Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

Fuzzy sliding-mode controllers with applications

This paper concerns the design of robust control systems using sliding-mode control that incorporates a fuzzy tuning technique. The control law superposes equivalent control, switching control, and fuzzy control. An equivalent control law is first designed using pole placement. Switching control is then added to guarantee that the state reaches the sliding mode in the presence of parameter and disturbance uncertainties. Fuzzy tuning schemes are employed to improve control performance and to reduce chattering in the sliding mode. The practical application of fuzzy logic is proposed here as a computational-intelligence approach to engineering problems associated with sliding-mode controllers. The proposed method can have a number of industrial applications including the joint control of a hydraulically actuated mini-excavator as presented in this paper. The control hardware is described together with simulated and experimental results. High performance and attenuated chatter are achieved. The results obtained verify the validity of the proposed control approach to dynamic systems characterized by severe uncertainties     

模糊滑模变结构控制技术的应用研究

针对包含非线性和不确定性的坦克炮控系统,提出了一种基于模糊控制的滑模变结构控制器的设计方法。首先采用极点配置的方法确定了等效控制,再通过应用带有切换增益的鲁棒反馈控制来保证滑模到达条件,然后,利用模糊调节策略来加速到达滑动模态区并削弱抖振。本文所提出的模糊逻辑的应用是一种可计算的智能方法,针对工程问题,具有精确表达式的调整过程,使得控制策略的调整变得更加容易实现。通过仿真结果可以看出,系统得到了更好的性能指标,并且削弱了抖振。系统响应的快速性和鲁棒性都得到了提高。     

基于反步滑模控制的TCP网络的主动队列管理

针对TCP网络的拥塞问题,考虑到网络本身存在参数不确定因素和非响应流的干扰,基于反步滑模控制提出了一种主动队列管理算法。在总的不确定的界已知而且不必很小的情况下,设计了一种反步滑模控制器来补偿系统不确定所带来的影响。仿真结果表明,该方法对TCP网络的复杂变化具有较好的鲁棒性和较快的系统响应。     

Adaptive incremental sliding mode control for a robot manipulator

An adaptive incremental sliding mode control (AISMC) scheme for a robot manipulator is presented in this paper. Firstly, an incremental backstepping (IBS) controller is designed using time-delay estimation (TDE) to reduce dependence on the mathematical model. After substituting IBS controller into the nonlinear system, a linear system w.r.t. tracking errors is obtained while TDE error is the disturbance. Then, the AISMC scheme, including a nominal controller and an SMC, is developed for the resulted linear system to improve control performance. According to the equivalent control method, the SMC in the AISMC scheme is to handle TDE error. To receive optimal control performance at the sliding manifold, an LQR controller is selected as the nominal controller. The SMC is designed based on positive semi-definite barrier function (PSDBF) since it prevents switching gains from being over/under-estimated, and two practical problems are addressed in this paper: A new PSDBF is designed and conservative (large) setting bounds affecting tracking precision and/or system stability are avoided; An improved PSDBF based SMC is developed where the PSDBF and an adaptive parameter are used simultaneously to regulate switching gains, and the system is still stable when sliding variable occasionally exceeds the predefined vicinity. Moreover, finite-time convergence property of the sliding variable is strictly analyzed. Finally, real-time experiments are conducted to verify the effectiveness of the proposed control method.     

Robust fuzzy neural network sliding mode control scheme for IPMSM drives

This article proposes a robust fuzzy neural network sliding mode control (FNNSMC) law for interior permanent magnet synchronous motor (IPMSM) drives. The proposed control strategy not only guarantees accurate and fast command speed tracking but also it ensures the robustness to system uncertainties and sudden speed and load changes. The proposed speed controller encompasses three control terms: a decoupling control term which compensates for nonlinear coupling factors using nominal parameters, a fuzzy neural network (FNN) control term which approximates the ideal control components and a sliding mode control (SMC) term which is proposed to compensate for the errors of that approximation. Next, an online FNN training methodology, which is developed using the Lyapunov stability theorem and the gradient descent method, is proposed to enhance the learning capability of the FNN. Moreover, the maximum torque per ampere (MTPA) control is incorporated to maximise the torque generation in the constant torque region and increase the efficiency of the IPMSM drives. To verify the effectiveness of the proposed robust FNNSMC, simulations and experiments are performed by using MATLAB/Simulink platform and a TI TMS320F28335 DSP on a prototype IPMSM drive setup, respectively. Finally, the simulated and experimental results indicate that the proposed design scheme can achieve much better control performances (e.g. more rapid transient response and smaller steady-state error) when compared to the conventional SMC method, especially in the case that there exist system uncertainties.     

Extended sliding mode observer based robust adaptive backstepping controller for electro-hydraulic servo system: Theory and experiment

This paper firstly presents an extended sliding mode observer (ESMO) for the electro-hydraulic servo systems (EHSSs) to deal with nonlinear factors like the external disturbance, parameter uncertainties as well as unmodeled characteristics in the EHSS. The model for the EHSS is established by taking these nonlinear factors into consideration and then the statespace representation is obtained. According to the state space, the ESMO for the EHSS is presented, the equivalence principle is properly utilized to simplify the ESMO and some saturation functions are employed to eliminate high frequency interferences caused by the chattering phenomenon. Based on estimated values from the ESMO, a robust adaptive backstepping controller (RABC) is presented in detail with taking some parameter uncertainties into consideration to further improve the tracking performance. The proposed controller has the following advantages: (1) utilizing the ESMO to cope with these nonlinear factors; (2) parameter online adaptive laws are employed in the RABC design to further improve the tracking performance. In order to verify the performance of the proposed controller, an experiment bench was established. Two sine waves reference signal (one amplitude 0.01 m, 1 Hz; the other 0.015 m, 2 Hz) are employed to verify the performance of the controller. Comparative experimental results show that: (1) the tracking performance of the proposed controller is better than that of a DOs based BC, a BC and a PI controller; (2) estimation values from the ESMO contains fewer noise than two conventional disturbance observers (DOs), which will decrease the control input ripples.     

导弹电液伺服机构的自适应模糊滑模跟踪控制

针对导弹电液伺服机构的跟踪控制问题,提出了一种自适应模糊滑模的设计方案.使用具有参数在线调节的自适应模糊控制,逼近滑模控制中的等效控制部分,并确定非线性控制项以保证系统的稳定性.根据滑模控制原理给出四条模糊规则,以平滑不连续控制,达到削弱抖振的目的.仿真结果表明了该方案的有效性.     

A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional–integral–derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.     

A supervisory fuzzy neural network controller for slider-crank mechanism

A supervisory fuzzy neural network (FNN) controller is proposed to control a nonlinear slider-crank mechanism in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive coupled with a slider-crank mechanism and a supervisory FNN position controller. The supervisory FNN controller comprises a sliding mode FNN controller and a supervisory controller. The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with on-line learning ability. The supervisory controller is designed to stabilize the system states around a defined bound region. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results are provided to show that the proposed control system is robust with regard to plant parameter variations and external load disturbance.     

基于非线性控制方法的AQM算法

首先利用非线性控制方法中的积分反步法设计了一种AQM算法,接着使用非线性控制方法中的模糊滑模变结构控制方法进行AQM算法的设计.仿真结果表明,与积分反步法相比,基于模糊滑模变结构控制的AQM算法性能上优于基于积分反步法的AQM算法.与基于线性控制方法的PID控制方法相比,基于积分反步法的AQM算法性能上优于基于PID控制的AQM算法.     

控制增益符号已知的MIMO非线性时滞系统自适应控制

针对一类具有死区模型并且控制增益符号已知的不确定多输入多输出非线性时滞系统,基于滑模控制原理提出了一种稳定的自适应神经网络控制方案。该方案通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性。通过利用积分型李亚普诺夫函数,并且构造逼近连续函数,闭环系统证明是半全局一致终结有界。仿真结果表明了该方法的有效性。     

Congestion Control for DiffServ Network Using Second-Order Sliding Mode Control

In this paper, a nonlinear fluid flow model is used to analyze and control DiffServ Network. The controller design is based on the integrated dynamic congestion control strategy and a leader–follower control scheme. With respect to standard sliding mode control (SMC), the second-order sliding mode technique shows the same properties of robustness to uncertainties of model and considerable simplification of model used in the design. Apart from the robustness feature, the proposed second-order SMC laws have the advantage of being continuous, thus eliminating the chattering effect and being more acceptable in application. The performance of the control scheme is verified by the simulation results.      

Leader‐Following Formation Control of Multiple Robots with Uncertainties through Sliding Mode and Nonlinear Disturbance Observer

This paper presents a control scheme for the leader‐following formation of multiple robots. The control scheme combines the sliding mode control (SMC) method with the nonlinear disturbance observer (NDOB) technique. The formation dynamics suffer from uncertainties because the individual robots are uncertain. Concerning such formation uncertainties, the leader‐following formation dynamics are modeled. Assuming that the formation uncertainties have an unknown boundary, an NDOB‐based observer was designed to estimate the formation uncertainties. A sliding surface containing the observer outputs has been defined. Regarding the sliding surface, an SMC‐based controller was investigated to form uncertain robots. A sufficient condition in the sense of the Lyapunov theory was proven such that the formation system is asymptotically stable. Herein, some comparison results between the sole SMC method and the second‐order SMC method are presented to demonstrate the effectiveness and feasibility of the control scheme for multiple robots in the presence of uncertainties.     

PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage

This paper presents a new scheme of adaptive sliding mode control (ASMC) for a piezoelectric ultrasonic motor driven X–Y stage to meet the demand of precision motion tracking while addressing the problems of unknown nonlinear friction and model uncertainties. The system model with Coulomb friction and unilateral coupling effect is first investigated. Then the controller is designed with adaptive laws synthesized to obtain the unknown model parameters for handling parametric uncertainties and offsetting friction force. The robust control term acts as a high gain feedback control to make the output track the desired trajectory fast for guaranteed robust performance. Based on a PID-type sliding mode, the control scheme has a simple structure to be implemented and the control parameters can be easily tuned. Theoretical stability analysis of the proposed novel ASMC is accomplished using a Lyapunov framework. Furthermore, the proposed control scheme is applied to an X–Y stage and the results prove that the proposed control method is effective in achieving excellent tracking performance.     

Sliding mode controller by use of neural networks

This paper proposes a method to design a robust controller by use of a neural network. The trained neural network functions as a sliding mode controller which is robust against uncertainties. From the analysis of the neural network, it is proved that the switching surface is not the same as the sliding surface like conventional sliding mode control theory. The neural network shows that the switching surface should be a nonlinear surface because of a hard limitation on control inputs, even if the designed sliding surface is linear. From the result of estimating the robustness of neural networks, we propose that generalization of neural networks which are used as controllers should be measured by the robustness. Numerical simulations show that the controller is robust against uncertainties and robustness can be improved by the proposed method.     

A relay-based method for servo performance improvement

This paper proposes a relay-based performance-improving method for servo mechanism systems. The method first utilizes a relay-based feedback technique to identify the model parameters and the Coulomb friction value. Then, based on the identified results, a control algorithm, which consists of a feedforward controller, a time-delay compensator and a sliding mode controller, is designed. The feedforward controller and the time-delay compensator are used to compensate the system dynamics and the external disturbances respectively. Their parameters are decided directly according to the identified values. The sliding mode controller is to stabilize the system, two of whose parameters are one-to-one mapping to the closed-loop characteristic roots. Thus, this method avoids the complicated parameters tuning process, which is attractive in practice to the control engineers. Experimental studies on a linear-motor-driven table illustrate that the proposed method is capable of improving the servo performance greatly and canceling the external disturbances effectively.     

Fuzzy sliding mode control for a class of piezoelectric system with a sliding mode state estimator

A new fuzzy sliding mode hysteresis compensating control strategy for a kind of typical piezoelectric system (PES) is proposed in this paper. Firstly, a typical nonlinear dynamic model of the PES is introduced. In order to compensate the hysteresis of the PES, an ideal linear hysteretic model is introduced by analyzing the characteristic of dynamic hysteretic model. Then, the ideal hysteretic model is transformed into an expected linear model by multiplying a slope conversion factor which can be obtained by experiment. Further, the sliding mode control principle is constructed to calculate the hysteretic compensating control law, which can guarantee the practical hysteretic characteristic to reach the expected linear output feature. Consider the unmeasured hysteresis output of the PES, we further design a sliding mode estimator to estimate the hysteretic part’s output. Finally, we derive the adaptive law of the fuzzy sliding mode controller, and demonstrate its stability through Lyapunov stability theory. The simulation results show the validity of the sliding mode compensator for this kind of nonlinear dynamic model of PES.     

航空发动机模糊滑模变结构控制研究

针对航空发动机是一个具有时变不确定性的非线性系统,结合模糊控制和滑模变结构控制的特点,提出了一种基于模糊滑模变结构控制的航空发动机控制方法.采用线性滑模面和指数趋近律设计变结构控制器,应用模糊逻辑系统自适应调节切换增益,避免了传统滑模变结构控制系统在到达阶段对不确定性的敏感性,消除了滑模控制中的抖振.通过数字仿真,结果表明所设计的模糊滑模变结构控制器对系统的参数摄动和外部干扰具有不变性,使被控系统在整个控制阶段都具有较强的鲁棒性.     

Nonlinear adaptive control of direct-drive brushless DC motors andapplications to robotic manipulators

Robust adaptive nonlinear control of brushless DC (BLDC) motors is considered. A controller is designed for the plant that is robust to parametric and dynamic uncertainties in the entire electromechanical system. These uncertainties are shown to be bounded by polynomials in the states. In addition, the controller can reject any bounded unmeasurable disturbances entering the system. A model for the motor incorporating magnetic saturation is used to design voltage-level control inputs for the motor. The design methodology is based on our earlier work on adaptive control of nonlinear systems. The overall stability of the system is shown using Lyapunov techniques. The tracking error is shown to be globally uniformly bounded. The design procedure is shown to be also applicable to multilink manipulators actuated by BLDC motors. The performance of the controller is verified through simulations and comparisons with a proportional-integral-derivative-type controller are made