基于改进的CMAC的电动加载系统复合控制

 由于电动加载系统的非线性和时变性,特别是在运动干扰下传统的前馈控制方法很难得到满意的控制效果。针对电动加载系统的非线性及多余力矩强扰动的特点,依据神经网络的非线性逼近和自学习特性,提出了基于改进小脑模型关联控制器(CMAC)的复合控制策略,结合改进的CMAC与PID实现复合控制,由CMAC实现前馈控制,PID控制实现反馈控制,既保证了快速实时,又进一步减小了多余力矩干扰。改进的CMAC利用存储单元的先前学习次数作为可信度,消除了常规前馈型CMAC的过学习现象。文中建立了电动加载系统的数学模型,给出了具体的控制结构和算法。系统的动态仿真表明,该方法可有效地抑制多余力矩,改善电动加载系统的动态加载性能,有很强的鲁棒性。     

舵机力矩负载模拟器的混合控制方法研究

对采用电液伺服控制实现加载的力矩负载模拟器进行了深入的分析和研究。针对多余力矩和参数变化问题,建立了准确的数学模型,并提出了一种新型的复合控制策略,它包括对扰动的定常补偿、内环鲁棒ＰＩＤ和前向误差比例积分３个组成部分。采用这种混合控制律,可以大大提高加载系统的鲁棒性和跟踪性能,使多余力矩减少９９％。     

基于BOWA小脑模型的高精度稳定 电动加载系统

 随着电动加载系统的不断发展,对控制精度、动态特性和稳定性提出了更高的要求,常规的小脑模型(CMAC)和PD控制相结合的复合控制策略难以满足加载指标要求。针对无人机舵机电动加载系统的控制需求,提出了一种基于平衡学习、最优权值和自适应学习率的新型小脑模型(BOWA-CMAC)复合控制策略,它在保留小脑模型算法正常学习过程的同时,避免了算法的过学习现象,保证了系统的稳定,同时提高了跟踪精度和动态特性。仿真和实验结果表明,BOWA-CMAC复合控制策略具有很强的鲁棒性,抑制了加载系统的多余力矩,保证了系统的稳定性,有效提高了系统的跟踪精度和动态特性,非常适合于实时控制。     

电液伺服加载的神经网络内部反馈控制

 针对电液伺服加载系统多余力问题，提出了一种反馈加载系统内部力差信号减少多余力的控制方法。为了消除液压非线性及参数变化等影响，进一步提出基于神经网络内部参考模型调节方法。该参考模型为无舵机扰动时的液压油缸负载压力方程，在加载过程中，将油缸的负载压力与参考模型输出比较，利用神经网络自适应调节能力，消除加载中舵机运动的速度和加速度干扰，同时也克服液压系统非线性，时变参数和扰动的影响，该方法有较好的适用性。     

基于改进的速度同步控制的电液负载模拟器

对地面半实物加载仿真实验中存在的"多余力"问题进行分析和研究。首先建立了电液加载系统的数学模型,提出"多余力干扰系数"的概念,并给出定义方法。利用多余力干扰系数对多余力"成分"进行定量分析,理论分析传统"速度同步控制"抑制多余力的机理以及存在的问题,并提出了改进方法。在传统"速度同步控制"的基础上,提出利用舵机和加载系统的速度差对"多余力"进行二次抑制。实验结果验证了改进方案的有效性。基于改进方法,电液负载模拟器取得了理想的动态加载效果,"多余力"抑制能力较传统的"速度同步控制"方法提高了25%以上。     

内模I-PD控制在舵机负载模拟器中的应用

为了提高舵机负载模拟器的抗干扰性能,解决控制对象参数时变、不确定性的问题,在PID控制的基础上提出了内模I-PD控制器.计算机仿真和实际应用表明,内模I-PD控制具有较好的鲁棒性和控制品质,能够进一步抑制多余力矩对系统的干扰,且易于工程实现,具有很好的应用价值.     

电动负载模拟器的多余力矩抑制

为实现负载台的恒力矩加载,必须抑制由于舵机主动运动造成的多余力矩。文章通过数学建模仿真和对系统扫频辨识,应用结构不变性原理抑制了多余力矩,并在实际系统进行了验证,证明了此种抑制多余力矩方法的有效性。     

电动模拟加载测试系统的设计与实现

针对导弹弹翼尾翼电动模拟加载测试系统，设计系统硬件结构，详细分析加载系统中多余力矩的测试及抑制方法，提出以TMS320LF2407 DSP和以直接转矩控制输出的ACS600伺服驱动器为核心的系统实现方法。对电动加载系统快速性和多余力消除这两个关键性的难点给出解决方案。实验结果表明，系统能精确地模拟弹翼及尾翼在飞行展开过程中的气流阻力，满足加载测试系统的快速性要求。     

CMAC-PID控制在飞机防滑刹车中的应用

提出了一种基于CMAC神经网络与PID相结合的控制方法,利用传统的PID控制器实现反馈控制,保证系统的稳定性并抑制扰动;利用CMAC神经网络控制器实现前馈控制,保证系统的控制精度和响应速度。以某型飞机为例,针对不同的跑道(干、湿、冰)情况,将该方法和传统的PID控制方法在MATLAB环境下进行了数字仿真。仿真结果表明:基于CMAC-PID控制方法较传统的PID控制方法,可以大大地提高飞机防滑刹车效率,具有更好的刹车控制效果,并具有较强的鲁棒性,为飞机防滑刹车系统的控制提供一条新的思路。     

航空发动机神经网络自学习PID控制

将神经网络与传统的PID控制相结合,构成神经网络自学习PID控制,用神经网络在线整定PID控制器的比例、积分及微分三个参数,使被控对象跟踪理想参考模型的输出。该系统具有自学习能力,能适用于非线性、时变的被控对象。将神经网络自学习PID控制方法用于航空发动机全包线控制以及蜕化发动机的控制,进行了数字仿真,验证了该方法的有效性。     

基于速度同步控制的电液负载模拟器

通过理论与试验相结合的方法建立了电液力伺服控制系统的精确非线性数学模型 ,从理论上对采用传统的结构不变性原理来消除多余力的方案进行了分析 ,找出了其效果有一定局限性的机理 ,说明电液力伺服系统的非线性和频率特性对电液负载模拟器的性能有较大的影响 ,进而提出了利用舵机伺服阀的控制信号进行速度同步控制、抑制多余力矩的新方案 ,消除了系统滞后的影响 ,另外 ,由于舵机与加载马达数学模型的相似性 ,对非线性起到了一定的补偿作用。仿真和试验结果证明该方案在系统的动态品质、鲁棒性和消扰能力等方面具有相当好的效果。     

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators. The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID (FOPID) controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead (N-M) optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers.     

无轴承异步电机的自抗扰控制策略

针对无轴承异步电机(BLIM)的逆系统解耦控制性能受负载和参数变化影响的问题,在转子磁链定向逆系统解耦控制的基础上,采用自抗扰控制器(ADRC)替换经典的PID控制器,将BLIM模型中的交叉耦合项、本体参数变化和负载视为“扰动”,统一用ADRC的扩张状态观测器(ESO)估测,非线性状态误差反馈控制器(NLSEF)进行补偿。仿真结果表明:采用了ADRC,系统具有较好的动态解耦控制性能；同时,对电机参数和负载变化具有更好的鲁棒性。     

Adaptive Nonlinear Optimal Compensation Control for Electro-hydraulic Load Simulator

 Directing to the strong position coupling problem of electro-hydraulic load simulator (EHLS), this article presents an adap-tive nonlinear optimal compensation control strategy based on two estimated nonlinear parameters, viz. the flow gain coeffi-cient of servo valve and total factors of flow-pressure coefficient. Taking trace error of torque control system to zero as control object, this article designs the adaptive nonlinear optimal compensation control strategy, which regards torque control output of closed-loop controller converging to zero as the control target, to optimize torque tracking performance. Electro-hydraulic load simulator is a typical case of the torque system which is strongly coupled with a hydraulic positioning system. This article firstly builds and analyzes the mathematical models of hydraulic torque and positioning system, then designs an adaptive nonlinear optimal compensation controller, proves the validity of parameters estimation, and shows the comparison data among three control structures with various typical operating conditions, including proportion-integral-derivative (PID) controller only, the velocity synchronizing controller plus PID controller and the proposed adaptive nonlinear optimal compensation controller plus PID controller. Experimental results show that systems’ nonlinear parameters are estimated exactly using the proposed method, and the trace accuracy of the torque system is greatly enhanced by adaptive nonlinear optimal compensation control, and the torque servo system capability against sudden disturbance can be greatly improved.     

Load distribution strategy for multi-lift system with helicopters based on power consumption and robust adaptive game control

It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption, relative position and interaction comprehensively. Therefore, the load distribution strategy based on power consumption and robust adaptive game control is proposed in this paper. The study is on a “2-lead” multi-lift system of four tandem helicopters carrying a load cooperatively. First, based on the hierarchical control, the load distribution problem is divided into two parts: the calculation of expected cable force and the calculation of the anti-disturbance cable force. Then, aimed at minimizing the maximum equivalent power of helicopter, an optimization problem is set up to calculate the expected cable force. Specially, the agent power model is trained by BP neural network, the safe distance constraint between helicopters is set to 2.5 rotor diameters to reduce aerodynamic interference, and the helicopters with different performance can be considered by introducing the equivalent power factor into the objective function. Next, considering the difference and interaction between helicopters, the robust adaptive differential game control is proposed to calculate the anti-disturbance cable force. Particularly, to solve the coupled Hamiltonian equations, an adaptive solving method for value function is proposed, and its stability is proved in the sense of Lyapunov. The simulation results indicate that the proposed load distribution method based on power consumption is applicable to the entire flight trajectory even there are differences between helicopters. The game control can consider interaction between helicopters, can deal with different objective functions, and has strong robustness and small steady-state error. Based on the entire strategy, the cable force can be reasonably allocated so as to resist disturbance and improve the flight performance of the whole system.     

航空发动机递归神经网络分路式解耦控制

针对航空发动机多变量控制中变量之间的耦合问题,提出了一种基于递归神经网络的分路式动态解耦控制方法,给出了发动机双路式解耦控制系统的结构及其解耦原理和算法。利用递归小波网络较强的动态非线性映射能力,在线完成发动机各控制通道的模型辨识,并回馈对应的灵敏度信息;神经网络PID控制器根据回馈的信息在线自适应调整参数,实现发动机各通道的准确跟踪和分路独立控制。仿真表明,该方法在保证控制系统良好的动态和稳态性能的同时,有效地减小了各回路之间的耦合影响,能够成功应用于发动机控制系统的解耦。      

A novel intelligent adaptive control of laser-based ground thermal test

Laser heating technology is a type of potential and attractive space heat flux simulation technology, which is characterized by high heating rate, controlled spatial intensity distribution and rapid response. However, the controlled plant is nonlinear, time-varying and uncertainty when implementing the laser-based heat flux simulation. In this paper, a novel intelligent adaptive controller based on proportion–integration–differentiation(PID) type fuzzy logic is proposed to improve the performance of laser-based ground thermal test. The temperature range of thermal cycles is more than 200 K in many instances. In order to improve the adaptability of controller,output scaling factors are real time adjusted while the thermal test is underway. The initial values of scaling factors are optimized using a stochastic hybrid particle swarm optimization(H-PSO)algorithm. A validating system has been established in the laboratory. The performance of the proposed controller is evaluated through extensive experiments under different operating conditions(reference and load disturbance). The results show that the proposed adaptive controller performs remarkably better compared to the conventional PID(PID) controller and the conventional PID type fuzzy(F-PID) controller considering performance indicators of overshoot, settling time and steady state error for laser-based ground thermal test. It is a reliable tool for effective temperature control of laser-based ground thermal test.     

数控机床切削力负载模拟器的显式力控制算法设计

为了对数控机床进行可靠性试验,设计了一种基于3P-(4S)并联机构的负载模拟器。基于PI反馈控制的显式力控制算法,并引入了模糊控制器,提高系统对不同加载误差的适应性。在控制系统中引入了力前馈控制器,提高控制系统的动态性能,减少实际加载力的滞后。同时,由于加载目标即机床主轴的进给运动轨迹未知,因此引入了主轴位置预测前馈以进行运动补偿,减少主轴运动所带来的干扰。最后设计并实施了静态与动态负载模拟试验,验证了所提控制算法的有效性。