Improved optimal sliding mode control for a non-linear vehicle active suspension system

Chen, S.A.,Wang, J.C.,Yao, M.,Kim, Y.B. Elsevier [etc.] 2017 Journal of Sound and Vibration Vol.395 No.-

<P>The objective of this study is to present an improved optimal sliding mode (SM) control method for non-linear active suspension systems to obtain both the true nominal optimal suspension performance and better robustness. A general non-linear suspension dynamics model is established first. Its non-linear control scheme is applied using the improved optimal SM control method. This non-linear active suspension control system is linearized utilizing the feedforward and feedback linearization method. A fact is theoretically discovered that the general optimal SM control for the linearized active suspension system cannot provide true optimal results. Thus, the improved optimal SM controller for the linearized active suspension is proposed to address the disadvantage's of the general optimal SM controller. The improved optimal SM controller is designed by constructing an augmented optimal sliding mode manifold function, which includes all of the information of the structure and expected performance of the suspension. The advantages of the proposed controller are illustrated by comparing the performance of the improved optimal SM control, the fuzzy logical SM control, and the passive suspension. The simulation results verify that the proposed improved optimal SM control achieve the true nominal optimal suspension performance for a non-linear active suspension system in general condition. The results also show that even if the structure parameters and/or running conditions change, the proposed improved optimal SM control can still provide more robust characteristics. (C) 2017 Elsevier Ltd. All rights reserved.</P>

Optimization approach for the analytical design of an industrial PI controller for the optimal regulatory control of first order processes under operational constraints

Tchamna, Rodrigue,Lee, Moonyong Elsevier 2017 Journal of the Taiwan Institute of Chemical Engine Vol.80 No.-

<P><B>Abstract</B></P> <P>In this paper, an optimization-based approach for the closed-form design of an industrial proportional-integral (PI) controller was proposed for the optimal regulatory control of first order process under three typical operational constraints. An ingenious parameterization with Lagrangian multiplier method was used to convert the constrained optimal control problem in the time domain to an unconstrained optimization problem to derive an analytical solution for the optimal regulatory control. Three typical operational constraints could be taken into account in the controller design stage, explicitly. The proposed analytical design method required no complicated optimization steps and guaranteed global optimal closed-loop performance and stability. The proposed analytical approach also provides useful insights into the optimal controller design and analysis. A practical and facile procedure for designing optimal PI parameters and a feasible constraint set was also proposed.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Analytical design of a PI controller for chemical processes is proposed. </LI> <LI> The controller handles the control performance and the operational constraints. </LI> <LI> The controller shows the connection between the plant and controller parameters. </LI> <LI> A procedure is provided, helping to know if a given constraint set is feasible. </LI> <LI> If the constraint set cannot be satisfied, the procedure suggests how to tune it. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>The proposed PI controller design guarantees global optimal regulatory closed-loop performance and stability requiring no complicated optimization steps </P> <P>[DISPLAY OMISSION]</P>

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints

Tchamna, Rodrigue,Lee, Moonyong Elsevier 2018 ISA transactions Vol.72 No.-

<P><B>Abstract</B></P> <P>This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Optimal regulatory control of open-loop unstable process under operational constraints. </LI> <LI> An optimization based approach to find a global optimal solution of control system. </LI> <LI> The proposed method can handle operational constraints explicitly in controller design. </LI> <LI> The analytical design offers many useful insights to process control practitioners. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

재실자 예측과 핑퐁 방법을 통한 환기 시스템 최적제어 시뮬레이션

김영진,박철수 대한건축학회 2011 대한건축학회논문집 Vol. No.

In general, On-off and Multi step controls are widely applied to DCV-CO2 ventilation systems. The problem of the on-off and Multi step control is that their controls are not based on an optimal algorithm. Therefore, this study suggests a simulation assisted optimal control. The simulation assisted optimal control uses optimization algorithm to solve for optimal control variables to minimize a cost function over the time horizon. For this study, CONTAMW 2.4 simulation tool and EnergyPlus are coupled in MATLAB platform to simulate thermal and air-flow phenomena using Ping-Pong method. And the optimal control of ERV (Energy Recovery Ventilator) system is performed by a gradient-based search that uses the derivative of the cost function. The cost elements are energy flow and CO2 concentration (bedroom1, living room). A prominent characteristic presents that occupant’s schedule applies to a stochastic model based prediction of occupants' presence using the Markov Chain method. To perform Markov Chain method, the number of occupants every hour in each of the rooms (20 households) was examined and then the transition probability matrix was generated. By comparing the optimal control with existing controls (On-off and Multi step controls), it is shown that the proposed optimal control can lead to significant improvements for ventilation system performance

Optimal LQG Control for Networked Control Systems with Remote and Local Controllers

Xiao Liang,Juanjuan Xu,Xiao Lu,Qingyuan Qi,Haixia Wang,Rong Gao 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.1

We consider the finite horizon optimal LQG control problem for networked control systems with a remote controller, a local controller and communication channels with packet dropouts and transmission delays. The local controller can directly observe state signals and send them to the remote controller via a packet-dropout channel. Then the remote controller sends the received measurement signals to the local controller. Afterwards, the two controllers operate the plant through a delayed channel. The contributions of this paper are as follows: Firstly, at the side of the remote controller, we develop an optimal estimator to show that the separation principle holds. Secondly, we derive a non- homogeneous relationship between the state and the costate of systems in virtue of the maximum principle. Finally, a necessary and sufficient condition for the optimal control problem is derived in terms of the two coupled Riccati equations. Numerical examples are employed to illustrate the theoretical results.

Optimal Incremental-containment Control of Two-order Swarm System Based on Reinforcement Learning

Haipeng Chen,Wenxing Fu,Kang Chen,Junmin Liu,Dengxiu Yu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10

In this paper, the optimal incremental-containment control of two-order swarm system based on reinforcement learning (RL) is proposed to avoid the dilemma that the number of agents in a swarm system is immutable, which is essential for a swarm system that cannot meet the containment demands and need more agents to expand the containment range. Notably, the number of agents in a swarm system with a traditional containment controller is immutable, which limits the containment range that the swarm system can achieve. Besides, in traditional optimal control theory, it is obtained by solving the Hamilton-Jacobi-Bellman (HJB) equation, which is difficult to solve due to the unknown nonlinearity. To overcome these problems, several contributions are made in this paper. Firstly, in order to overcome the dilemma that the number of agents in the swarm system is immutable, the incremental-containment control is proposed. Secondly, considering the error and control input as the optimization goal, the optimal cost function is introduced and the optimal incremental-containment control is proposed to reduce resource waste and increase hardware service life. Furthermore, based on the proposed optimal incrementalcontainment control, the controller is designed by a new RL based on the backstepping method. The Lyapunov function is used to prove the stability of controller. The simulation show the efficiency of the proposed controller.

INTEGRATED FUZZY/OPTIMAL VEHICLE DYNAMIC CONTROL

A. GOODARZI,M. ALIREZAIE 한국자동차공학회 2009 International journal of automotive technology Vol.10 No.5

There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers. There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers.

사장교의 구조적 성능 개선을 위한 진동제어

김충길(Kim, Chunggil),허광희(Heo, Gwanghee),전준용(Jeon, Joonryong),전승곤(Jeon, Seunggon),오주원(Oh, Juwon) 한국구조물진단유지관리학회 2009 한국구조물진단학회 학술발표회논문집 Vol.2009 No.2

This paper is concerned with the control of the harmful vertical vibration occurring on a cable-stayed bridge, a type of large structure bridges. For the control, we designed a model structure of the bridge and a shear type MR damper. With those, vibration control experiments were performed and evaluated under various conditions: non-control, clipped-optimal control, and passive off and passive on the last two of which were added to evaluate the clipped-optimal control. As a result of the experiments, displacement and acceleration on the middle span were obtained, and from those were derived maximum displacement and maximum acceleration by which control performance was also evaluated. Additionally, each different voltage consumed at the moment of control was compared each other. Finally, it is proven that the clipped-optimal control method was functionally and economically effective in the case where such a semi-active control device as MR damper was employed in the control of a cable-stayed bridge.

Stochastic vibration suppression analysis of an optimal bounded controlled sandwich beam with MR visco-elastomer core

Z.G. Ying,Y.Q. Ni,Y.F. Duan 국제구조공학회 2017 Smart Structures and Systems, An International Jou Vol.19 No.1

To control the stochastic vibration of a vibration-sensitive instrument supported on a beam, the beam is designed as a sandwich structure with magneto-rheological visco-elastomer (MRVE) core. The MRVE has dynamic properties such as stiffness and damping adjustable by applied magnetic fields. To achieve better vibration control effectiveness, the optimal bounded parametric control for the MRVE sandwich beam with supported mass under stochastic and deterministic support motion excitations is proposed, and the stochastic and shock vibration suppression capability of the optimally controlled beam with multi-mode coupling is studied. The dynamic behavior of MRVE core is described by the visco-elastic Kelvin-Voigt model with a controllable parameter dependent on applied magnetic fields, and the parameter is considered as an active bounded control. The partial differential equations for horizontal and vertical coupling motions of the sandwich beam are obtained and converted into the multi-mode coupling vibration equations with the bounded nonlinear parametric control according to the Galerkin method. The vibration equations and corresponding performance index construct the optimal bounded parametric control problem. Then the dynamical programming equation for the control problem is derived based on the dynamical programming principle. The optimal bounded parametric control law is obtained by solving the programming equation with the bounded control constraint. The controlled vibration responses of the MRVE sandwich beam under stochastic and shock excitations are obtained by substituting the optimal bounded control into the vibration equations and solving them. The further remarkable vibration suppression capability of the optimal bounded control compared with the passive control and the influence of the control parameters on the stochastic vibration suppression effectiveness are illustrated with numerical results. The proposed optimal bounded parametric control strategy is applicable to smart visco-elastic composite structures under deterministic and stochastic excitations for improving vibration control effectiveness.

Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method

Song, Dongran,Fan, Xinyu,Yang, Jian,Liu, Anfeng,Chen, Sifan,Joo, Young Hoon Elsevier 2018 APPLIED ENERGY Vol.224 No.-

<P><B>Abstract</B></P> <P>To optimize the power extraction from the wind, horizontal-axis wind turbines are normally manipulated by the yaw control system to track the wind direction. How is the potential power extraction efficiency of such wind turbines related to the parameter optimization of a yaw control system? We intend to answer this question in this study. First, we develop two control systems, a direct measurement-based conventional logic control (Control system 1), and a soft measurement-based advanced model predictive control (Control system 2). Then, a multi-objective Particle Swarm Optimization-based method is introduced to optimize control parameters and search for the Pareto Front, which represents different potential performance. On this basis, result investigation and analysis are carried out on an electrical yaw system of China Ming Yang 1.5 MW wind turbines based on three wind directions with different variations. Experimental results show that, under a large wind direction variation and with a 14% yaw actuator usage, 0.32% and 0.8% more power extraction efficiency are gained by Control system 1 and 2, respectively, after optimization. The achievable power extraction efficiency for the two yaw control systems goes down when the allowable yaw actuator usage is reduced. For instance, when the yaw actuator usage is 14%, 4.9% and 2%, the efficiency is 97.19%, 96.76% and 96.37% for Control system 1, and is 97.73%, 96.76% and 95.45% for Control system 2, respectively. Therefore, Control system 2 takes precedence over Control system 1 for having higher efficiency when the allowable yaw actuator usage is more than 4.9%. We also find that the potential power extraction efficiency of the two control systems is significantly influenced by the wind direction variation, that is, the optimized efficiency under small wind direction variation is 1.5% higher than that under large wind direction variation. In addition, the parameters of Control system 1 need to be re-optimized according to the wind condition, whereas the ones of Control system 2 may not. Finally, a novel yaw control strategy employing the optimized parameters as the query tables is suggested for the real applications.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Two favorable yaw control systems are developed and optimized. </LI> <LI> Intelligent optimization method is proposed to optimize the potential performance. </LI> <LI> Power extraction efficiency is optimized by 0.32% and 0.8% for two control systems. </LI> <LI> Optimized efficiency under small wind variation is 1.5% more than the large variation one. </LI> <LI> Novel yaw control strategy employing optimized parameters is suggested. </LI> </UL> </P>