LQ Speed Control of Pump Controlled Motor System

A linear quadric (LQ) optimal speed control algorithm is proposed for the speed control of a pump controlled motor hydraulic system. The control theme consists of optimal state feedback and disturbing compensation based on observation. The optimal state feedback bases on LQ cost function. The disturbing compensation is realized through reconstructing the state of load torque. A series of simulation are performed, and the results show that the control performance is satisfactory and can be maintained under changes of load torque.

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.

H~∞ Theory and its Application to the Position of Rolling Mill Control System

The controller designed according to classical or modern control theory will not satisfy the performance requirements when the controlled object in industrial field can not be described by exact mathematical model or the disturbance of the controlled system. In order to make the controlled system stable and having good performance, H∞ control theory was put forward to solve this practical problem. Taking the position of a rolling mill as the controlled object, it was rectified by optimal engineering way. Then, three different plans were put forward according to Bang-Bang control, LQ control and H∞ control, respectively. The result of the simulation shows that the controller designed according to H∞ method whose robust performance and ability to restrain colors disturbance is satisfactory.

A Mean-Field Linear-Quadratic Stochastic Stackelberg Differential Game with one Leader and Two Followers

This paper is concerned with a linear-quadrati stochastic Stackelberg differential game with one leader and two followers,where the game system is governed by a mean-field stochastic differential equatio.By maximum principle and verification theorem,the open-loop Stackelberg solution is expressed as a feedback form of the state and its mean with the help of three systems of Riccati equations.

Infinite horizon indefinite stochastic linear quadratic control for discrete-time systems

This paper discusses discrete-time stochastic linear quadratic （LQ） problem in the infinite horizon with state and control dependent noise, where the weighting matrices in the cost function are assumed to be indefinite. The problem gives rise to a generalized algebraic Riccati equation （GARE） that involves equality and inequality constraints. The well-posedness of the indefinite LQ problem is shown to be equivalent to the feasibility of a linear matrix inequality （LMI）. Moreover, the existence of a stabilizing solution to the GARE is equivalent to the attainability of the LQ problem. All the optimal controls are obtained in terms of the solution to the GARE. Finally, we give an LMI -based approach to solve the GARE via a semidefinite programming.

Stochastic H_2/H_∞ Control with Random Coefcients

Abstract This paper is concerned with the mixed H2/H∞ control for stochastic systems with random coefficients, which is actually a control combining the H2 optimization with the H∞ robust performance as the name of H2/H∞ reveals. Based on the classical theory of linear-quadratic （LQ, for short） optimal control, the sufficient and necessary conditions for the existence and uniqueness of the solution to the indefinite backward stochastic Riccati equation （BSRE, for short） associated with H∞ robustness are derived. Then the sufficient and necessary conditions for the existence of the H2/H∞ control are given utilizing a pair of coupled stochastic Pdccati equations.

Stochastic Nash Games for Markov Jump Linear Systems with State-and Control-Dependent Noise

This paper investigates Nash games for a class of linear stochastic systems governed by Itô’s differential equation with Markovian jump parameters both in finite-time horizon and infinite-time horizon.First,stochastic Nash games are formulated by applying the results of indefinite stochastic linear quadratic(LQ)control problems.Second,in order to obtain Nash equilibrium strategies,crosscoupled stochastic Riccati differential(algebraic)equations(CSRDEs and CSRAEs)are derived.Moreover,in order to demonstrate the validity of the obtained results,stochastic H2/H∞control with state-and control-dependent noise is discussed as an immediate application.Finally,a numerical example is provided.

Robust Hybrid Control for Ballistic Missile Longitudinal Autopilot

This paper investigates the boost phase＇s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor （RLC） network compensator as a control strategy, which does not take into account the time-varying missile dynamics. This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Therefore, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative （PID） with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. Moreover, the controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-scheduled optimal linear quadratic （LQ） in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.

Continuous-Time Mean-Variance Portfolio Selection Under Non-Markovian Regime-Switching Model with Random Horizon

This paper considers a continuous-time mean-variance portfolio selection with regime-switching and random horizon.Unlike previous works,the dynamic of assets are described by non-Markovian regime-switching models in the sense that all the market parameters are predictable with respect to the filtration generated jointly by Markov chain and Brownian motion.The Markov chain is assumed to be independent of Brownian motion,thus the market is incomplete.The authors formulate this problem as a constrained stochastic linear-quadratic optimal control problem.The authors derive closed-form expressions for both the optimal portfolios and the efficient frontier.All the results are different from those in the problem with fixed time horizon.