内燃机活塞裙部二次型线的弹性流体润滑分析

在对活塞动力学和流体动压润滑行为进行耦合建模的基础上,以椭圆曲线为例分析了二次裙部型线对承压油膜形成的影响,并通过仿真计算考察了活塞裙部二次型线下的油膜力及其在活塞两侧的分布、裙部摩擦损失、活塞二阶运动等。通过分析可知,与直线型裙部型线相比,二次型线具有如下特点:裙部与缸套间的多段楔形有利于形成分布更加合理的多段承压油膜,从而有利于活塞的可靠润滑和导向;活塞裙部摩擦损失有所减小;活塞横向运动速度和位移有明显增加等。

Theoretical Study of Double Cost Function Linear Quadratic Regulator(LQR)

Double cost function linear quadratic regulator (DLQR) is developed from LQR theory to solve an optimal control problem with a general nonlinear cost function. In addition to the traditional LQ cost function, another free form cost function was introduced to express the physical need plainly and optimize weights of LQ cost function using the search algorithms. As an instance, DLQR was applied in determining the control input in the front steering angle compensation control (FSAC) model for heavy duty vehicles. The brief simulations show that DLQR is powerful enough to specify the engineering requirements correctly and balance many factors effectively. The concept and applicable field of LQR are expanded by DLQR to optimize the system with a free form cost function.

Application of hybrid robust three-axis attitude control approach to overactuated spacecraft——A quaternion based model

A novel hybrid robust three-axis attitude control approach, namely HRTAC, is considered along with the well-known developments in the area of space systems, since there is a consensus among the related experts that the new insights may be taken into account as decision points to outperform the available materials. It is to note that the traditional control approaches may generally be upgraded, as long as a number of modifications are made with respect to state-of-the-art, in order to propose high-precision outcomes. Regarding the investigated issues, the robust sliding mode finite-time control approach is first designed to handle three-axis angular rates in the inner control loop, which consists of the pulse width pulse frequency modulations in line with the control allocation scheme and the system dynamics. The main subject to employ these modulations that is realizing in association with the control allocation scheme is to be able to handle a class of overactuated systems, in particular. The proportional derivative based linear quadratic regulator approach is then designed to handle three-axis rotational angles in the outer control loop, which consists of the system kinematics that is correspondingly concentrated to deal with the quaternion based model. The utilization of the linear and its nonlinear terms, simultaneously, are taken into real consideration as the research motivation, while the performance results are of the significance as the improved version in comparison with the recent investigated outcomes. Subsequently, there is a stability analysis to verify and guarantee the closed loop system performance in coping with the whole of nominal referenced commands. At the end, the effectiveness of the approach considered here is highlighted in line with a number of potential recent benchmarks.

Stiffness-damping matching method of an ECAS system based on LQG control

A novel method of matching stiffness and continuous variable damping of an ECAS(electronically controlled air suspension) based on LQG(linear quadratic Gaussian) control was proposed to simultaneously improve the road-friendliness and ride comfort of a two-axle school bus.Taking account of the suspension nonlinearities and target-height-dependent variation in suspension characteristics,a stiffness model of the ECAS mounted on the drive axle of the bus was developed based on thermodynamics and the key parameters were obtained through field tests.By determining the proper range of the target height for the ECAS of the fully-loaded bus based on the design requirements of vehicle body bounce frequency,the control algorithm of the target suspension height(i.e.,stiffness) was derived according to driving speed and road roughness.Taking account of the nonlinearities of a continuous variable semi-active damper,the damping force was obtained through the subtraction of the air spring force from the optimum integrated suspension force,which was calculated based on LQG control.Finally,a GA(genetic algorithm)-based matching method between stepped variable damping and stiffness was employed as a benchmark to evaluate the effectiveness of the LQG-based matching method.Simulation results indicate that compared with the GA-based matching method,both dynamic tire force and vehicle body vertical acceleration responses are markedly reduced around the vehicle body bounce frequency employing the LQG-based matching method,with peak values of the dynamic tire force PSD(power spectral density) decreased by 73.6%,60.8% and 71.9% in the three cases,and corresponding reduction are 71.3%,59.4% and 68.2% for the vehicle body vertical acceleration.A strong robustness to variation of driving speed and road roughness is also observed for the LQG-based matching method.

Design of an optimal active stabilizer mechanism for enhancing vehicle rolling resistance

Improving rollover and stability of the vehicles is the indispensable part of automotive research to prevent vehicle rollover and crashes.The main objective of this work is to develop active control mechanism based on fuzzy logic controller(FLC) and linear quadratic regulator(LQR) for improving vehicle path following,roll and handling performances simultaneously.3-DOF vehicle model including yaw rate,lateral velocity(lateral dynamic) and roll angle(roll dynamic) were developed.The controller produces optimal moment to increase stability and roll margin of vehicle by receiving the steering angle as an input and vehicle variables as a feedback signal.The effectiveness of proposed controller and vehicle model were evaluated during fishhook and single lane-change maneuvers.Simulation results demonstrate that in both cases(FLC and LQR controllers) by reducing roll angle,lateral acceleration and side slip angles remain under 0.6g and 4° during maneuver,which ensures vehicle stability and handling properties.Finally,the sensitivity and robustness analysis of developed controller for varying longitudinal speeds were investigated.

Attitude controller for reentry vehicles using state-dependent Riccati equation method

To get better tracking performance of attitude command over the reentry phase of vehicles, the use of state-dependent Riccati equation (SDRE) method for attitude controller design of reentry vehicles was investigated. Guidance commands are generated based on optimal guidance law. SDRE control method employs factorization of the nonlinear dynamics into a state vector and state dependent matrix valued function. State-dependent coefficients are derived based on reentry motion equations in pitch and yaw channels. Unlike constant weighting matrix Q, elements of Q are set as the functions of state error so as to get satisfactory feedback and eliminate state error rapidly, then formulation of SDRE is realized. Riccati equation is solved real-timely with Schur algorithm. State feedback control law u(x) is derived with linear quadratic regulator (LQR) method. Simulation results show that SDRE controller steadily tracks attitude command, and impact point error of reentry vehicle is acceptable. Compared with PID controller, tracking performance of attitude command using SDRE controller is better with smaller control surface deflection. The attitude tracking error with SDRE controller is within 5°, and the control deflection is within 30°.

SVM with Quadratic Polynomial Kernel Function Based Nonlinear Model One-step-ahead Predictive Control

A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection.

Using Adaptive Gain Scheduling LQR Method Control of Arm Driven Inverted Pendulum System Based on PIC18F4431

The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum with variable position of the ann. To solve this problem, this paper presents a mathematical model for arm driven inverted pendulum in mid-position configuration and an adaptive gain scheduling linear quadratic regulator control method for the stabilizing the inverted pendulum. The proposed controllers for arm driven inverted pendulum are simulated using MATLAB-SIMULINK and implemented on an experiment system using PIC 18F4431 mieroeontroller. The result of experiment system shows the control performance to be very good in a wide range stabilization of the arm position.

Computer simulation of active suspension based on the full-vehicle model

Abstract: The current method to solve the problem of active suspension control for a vehicle is often dealt with a quarter-car or half-car model. But it is not enough to use this kind of model for practical applications. In this paper, based on considering the influence of factors such as, seat and passengers, a MDOF(multi-degree-of-freedom) model describing the vehicle motion is set up. The MODF model, which is 8DOF of four independent suspensions and four wheel tracks, is more applicable by comparison of its analysis result with some conventional vehicle models. Therefore, it is more suitable to use the 8DOF full-car model than a conventional 4DOF half-car model in the active control design for car vibration. Based on the derived 8DOF model, a controller is designed by using LQ (linear quadratic ) control theory, and the appropriate control scheme is selected by testing various performance indexes. Computer simulation is carried out for a passenger car running on a road with step disturbance and random road disturbance expressed by Power Spectral Density (PSD). Vibrations corresponding to ride comfort are derived under the foregoing road disturbances. The response results for uncontrolled and controlled system are compared. The response of vehicle vibration is greatly suppressed and quickly damped, which testifies the effect of the active suspension. The results achieved for various controllers are compared to investigate the influence of different control schemes on the control effect.

Study of Comparative Saturated Sliding Mode Control and LQR Controller

The saturation problem is the one of the most common handicaps for applying to real applications, especially the actuator saturation. This paper focuses on the robustness of the sliding mode control （SMC） which incorporates a saturation constraint technique compared to classical linear quadratic regulator （LQR） with saturation. In the first step, the authors present a design methodology of SMC of a class of linear saturated systems. The authors present the structure of the saturation, after that the synthesis of the sliding surface is formulate as a problem of root clustering, which leads to the development of a continuous and non-linear control law that ensures the reaching condition of the sliding mode. The second step is devoted to present briefly the LQR controller technique. Finally, to validate results, the authors demonstrate an example of a quarter of vehicle system.

Control of a Rigid-Flexible Satellite Solar Panel with Non-collocated Sensor/Actuator

This paper presents a model and analysis for a flexible link with non-collocations of sensors and actuators. It shows the changes in the system dynamics and the appearance of zeroes in the right-plan complex, turning the system a non-minimum phase system. The performance of the PID （proportional-integral-derivative） and LQR （linear quadratic regulator） controller are discussed considering the zero dynamics of the system in three points of special interest： （I） the collocated case, when the sensor is in the base of the link; （2） the critical case, where the system starts to present zeroes in the right-plan complex and （3） the limit case, when the sensors are in the end point of the flexible link. Investigation for a simple rigid-flexible model with one mode, in the three cases, the PID and LQR controller performance are damage. To deal with this kind of problem, new control techniques should be developed.

Satellite Simulator Control System Design Using SDRE Method

This paper presents the application of the State-Dependent Riccati Equation （SDRE） method in conjunction with Kalman filter technique to design a satellite simulator control system. The performance and robustness of the SDRE controller is compared with the Linear Quadratic Regulator （LQR） controller. The Kalman filter technique is incorporated to the SDRE method to address the presence of noise in the process, measurements and incomplete state estimation. The effects of the plant non-linearities and noises （uncertainties） are considered to investigated the controller performance and robustness designed by the SDRE plus Kalman filter. A general 3-D simulator Simulink model is developed to design the SDRE controller using the states estimated by the Kalman filter. Simulations have demonstrated the validity of the proposed approach to deal with nonlinear system. The SDRE controller has presented good stability, great performance and robustness at the same time that it keeps the simplicity of having constant gain which is very important as for satellite onboard computer implementation.

DYNAMICAL ANALYSIS OF A 3-D CHAOTIC SYSTEM WITH ONLY TWO QUADRATIC NONLINEARITIES

The paper reports the dynamical study of a three-dimensional quadratic autonomous chaotic system with only two quadratic nonlinearities, which is a special case of the so-called conjugate Lue system. Basic properties of this system are analyzed by means of Lyapunov exponent spectrum and bifurcation diagram. The analysis shows that the system has complex dynamics with some interesting characteristics in which there are several periodic regions, but each of them has quite different periodic orbits.

Pendulum-like oscillation controller for micro aerial vehicle with ducted fan based on LQR and PSO

This paper describes a novel type of pendulum-like oscillation controller for micro air vehicle(MAV) hover and stare state in the presence of external disturbances,which is based on linear-quadratic regulator(LQR) and particle swarm optimization(PSO).A linear mathematical model of pendulum phenomenon based upon actual wind tunnel test data representing the hover mode is established,and a hybrid LQR and PSO approach is proposed to stabilize oscillation.PSO is applied to parameter optimization of the designed LQR controller.A series of comparative experiments are conducted,and the results have verified the feasibility,effectiveness and robustness of our proposed approach.

STOCHASTIC DIFFERENTIAL EQUATIONS AND STOCHASTIC LINEAR QUADRATIC OPTIMAL CONTROL PROBLEM WITH LEVY PROCESSES

In this paper, tile authors first study two kinds of stochastic differential equations （SDEs） with Levy processes as noise source. Based on the existence and uniqueness of the solutions of these SDEs and multi-dimensional backward stochastic differential equations （BSDEs） driven by Levy pro- cesses, the authors proceed to study a stochastic linear quadratic （LQ） optimal control problem with a Levy process, where the cost weighting matrices of the state and control are allowed to be indefinite. One kind of new stochastic Riccati equation that involves equality and inequality constraints is derived from the idea of square completion and its solvability is proved to be sufficient for the well-posedness and the existence of optimal control which can be of either state feedback or open-loop form of the LQ problems. Moreover, the authors obtain the existence and uniqueness of the solution to the Riccati equation for some special cases. Finally, two examples are presented to illustrate these theoretical results.

Optimal variational principle for backward stochastic control systems associated with Lévy processes

The paper is concerned with optimal control of backward stochastic differentiM equation （BSDE） driven by Teugel＇s martingales and an independent multi-dimensional Brownian motion, where Teugel＇s martingales are a family of pairwise strongly orthonormal martingales associated with L6vy processes （see e.g., Nualart and Schoutens＇ paper in 2000）. We derive the necessary and sufficient conditions for the existence of the optimal control by means of convex variation methods and duality techniques. As an application, the optimal control problem of linear backward stochastic differential equation with a quadratic cost criteria （or backward linear-quadratic problem, or BLQ problem for short） is discussed and characterized by a stochastic Hamilton system.

Optimization of formation for multi-agent systems based on LQR

In this paper,three optimal linear formation control algorithms are proposed for first-order linear multiagent systems from a linear quadratic regulator(LQR) perspective with cost functions consisting of both interaction energy cost and individual energy cost,because both the collective ob ject(such as formation or consensus) and the individual goal of each agent are very important for the overall system.First,we propose the optimal formation algorithm for first-order multi-agent systems without initial physical couplings.The optimal control parameter matrix of the algorithm is the solution to an algebraic Riccati equation(ARE).It is shown that the matrix is the sum of a Laplacian matrix and a positive definite diagonal matrix.Next,for physically interconnected multi-agent systems,the optimal formation algorithm is presented,and the corresponding parameter matrix is given from the solution to a group of quadratic equations with one unknown.Finally,if the communication topology between agents is fixed,the local feedback gain is obtained from the solution to a quadratic equation with one unknown.The equation is derived from the derivative of the cost function with respect to the local feedback gain.Numerical examples are provided to validate the effectiveness of the proposed approaches and to illustrate the geometrical performances of multi-agent systems.

Real-time optimization power-split strategy for hybrid electric vehicles

Energy management strategies based on optimal control theory can achieve minimum fuel consumption for hybrid electric vehicles, but the requirement for driving cycles known in prior leads to a real-time problem. A real-time optimization power-split strategy is proposed based on linear quadratic optimal control. The battery state of charge sustainability and fuel economy are ensured by designing a quadratic performance index combined with two rules. The engine power and motor power of this strategy are calculated in real-time based on current system state and command, and not related to future driving conditions. The simulation results in ADVISOR demonstrate that, under the conditions of various driving cycles, road slopes and vehicle parameters, the proposed strategy significantly improves fuel economy, which is very close to that of the optimal control based on Pontryagin's minimum principle, and greatly reduces computation complexity.

Linear quadratic stochastic integral games and related topics

This paper studies linear quadratic games problem for stochastic Volterra integral equations(SVIEs in short) where necessary and sufficient conditions for the existence of saddle points are derived in two different ways.As a consequence,the open problems raised by Chen and Yong(2007) are solved.To characterize the saddle points more clearly,coupled forward-backward stochastic Volterra integral equations and stochastic Fredholm-Volterra integral equations are introduced.Compared with deterministic game problems,some new terms arising from the procedure of deriving the later equations reflect well the essential nature of stochastic systems.Moreover,our representations and arguments are even new in the classical SDEs case.

THE MAXIMUM PRINCIPLE FOR PARTIALLY OBSERVED OPTIMAL CONTROL OF FORWARD-BACKWARD STOCHASTIC SYSTEMS WITH RANDOM JUMPS

This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.