Lyapunov-based boundary feedback control in multi-reach canals

This paper presents a Lyapunov-based approach to design the boundary feedback control for an openchannel network composed of a cascade of multi-reach canals, each described by a pair of Saint-Venant equations. The weighted sum of entropies of the multi-reaches is adopted to construct the Lyapunov function. The time derivative of the Lyapunov function is expressed by the water depth variations at the gate boundaries, based on which a class of boundary feedback controllers is presented to guarantee the local asymptotic closed-loop stability. The advantage of this approach is that only the water level depths at the gate boundaries are measured as the feedback. Supported by the National Natural Science Foundation of China (Grant Nos. 60504026, 60674041), and the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z173)     

Modeling and speed control design of an ethanol engine for variable speed gensets

This paper presents the development of a discrete dynamic mean value engine model (MVEM) suitable for the design of speed controllers of ethanol fueled internal combustion engines (ICE), to be used in variable speed gensets. Two MVEMs are developed for the ICE: the Time Based model and the Crank Based model. The speed controller design is held through the discretization and linearization of the Crank Based MVEM. This model is used due to the advantages over the time based MVEM especially with respect to the transport delay which becomes constant. Two approaches for the ICE speed control are investigated: (i) a single loop gain-scheduled proportional integral (PI) controller and (ii) a dual loop control based on an internal gain-scheduled Manifold Absolute Pressure (MAP) feedback loop and an outer loop composed of a gain-scheduled PI controller. The control design is developed in the frequency domain and its stability is ensured by the phase and gain margins. In addition, an integral anti-windup and a feed forward action are also proposed to improve the behavior during control law saturation, improve transient responses and disturbance rejection capability. Experimental results on a 50 kW generator set are provided to validate the controllers and to demonstrate the performance of the system.     

Quantitative feedback design of air and boost pressure control system for turbocharged diesel engines

For modern diesel engines, variable geometry turbocharger (VGT) is used to boost engine power output. In addition, exhaust gas recirculation (EGR) is utilized to reduce engine out NO_x emission. To realize these functions, a multivariable control system needs to control both VGT and EGR valve to deliver desired intake manifold (or boost) pressure, and desired EGR flow rate. This two-input and two-output system is nonlinear with cross-couplings between the boost and EGR responses to the input actuators, the system parameters are varying with different engine operating conditions. This paper proposes a closed loop design of a multivariable VGT/EGR control system for a turbocharged diesel engine. The control system is synthesized based on quantitative feedback theory to maintain robust stability and performance via sequential MIMO loop shaping in the frequency domain. Experiment results are included from a turbocharged diesel engine to show the effectiveness of the proposed control design.     

Adaptive coordinated control of engine speed and battery charging voltage

In this paper, the control problem of auxiliary power unit (APU) for hybrid electric vehicles is investigated.An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the powerconverter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.     

Adaptive coordinated control of engine speed and battery charging voltage

In this paper, the control problem of auxiliary power unit （APU） for hybrid electric vehicles is investigated. An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the power-converter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.     

Robust nonlinear output feedback control for brake by wire control systems

This work proposes a nonlinear output feedback control law for active braking control systems. The control law guarantees bounded control action and can cope also with input constraints. Moreover, the closed-loop system properties are such that the control algorithm allows to detect—without the need of a friction estimator—if the closed-loop system is operating in the unstable region of the friction curve, thereby allowing to enhance both braking performance and safety. The design is performed via Lyapunov-based methods and its effectiveness is assessed via simulations on a multibody vehicle simulator.     

Lyapunov-based switching control of nonlinear systems using high-gain observers

We consider output feedback stabilization of uniformly observable uncertain nonlinear systems when the uncertain parameters belong to a known but comparably large compact set. In a previous paper, we proposed a new logic-based switching control to improve the performance of continuous high-gain-observer-based sliding mode controllers. Our main goal here is to show that similar techniques can be exploited for solving challenging control problems for a more general class of uncertain nonlinear systems. We require neither the sign of the high-frequency gain to be known nor the system to be minimum-phase. The key idea is to split the set of parameters into smaller subsets, design a controller for each of them, and switch the controller if, after a dwell-time period, the derivative of the Lyapunov function does not satisfy a certain inequality. A high-gain observer is used to estimate the derivatives of the output as well as the derivative of the Lyapunov function. Another goal of this paper is to introduce a switching strategy that uses on-line information to decide on the controller to switch to, instead of using a pre-sorted list as in our previous work. The new strategy can improve the transient performance of the system.     

Multi-input/single-output computer-aided control design using the quantitative feedback theory

The quantitative feedback theory is an engineering design technique of uncertain feedback systems having robust stability and robust performance specifications. The crux of the quantitative feedback theory is a transformation of robust stability and robust performance specifications into domains in the complex plane, referred to as bounds, where a nominal loop transmission should lie within. To date, a quantitative feedback theory design is being carried out using manual (i.e. graphical) procedures or search algorithms. This paper shows that there exists a formal map from the uncertain plant and each closed-loop specification to these bounds. In particular, it is shown that each map has a closed form consisting of a quadratic inequality. These maps greatly simplify the computational aspects of the quantitative feedback theory in design of single-loop feedback systems. Based on this new development, a simple-to-implement, efficient computer algorithm is outlined.     

Output feedback control for attitude tracking

In this paper the problem of attitude tracking control for a rigid spacecraft is addressed. It is assumed that only attitude measurements are available, and thus spacecraft's angular velocity has to be properly estimated. Two alternative schemes are proposed in which the unit quaternion is adopted to represent the orientation. In the first scheme, a second-order model-based observer is adopted to estimate the angular velocity used in the control law. In the second scheme, an estimate of the angular velocity error is obtained through a lead filter. Sufficient conditions ensuring local exponential stability of the two controllers are derived via Lyapunov analysis.     

预测反馈控制法及其特性研究

基于与延迟反馈控制法相似的原理，提出了一种新的混沌系统控制方法——预测反馈控制法．该方法基于目标系统的预测状态来构造控制信号，更为简单实用．首先系统阐述了该方法的基本原理和算法过程；然后严格论证了新方法在不同条件下的稳定性；最后借助于实例模拟总结了预测反馈控制法的一些重要特性，这对该方法的深入理解及应用提供了重要的指导作用．     

基于速度建模前馈控制方法的研究

常采用的双闭环控制方法无法解决动机座下的光电跟踪设备其跟踪精度与稳定性的矛盾,而导致跟踪失败。本文对平台罗经角度数据进行速度数学建模,首先通过有限记忆最小二乘滤波得到速度的平滑数据;再进行动机座下的坐标变换和视轴校正;最后将平滑的速度数据通过复合控制前馈到速度回路;试验表明:提高了精度了同时,保证系统的稳定性,其有效隔离度为13.06,大大提高了设备的跟踪性能。     

Lyapunov-based adaptive control of MIMO systems

The design of Model-Reference Adaptive Control for MIMO linear systems has not yet achieved, in spite of significant efforts, the completeness and simplicity of its SISO counterpart. One of the main obstacles has been the generalization of the SISO assumption that the sign of the high-frequency gain (HFG) is known. Here we overcome this obstacle and present a more complete MIMO analog to the well known Lyapunov-based SISO design which is significantly less restrictive than the existing analogs. Our algorithm makes use of a new control parametrization derived from a factorization of the HFG matrix K_p=SDU, where S is symmetric positive definite, D is diagonal, and U is unity upper triangular. Only the signs of the entries of D or, equivalently, the signs of the leading principal minors of K_p, are assumed to be known.     

Robust finite frequency range iterative learning control design and experimental verification

Iterative learning control is an application for two-dimensional control systems analysis where it is possible to simultaneously address error convergence and transient response specifications but there is a requirement to enforce frequency attenuation of the error between the output and reference over the complete spectrum. In common with other control algorithm design methods, this can be a very difficult specification to meet but often the control of physical/industrial systems is only required over a finite frequency range. This paper uses the generalized Kalman–Yakubovich–Popov lemma to develop a two-dimensional systems based iterative learning control law design algorithm where frequency attenuation is only imposed over a finite frequency range to be determined from knowledge of the application and its operation. An extension to robust control law design in the presence of norm-bounded uncertainty is also given and its applicability relative to alternative settings for design discussed. The resulting designs are experimentally tested on a gantry robot used for the same purpose with other iterative learning control algorithms.     

A hybrid feedback for a benchmark problem of idle speed control

The ever increasing demands on passengers' comfort, safety, emissions and fuel consumption imposed by car manufacturers and regulations call for advanced techniques and the use of cycle‐accurate models in automotive control. In this paper, we focus on such approach to the idle speed control. It is natural to resort to hybrid methodologies, because of the rich combination of time and event‐based behaviors exhibited by a controlled engine. A hybrid benchmark problem is considered and addressed first by analyzing the equilibria of the system and then testing a simple hybrid feedback strategy. Copyright © 2009 John Wiley & Sons, Ltd.     

基于混合观测器的混合反馈控制

对于一类混合动态系统,研究基于混合观测器的混合反馈控制问题．通过系统线性部分和离散事件部分的Lyapunov函数构造了整个混合系统的Lyapunov函数．据此设计了使整个系统稳定的混合反馈控制且证明了闭环系统的稳定性．仿真实例说明该方法的有效性．     

Application of adaptive control to the fluctuation of engine speed at idle

Idle speed control in a fuel-injection engine system has focused on controlling long-term averages of engine speed, but short-term fluctuations of engine speed have been neglected. The torque differences among cylinders influence the idle stability and cause vibration of the vehicle. In this paper, we introduce two intelligent control systems to reduce the fluctuations of engine speed at idle, an evolutionary computing control based on genetic algorithms and a stochastic control based on Alopex algorithm. We first estimate the torque differences among the cylinders by observing an engine cycle of crankshaft angular speed. Then the uniformity level over the engine speed is fedback into the control system. It manipulates spark ignition timings to suppress unbalanced combustions among the cylinders. We test the two adaptive approaches with simulation of a nonlinear engine model, and compare their performances.     

Direct discrete time design of robust state derivative feedback control laws

This paper is concerned with the problem of designing robust state derivative feedback control laws in discrete time. The main contribution consists of a method for recasting a continuous time state space model in the form of a discrete time model formulated in terms of the state derivative. Uncertain input delays and parametric uncertainties in polytopic form can be propagated from the original state space representation to the resulting state derivative model. Therefore, robust control techniques originally developed for discrete time state space models can be directly employed to design the state derivative feedback law. Three computational examples are presented for illustration. The first example highlights the importance of accounting for the effect of sampling in the design procedure. More specifically, a linear quadratic regulation problem involving the state derivative is addressed. The second example involves the design of a robust predictive controller in the presence of input constraints and uncertain time delay. Finally, the third example is concerned with robust pole placement in the presence of parametric uncertainty.     

Output feedback stabilization control design for Boolean control networks

This paper investigates the output feedback stabilization of Boolean control networks (BCNs) by using the semi-tensor product method and presents a number of new results. First, based on the algebraic expression of BCNs, a necessary and sufficient condition is presented for the existence of output feedback stabilizers. Second, a constructive procedure is proposed to design output feedback stabilization controllers for BCNs. The study of an illustrative example shows that the new results obtained in this paper are very effective in designing output feedback stabilizers for BCNs.     

柴油机的模糊PID调速控制策略研究

研究了一种基于模糊PID算法的柴油机调速控制策略。提出了一种模糊控制改进算法,对电子调速器PID参数按调速系统过渡过程进行在线实时模糊自整定。Matlab/Simulink仿真结果表明,该系统超调量控制效果明显得到改善,动、静态控制效果要好于常规PID控制,具有控制灵活、响应速度快和适应性强等优点。     

Economic Lyapunov-based model predictive control with event-triggered parametric identification

This article focuses on the design of model predictive control (MPC) for nonlinear systems with slow time-dynamic change. To avoid frequent updates of the predictive model and guarantee the state always stays inside of a given feasible region, an event-triggered parametric estimation mechanism is designed. Firstly, a trigger condition is designed to judge if parameters of the predictive model are out of date and differ a lot from their current true values so that there is no feasible solution to regulate the state within the given bound without predictive model parameter update. This condition also depends on the current state and is deduced from a designed Lyapunov constraint, inputs constraints, and the mismatched predictive model. Then the EMPC is designed based on this condition. If the trigger condition is met, the MPC recursively updates the parameters and imposes the Lyapunov constraint. The Lyapunov constraint is based on the mismatched model and the real state does not need to be convergence. Else, the MPC only optimizes the cost function to derive a good profit. We proved that the proposed EMPC promises that the closed-loop system state is maintained within a predefined stable region when the model mismatch bound can be estimated accurately. A simulation of a chemical process demonstrates the effectiveness of the proposed method.