotic attractors contain an infinite number of unstable periodic orbits (UPO) with different lengths, our idea consists in stabilizing a predetermined orbit of a given length by using an optimal control method. Our approach is to determine the switching instants from one subsystem to the other while minimizing the difference between two successive orbits. Should the switchings be state dependent, as is the case for the well known Chua’s circuit, then our approach consists in perturbing the switching boundaries such that the system trajectory hits those boundaries at the specified instants. Numerical simulations illustrating the efficiency of the proposed method are presented.

Optimal control of partitioned hybrid systems via discrete-time Hamilton–Jacobi theory

Computational framework for optimal control of hybrid systems with a partitioned state space is presented. It is shown that necessary conditions for optimality for a discrete-time dynamic system can be solved concurrently for various boundary conditions, according to the recent development of discrete-time Hamilton–Jacobi theory. This unique property is utilized to construct computationally efficient numerical optimization of hybrid systems where discrete switching dynamics occurs at the boundary between partitions of the configuration space. A benchmark example shows that the proposed approach has substantial computational advantages compared with the existing ones.

Structural performance and cost analysis of wind-induced vibration control schemes for a real super-tall building

To evaluate different energy dissipation systems used to control wind-induced vibrations of a 456 m super-tall building in fluctuating wind excitations, the finite element (FE) method was employed to simulate the dynamic responses of the building. A series of wind tunnel pressure tests were conducted on a 1:450 scale model to determine the wind forces acting on the super-tall building. A FE model was also constructed and mass, damping and stiffness matrices were subsequently formulated as an evaluation model for numerical analysis. The evaluation model was further simplified to a state reduced-order system using the state order reduction method. Three different vibration control schemes, namely a tuned mass damper (TMD) system, a system containing only nonlinear viscous dampers and a hybrid control system combining TMD and viscous dampers, were examined through simulations with respect to their effectiveness in reducing the accelerations at the top of the building. Furthermore, a cost evaluation was conducted to determine the most economical structural design and vibration control scheme. The results show that the wind-induced vibrations of the analysed building can be controlled effectively by all the three examined schemes, while the hybrid control scheme and the scheme containing only viscous dampers further reduce the wind-induced vibration to satisfy a more stringent criterion for a six-star hotel. In addition, the hybrid vibration control scheme is also the most cost-effective among the examined schemes.

A dynamic programming based approach for explicit model predictive control of hybrid systems

This work presents an algorithm for explicit model predictive control of hybrid systems based on recent developments in constrained dynamic programming and multi-parametric programming. By using the proposed approach, suitable for problems with linear cost function, the original model predictive control formulation is disassembled into a set of smaller problems, which can be efficiently solved using multi-parametric mixed-integer programming algorithms. It is also shown how the methodology is applied in the context of explicit robust model predictive control of hybrid systems, where model uncertainty is taken into account. The proposed developments are demonstrated through a numerical example where the methodology is applied to the optimal control of a piece-wise affine system with linear cost function.

Synthesis of modulated–demodulated control systems

We propose systematic design methods for realization of a given LTI compensator with complex poles using a modulated–demodulated control framework. Applicability of the proposed realization methods is established through simulations performed on an undamped resonant plant compensated by a low gain controller to obtain better noise rejection performance. It is demonstrated how a modulated–demodulated structure may reduce the sampling rate in a hybrid control system. In addition, superior robust performance is achieved against variations in baseband parameters using direct reference injection into the modulated–demodulated control systems compared to the indirect injection approach.

Modelling and Simulation of Suborbital Launcher for Testing

The purpose of this paper is to present some aspects regarding the computational model and technical solutions for multistage suborbital launcher for testing (SLT) used to test spatial equipment and scientific measurements. The computational model consists in numerical simulation of SLT evolution for different start conditions. The launcher model presented will be with six degrees of freedom (6DOF) and variable mass. The results analysed will be the flight parameters and ballistic performances. The discussions area will focus around the technical possibility to realize a small multi-stage launcher, by recycling military rocket motors. From technical point of view, the paper is focused on national project “Suborbital Launcher for Testing” (SLT), which is based on hybrid propulsion and control systems, obtained through an original design. Therefore, while classical suborbital sounding rockets are unguided and they use as propulsion solid fuel motor having an uncontrolled ballistic flight, SLT project is introducing a different approach, by proposing the creation of a guided suborbital launcher, which is basically a satellite launcher at a smaller scale, containing its main subsystems. This is why the project itself can be considered an intermediary step in the development of a wider range of launching systems based on hybrid propulsion technology, which may have a major impact in the future European launchers programs. SLT project, as it is shown in the title, has two major objectives: first, a short term objective, which consists in obtaining a suborbital launching system which will be able to go into service in a predictable period of time, and a long term objective that consists in the development and testing of some unconventional sub-systems which will be integrated later in the satellite launcher as a part of the European space program. This is why the technical content of the project must be carried out beyond the range of the existing suborbital vehicle programs towards the current technological necessities in the space field, especially the European one.

Analysis and synthesis of linear hybrid systems with state-triggered jumps

This paper investigates first the stability and L2-gain problems for a class of linear hybrid control systems with state-triggered jumps by using an extended Lyapunov-like function (ELF) technique. The obtained results are then applied to facilitate the joint design of a hybrid controller (linear controller plus reset law) for a continuous-time linear time-invariant (LTI) plant. The hybrid H∞ synthesis conditions are expressed in linear matrix inequalities (LMIs) with two line search parameters. An inverted pendulum example is used to illustrate the effectiveness of the proposed approach.

Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

Efficient Computation of Separation-Compliant Speed Advisories for Air Traffic Arriving in Terminal Airspace

A class of problems in air traffic management (ATM) asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs (MIPs), hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the fully routed nominal problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively piecewise linear with finitely many vertices, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.

ANFIS-Based Control of a Grid-Connected Hybrid System Integrating Renewable Energies, Hydrogen and Batteries

This paper describes and evaluates an adaptive neuro-fuzzy inference system (ANFIS)-based energy management system (EMS) of a grid-connected hybrid system. It presents a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and an energy storage system (ESS) based on hydrogen (fuel cell -FC-, hydrogen tank and electrolyzer) and battery. All of the energy sources use dc/dc power converters in order to connect them to a central DC bus. An ANFIS-based supervisory control system determines the power that must be generated by/stored in the hydrogen and battery, taking into account the power demanded by the grid, the available power, the hydrogen tank level and the state-of-charge (SOC) of the battery. Furthermore, an ANFIS-based control is applied to the three-phase inverter, which connects the hybrid system to grid. Otherwise, this new EMS is compared with a classical EMS composed of state-based supervisory control system based on states and inverter control system based on PI controllers. Dynamic simulations demonstrate the right performance of the ANFIS-based EMS for the hybrid system under study and the better performance with respect to the classical EMS.

Adaptive hybrid control system using a recurrent RBFN-based self-evolving fuzzy-neural-network for PMSM servo drives

In this paper, an adaptive hybrid control system (AHCS) based on the computed torque control for permanent-magnet synchronous motor (PMSM) servo drive is proposed. The proposed AHCS incorporating an auxiliary controller based on the sliding-mode, a recurrent radial basis function network (RBFN)-based self-evolving fuzzy-neural-network (RRSEFNN) controller and a robust controller. The RRSEFNN combines the merits of the self-evolving fuzzy-neural-network, recurrent-neural-network and RBFN. Moreover, it performs the structure and parameter-learning concurrently. Furthermore, to relax the requirement of the lumped uncertainty, an adaptive RRSEFNN uncertainty estimator is used to adaptively estimate the non-linear uncertainties online, yielding a controller that tolerate a wider range of uncertainties. Additionally, a robust controller is proposed to confront the uncertainties including approximation error, optimal parameter vector and higher order term in Taylor series. The online adaptive control laws are derived based on the Lyapunov stability analysis, so that the stability of the AHCS can be guaranteed. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed AHCS. All control algorithms are implemented in a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the AHCS grants robust performance and precise dynamic response regardless of load disturbances and PMSM uncertainties.