Hybrid control system design using a fuzzy logic interface

A hybrid control system is proposed for regulating an unknown nonlinear plant. The interface between the continuous-state plant and the discrete-event supervisor is designed using a fuzzy logic approach. The fuzzy logic interface partitions the continuous-state space into a finite number of regions. In each region, the original unknown nonlinear plant is approximated by a fuzzy logic-based linear model, then state-feedback controllers are designed for each linear model. A high-level supervisor coordinates (mode switching) the set of closed-loop systems in a stable and safe manner. The stability of the system is studied using nonsmooth Lyapunov functions. For illustration and verification purposes, this technique has been applied to the well-known inverted pendulum balancing problem.     

Practical Controller Design of Hybrid Experimental System for Seismic Tests

A hybrid experimental system is one of the powerful tools to perform various seismic tests for unknown and/or huge structures, where an actuator-excited experimental vibratory system and a computational response analysis are simultaneously combined and implemented. This paper presents a control methodology for high-performance hybrid experimental systems. A 2-DOF control framework is applied from the viewpoint of control techniques, where a feedback compensator is designed according to the system stabilization analysis, and a feedforward (FF) compensator is designed to achieve the desired servo characteristics. In the FF compensator design, an iterative learning control approach is particularly adopted to eliminate the response delays in the hydraulic actuator. The proposed compensation algorithm has been verified using a laboratory hybrid experimental set up with two-mass structure as a load mechanism.     

A bumpless hybrid supervisory control algorithm for the formation of unmanned helicopters

This paper presents a bumpless hybrid supervisory control scheme for the formation of unmanned helicopters. The approach is based on the polar partitioning of the space, from which a finite bisimilar quotient transition system of the original continuous variable control system is obtained. Then, to implement the designed hybrid supervisory control algorithm, a hierarchical control structure is introduced with a discrete supervisor on the top layer that is connected to the regulation layer via an interface layer. Transiting over the partitioned space may cause jumps on the generated control signal which is harmful for a real flight system. Hence, a smooth control mechanism is introduced that has no jump when the system’s trajectory transits from one region to its adjacent region while preserving the bisimulation relation between the abstract model and the original partitioned system. Several actual flight tests have been conducted to verify the algorithm and the control performance.     

锂电池组储能的混合动力RTG系统设计

锂电池组与柴油机构成的混合动力起重机系统是港口节能减排的一项重要技术。针对起重机再生制动能量的回收,设计了双向DC-DC变换器来实现锂电池组储能系统的两种工作模式(再生制动模式和锂电池组放电模式);对双向DC-DC变流器升压工作方式设计了双闭环控制器,降压工作方式设计了电流环和电压环两种控制器,并进行了对比,从而实现了对锂电池组储能系统充、放电过程和不同运行模式间切换过程的控制。运用PLECS搭建了系统仿真模型,仿真结果表明,在制动能量回收过程中,采用电压环控制器可以实现较高效率的制动能量回收。     

Utilizing online learning based on echo-state networks for the control of a hydraulic excavator

In this paper, we present a control framework for the control of a hydraulic excavator. An excavator can be viewed as a robotic manipulator that interacts with the environment. It follows that the control method employed to control the excavator must take into account the complex soil–tool interaction in order to achieve the desired trajectory of the manipulator. Impedance control has been proven to be effective in this aspect in that it provides an unified approach to constrained and unconstrained motion. Another important aspect when considering the automation of an excavator is the control of the hydraulic servo system. Obtaining a useful explicit model for the control of hydraulic servo systems is not a simple task due to their inherent complex nonlinearity. Therefore, control techniques that do not require an explicit representation of the plant are required. In this work, we integrate two controllers for the automation of an excavator. To control the rigid-body motion of the excavator, impedance control and sliding mode control are applied. The results are desired cylinder forces that are required to achieve the desired trajectory. Given the desired cylinder forces, an online learning control method is employed to control the hydraulic servo system so that the desired forces are generated. Echo-state networks, which are a class of recurrent neural networks, are utilized within the online learning control framework in order to learn an inverse model of the hydraulic servo system. Thus, the online learning control framework does not require an explicit model of the plant and also adapts to the plant using only the input and output signals. We present results of the proposed control framework on an excavator simulation environment that has been verified based on operation data from a real hydraulic excavator.     

基于BOM的光电信息控制仿真系统设计

介绍了BOM模板结构及其相互关系,采用BOM开发标准设计光电信息控制系统的层次化仿真框架和模型设计,阐述模型实现的基本方法,建立了基于BOM的HLA光电信息控制仿真系统,说明了光电信息控制仿真系统的开发步骤和实现过程。基于BOM标准构建的光电信息控制仿真系统可有效提高系统效率和模型重用性,为今后光电信息控制仿真系统的高效开发提供有利技术支持。     

Specification and analysis of power-managed systems

Dynamic power management encompasses several techniques for reducing energy dissipation in electronic systems by selective slowdown or shutdown of components. We present a theoretical framework for explaining and classifying different approaches to power management. Within this framework, we model power-manageable components, workloads, and controllers as discrete-event systems (DESs). The structure of these DESs is specified in terms of physical states (representing operation modes) and events (triggering state transitions), while system behavior is specified in terms of next-event and next-state functions. In particular, nondeterministic next-event and next-state functions are modeled by conditional probability distributions, according to generalized semi-Markov processes (GSMPs). The modeling framework provides a general denotational model for system specification and a rigorous execution semantics that enables event-driven simulation. We introduce a modeling framework, built on top of MathWork's Simulink, supporting the specification and execution of our model. In particular, we present templates for the Simulink simulator to execute GSMP models, and we describe how to use such templates for specifying, analyzing, and optimizing dynamic power-managed systems. Finally, we demonstrate the expressive power and versatility of the proposed approach by using the modeling framework and the simulator for the analysis of representative real-life case studies, including the Intel Xscale processor architecture, a multitasking real-time system, and a sensor network.     

Dynamic hybrid model of an electro-pneumatic clutch system

This paper deals with modelling an electro-pneumatic clutch system, which is used for medium- and heavy duty commercial vehicles. The mathematical model is built up for dynamic simulation, parameter estimation and control design/validation purposes, which is a phase of the design process of a new clutch system. These intended applications define the modelling goals and determine the modelling assumptions, which let one to reduce the model complexity. Since the model shows discrete–continuous behaviour, i.e. the model has hybrid properties, a nominal state domain or hybrid mode has been chosen for the sake of simplicity, where the model is continuous. In addition all the cases are given systematically, where the model has discrete transients. The model is constructed on the basis of the conservation principles such as mass, energy, momentum and magnetic linkage conservation and it is provided with constitutive equations to get a solvable set of equations. This final collection is then transformed into state space form for the given applications above. The verification of the developed model is carried out using extensive simulations against engineering perception and operation experience on the qualitative behaviour. Then for validation purposes the outputs of the model are compared to measurements on the real system to give a quantitative performance index about the model accuracy. Since for model-based controller design the developed model is too complex it should be simplified. Hence possible model reduction methods are proposed, which omit all details that are weakly represented in the state variables/outputs and not coupled with the control aims.     

A game theoretic approach to controller design for hybrid systems

We present a method to design controllers for safety specifications in hybrid systems. The hybrid system combines discrete event dynamics with nonlinear continuous dynamics: the discrete event dynamics model linguistic and qualitative information and naturally accommodate mode switching logic, and the continuous dynamics model the physical processes themselves, such as the continuous response of an aircraft to the forces of aileron and throttle. Input variables model both continuous and discrete control and disturbance parameters. We translate safety specifications into restrictions on the system's reachable sets of states. Then, using analysis based on optimal control and game theory for automata and continuous dynamical systems, we derive Hamilton-Jacobi equations whose solutions describe the boundaries of reachable sets. These equations are the heart of our general controller synthesis technique for hybrid systems, in which we calculate feedback control laws for the continuous and discrete variables, which guarantee that the hybrid system remains in the “safe subset” of the reachable set. We discuss issues related to computing solutions to Hamilton-Jacobi equations. Throughout, we demonstrate out techniques on examples of hybrid automata modeling aircraft conflict resolution, autopilot flight mode switching, and vehicle collision avoidance     

Accurate System Voltage and Timing Margin Simulation in High-Speed I/O System Designs

Accurate analysis of system timing and voltage margin including deterministic and random jitter is crucial in high-speed I/O system designs. Traditional SPICE-based simulation techniques can precisely simulate various deterministic jitter sources, such as intersymbol interference (ISI) and crosstalk from passive channels. The inclusion of random jitter in SPICE simulations, however, results in long simulation time. Innovative simulation techniques based on a statistical simulation framework have been recently introduced to cosimulate deterministic and random jitter effects efficiently. This paper presents new improvements on this statistical simulation framework. In particular, we introduce an accurate jitter modeling technique which accounts for bounded jitter with arbitrary spectrum in addition to Gaussian jitter. We also present a rigorous approach to model duty cycle distortion (DCD). A number of I/O systems are considered as examples to validate the proposed modeling methodology.      

A New Topology Pattern for AC-DC Mixed Microgrid

In order to realize the modular design of the microgrid, this paper proposed a new modular topology for the AC-DC mixed microgrid. In that topology, the AC microgrid unit and the DC microgrid unit were packaged together by the back-to-back converter. The battery-supercapacitor hybrid energy storage system was connected to the DC bus of back-to-back converter. By the reasonable design on the battery-supercapacitor hybrid system, the energy storage system could supply the rapid power and energy support for the microgrid spontaneously. The mathematical model and the control algorithm of that microgrid topology were studied. By the simulation analysis, it can be concluded that AC-DC mixed modular microgrid topology could operate steadily on both the grid-connected mode and the isolated mode. Furthermore, we can conclude by the simulation that the designed modular microgrid could operate uninterrupted when the microgrid topology switched from the grid-connected mode to the isolated mode. The seamless switching became the natural property for the modular microgrid. As a result, the modular microgrid topology can be considered as a usual power/load module to realize the friendly power interaction with the power grid.     

Use of hybrid models for testing and debugging control software for electromechanical systems

This paper proposes a hybrid modeling language and its application to a simulator-based testing and debugging environment for the control software for electromechanical systems. The new hybrid modeling language is designed mainly focusing on simulation speed, flexibility in connecting with control software, and model reusability. This language maintains the advantages of existing hybrid modeling languages such as Hybrid cc, including the flexibility of constraint programming and the reusability of the object-oriented approach. A new feature of the language is that it allows combination of compositional constraint programming and sequential procedural programming. The compiled code is executed efficiently by the runtime system, which has a built-in mechanism for communicating with external software, eliminating the complicated setup required for integrating the simulator with the control software. Model components programmed by the object-oriented approach allow designers to use existing components and to concentrate on the task of modeling the newly designed hardware. The runtime system has been integrated with a three-dimensional kinematics simulator and a control software design tool to create a simulator-based testing and debugging environment. The effectiveness of this system has been confirmed through its application to real product design projects.     

An MRAS-based sensorless high-performance induction motor drive with a predictive adaptive model

This paper presents a new model reference adaptive system (MRAS) speed observer for high-performance field-oriented control induction motor drives based on adaptive linear neural networks. It is an evolution and an improvement of an MRAS observer presented in the literature. This new MRAS speed observer uses the current model as an adaptive model discretized with the modified Euler integration method. A linear neural network has been then designed and trained online by means of an ordinary least-squares (OLS) algorithm, differently from that in the literature which employs a nonlinear backpropagation network (BPN) algorithm. Moreover, the neural adaptive model is employed here in prediction mode, and not in simulation mode, as is usually the case in the literature, with a consequent quicker convergence of the speed estimation, no need of filtering the estimated speed, higher bandwidth of the speed loop, lower estimation errors both in transient and steady-state operation, better behavior in zero-speed operation at no load, and stable behavior in field weakening. A theoretical analysis of some stability issues of the proposed observer has also been developed. The OLS MRAS observer has been verified in numerical simulation and experimentally, and in comparison with the BPN MRAS one presented in the literature.     

Run by run process control: combining SPC and feedback control

The run by run controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The run by run controller combines the advantages of both statistical process control (SPC) and feedback control. It has three components: rapid mode, gradual mode, and generalized SPC. Rapid mode adapts to sudden shifts in the process such as those caused by maintenance operations. Gradual mode adapts to gradual drifts in the process such as those caused by build-up of deposition inside a reactor. The choice between the two modes is determined by the outcome from generalized SPC which allows SPC to be applied to a process while it is being tuned. The run by run controller has been applied to the control of a silicon epitaxy process in a barrel reactor. Rapid mode recovered the process within 3 runs after a disturbance. Gradual mode reduced the variation of the process by a factor of 2.7 as compared to historical data     

Optimal control of hybrid systems in manufacturing

Hybrid systems combine time-driven and event-driven dynamics. This is a natural framework for manufacturing processes: The physical characteristics of production parts undergo changes at various operations described by time-driven models, while the timing control of operations is described by event-driven models. Accordingly, in the framework we propose, manufactured parts are characterized by physical states (e.g. temperature, geometry) subject to time-driven dynamics and by temporal states (e.g., operation start and stop times) subject to event-driven dynamics. We first provide a tutorial introduction to this hybrid system framework and associated optimal control problems through a single-stage manufacturing process model. We then show how the structure of the problem can be exploited to decompose what is a hard nonsmooth, nonconvex optimization problem into a collection of simpler problems. Next, we present extensions to multistage manufacturing processes for which we develop solution algorithms that make use of Bezier approximation techniques. Emphasis is given to the issue of deriving solutions through efficient algorithms, and some explicit numerical results are included     

基于模糊控制的有源滤波器直流母线电压控制

针对传统直流侧电压控制方法存在超调量和静差较大的问题,设计了混合有源电力滤波器控制系统,建立了混合有源电力滤波器的系统模型,并针对直流侧电压控制设计了一套双模糊控制器,与传统直流侧电压控制方法相比,该控制方法具有超调小、响应速度快、静差较小的特点。仿真结果验证了该方法的正确性和可行性。     

Statistical delta modulation

This report describes the results of a study of Statistical Delta Modulation (SDM), a new method of digital transmission of analog information [1]. In this method the system design is tailored to the statistical properties of the input data so as to provide analog reconstruction values with a minimum mean squared error. The method of system design is an iterative procedure in which conditional means are evaluated based upon actual input data. The report presents the theory of operation of the system and describes the results of a computer simulation in which such questions as the effects of sampling rate, channel noise, system memory, and mismatched input processes are discussed. At the present time only a brief comparison has been made with conventional techniques. It was found that at low sampling rates and for a particular non-Gaussian process, sampling rate reductions of 38 percent could be achieved relative to a conventional delta modulation system at the same SNR performance.     

计算轴对称粒子光散射问题的简化T矩阵方法

首先给出了光散射计算中的T矩阵方法的推导过程,然后分析了轴对称粒子T矩阵的特点——方位模m的独立性。并由此特点对原始的T矩阵进行了简化和变形,去除了其中的零元素并将其分成关于方位模m的小矩阵。然后运用基于方位模m的独立方程求得散射场系数。最后以球形粒子为例得到散射场的仿真结果与用微元法有很好的吻合。     

怠速模糊控制算法的研究

在研究传统PID控制算法在发动机怠速应用的基础上,提出了模糊怠速控制策略。在基于MATLAB/SIMULINK的仿真工具上,设计出了发动机怠速系统,并在此基础上设计出了模糊控制器。仿真过程中,研究了模糊控制算法的对怠速的控制能力,包括发动机启动到真正怠速的响应速度,以及发动机在外部负荷变化情况下的响应能力,随时增加负荷或者是减小负荷,模糊控制器都能做出快速响应。实验表明:模糊控制器的抗干扰能力相对PID有了很大的提高,由于不需要精确地数学模型,发动机具有了较强的自适应能力。     

Mastering the complexity of an Ultrasonic Sealing System: The port-Hamiltonian approach

This paper deals with the problem of simulating an Ultrasonic Sealing System (USS). The USS is a complex electromechanical system used to seal aseptic packages for liquid foods that is the core of the most advanced filling machines. Since the overall device is the result of the interconnection of several sub-systems that belong to different physical domains, the problem is tackled within the port-Hamiltonian framework, which is naturally multi-domain and multi-scale. On the other hand, the simulation of the whole sealing process is not a trivial task due to the presence of a Compact Transducer (CT) that can be modeled only by means of commercial finite-element software. Then, only extremely high-order models are available, which makes the simulation of the complete system impractical. Consequently, a novel model reduction procedure for port-Hamiltonian systems has been developed. The method is able to preserve the frequency behavior of the original system in a neighborhood of a predefined set of frequencies of interest. In this way, simulation times have been drastically shortened without loosing the essential dynamical information. The reduced order model can be adopted to test the validity of the controller, and to simulate and perform the diagnosis of the entire sealing process. The results of the model reduction algorithm have been experimentally validated. Moreover, also the complete USS model has been derived.