Water-Assisted Injection Molding System Based on Water Hydraulic Proportional Control Technique

Water-assisted injection molding（WAIM）, an innovative process to mold plastic parts with hollow sections, is characterized with intermittent, periodic process and large pressure and flow rate variation. Energy savings and injection pressure control can not be .attained based on conventional valve control system. Moreover, the injection water can not be supplied directly by water hydraulic proportional control system. Poor efficiency and control performance are presented by current trial systems, which pressurize injection water by compressed air. In this paper, a novel water hydraulic system is developed applying an accumulator for energy saving. And a new differential pressure control method is proposed by using pressure cylinder and water hydraulic proportional pressure relief valve for back pressure control. Aiming at design of linear controller for injection water pressure regulation, a linear load model is approximately built through computational fluid dynamics（CFD） simulation on two-phase flow cavity filling process with variable temperature and viscosity, and a linear model of pressure control system is built with the load model and linearization of water hydraulic components. According to the simulation, model based feedback is brought forward to compensate the pressure decrease during accumulator discharge and eliminate the derivative element of the system. Meanwhile, the steady-state error can be reduced and the capacity of resisting disturbance can be enhanced, by closed-loop control of load pressure with integral compensation. Through the developed experimental system in the State Key Lab of Fluid Power Transmission and Control, Zhejiang University, China, the static characteristic of the water hydraulic proportional relief valve was tested and output pressure control of the system in Acrylonitrile Butadiene Styrene（ABS） parts molding experiments was also studied. The experiment results show that the dead band and hysteresis of the water hydraulic proportional pressure relief valve are large, but the control precision and linearity can be improved with feed-forward compensation. With the experimental results of injection water pressure control, the applicability of this WAIM system and the effect of its linear controller are verified. The novel proposed process of WAIM pressure control and study on characteristics of control system contribute to the application of water hydraulic proportional control and WAIM technology.

Quaternion-based Nonlinear Trajectory Tracking Control of a Quadrotor Unmanned Aerial Vehicle

At present, most controllers of quadrotor unmanned aerial vehicles（UAVs） use Euler angles to express attitude. These controllers suffer a singularity problem when the pitch angle is near 90°, which limits the maneuverability of the UAV. To overcome this problem, based on the quatemion attitude representation, a 6 degree of freedom（DOF） nonlinear controller of a quadrotor UAV is designed using the trajectory linearization control（TLC） method. The overall controller contains a position sub-controller and an attitude sub-controller. The two controllers regulate the translational and rotational motion of the UAV, respectively. The controller is improved by using the commanded value instead of the nominal value as the input of the inner control loop. The performance of controller is tested by simulation before and after the improvement, the results show that the improved controller is better. The proposed controller is also tested via numerical simulation and real flights and is compared with the traditional controller based on Euler angles. The test results confirm the feasibility and the robustness of the proposed nonlinear controller. The proposed controller can successfully solve the singularity problem that usually occurs in the current attitude control of UAV and it is easy to be realized.

Trajectory linearization control of an aerospace vehicle based on RBF neural network

An enhanced trajectory linearization control （TLC） structure based on radial basis function neural network （RBFNN） and its application on an aerospace vehicle （ASV） flight control system are presensted. The influence of unknown disturbances and uncertainties is reduced by RBFNN thanks to its approaching ability, and a robustifying itera is used to overcome the approximate error of RBFNN. The parameters adaptive adjusting laws are designed on the Lyapunov theory. The uniform ultimate boundedness of all signals of the composite closed-loop system is proved based on Lyapunov theory. Finally, the flight control system of an ASV is designed based on the proposed method. Simulation results demonstrate the effectiveness and robustness of the designed approach.

A new reduction-based LQ control for dynamic systems with a slowly time-varying delay

Time delays in the feedback control often dete- riorate the control performance or even cause the instability of a dynamic system. This paper presents a control strategy for the dynamic system with a constant or a slowly time-varying input delay based on a transformation, which sire-plifies the time-delay system the relation is discussed for into a delay-free one. Firstly, two existing reduction-based linear quadratic controls. One is continuous and the other is discrete. By extending the relation, a new reduction-based control is then developed with a numerical algorithm presented for practical control implementation. The controller suggested by the proposed method has such a promising property that it can be used for the cases of different values of an input time delay without redesign of controller. This property provides the potential for stabilizing the dynamic system with a time-varying input delay. Consequently, the application of the proposed method to the dynamic system with a slowly time-varying delay is discussed. Finally, numerical simulations are given to show the efficacy and the applicability of the method.

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

A new hyperchaotic system and its linear feedback control

This paper reports a new hyperchaotic system by adding an additional state variable into a three-dimensional chaotic dynamical system, studies some of its basic dynamical properties, such as the hyperchaotic attractor, Lyapunov exponents, bifurcation diagram and the hyperchaotic attractor evolving into periodic, quasi-periodic dynamical behaviours by varying parameter k. Furthermore, effective linear feedback control method is used to suppress hyperchaos to unstable equilibrium, periodic orbits and quasi-periodic orbits. Numerical simulations are presented to show these results.

Hybrid Predictive Control with Simple Linear Control Based Circulating Current Suppression for Modular Multilevel Converters

The modular multilevel converter(MMC)has become a promising topology for widespread power converter applications.However,an evident circulating current flowing between the phases will increase system losses and complicate the heatsink design.This paper proposes a novel hybrid model predictive control method for MMCs.This method utilizes an indirect structure MPC and a sorting algorithm to implement current tracking and capacitor voltages balancing,considerably resulting in reduced calculation burden.In addition,different from the conventional MPC solutions,we add a simple proportional-integral(PI)controller to suppress circulating current through modifying the submodule(SM)inserted number,which is parallel to the MPC loop.This hybrid control solution combines both advantages of MPC and linear control,evidently resulting in improved performance of circulating current.Finally,the MATLAB/Simulink results of an 11-level MMC system verify the effectiveness of the proposed solution.

Integrated guidance and control design of the suicide UCAV for terminal attack

A novel integrated guidance and control (IGC) design method is proposed to solve problems of low control accuracy for a suicide unmanned combat aerial vehicle (UCAV) in the terminal attack stage. First of all, the IGC system model of the UCAV is built based on the three-channel independent design idea, which reduces the difficulties of designing the controller. Then, IGC control laws are designed using the trajectory linearization control (TLC). A nonlinear disturbance observer (NDO) is introduced to the IGC controller to reject various uncertainties, such as the aerodynamic parameter perturbation and the measurement error interference. The stability of the closed-loop system is proven by using the Lyapunov theorem. The performance of the proposed IGC design method is verified in a terminal attack mission of the suicide UCAV. Finally, simulation results demonstrate the superiority and effectiveness in the aspects of guidance accuracy and system robustness.

A hybrid multi-degree-of-freedom vibration isolation platform for spacecrafts by the linear active disturbance rejection control

The hybrid vibration isolation, which takes advantages of both the passive and active approaches, has been an important solution for space missions. The objective of this paper is to design a vibration isolation platform for payloads on spacecrafts with the robust, wide bandwidth, and multi-degree-of-freedom(MDOF). The proposed solution is based on a parallel mechanism with six voice-coil motors(VCMs) as the actuators. The linear active disturbance resistance control(LADRC) algorithm is used for the active control. Numerical simulation results show that the vibration isolation platform performs effectively over a wide bandwidth, and the resonance introduced by the passive isolation is eliminated. The system robustness to the uncertainties of the structure is also verified by simulation.

ROBUST CONTROL VIA STATE FEEDBACK FOR A CLASS OF UNCERTAIN BILINEAR SYSTEMS

This paper is concerned with the problem of designing a stabilizing controller for a class of uncertain bilinear systems. The uncertainties in the systems must satisfy the matching condition and their bounds should be known. The so-called improved approach for stability analysis of nonlinear system was used. Under some suitable assumptions a linear robust state feedback controller can be designed. At last, an illustrative example was demonstrated.

Temperature Compensation Algorithm for Hydraulic System Pressure Control

In this paper the control mechanism of solenoid valve is analyzed,which shows the solenoid valve control is actually the control of coil current.The response characteristic of coil current is related to coil inductance and resistance.The coil resistance is influenced greatly by the ambient temperature and the self-heating of coil,which affects the control precision of coil current.First,considering the heat dissipation mode of coil,the coil temperature model is established from the perspective of heat conduction,and a temperature compensation algorithm for hydraulic system pressure control is put forward.Then the hardware-in-the-loop testbed is set up by using the dSPACE platform,carrying out wheel cylinder pressurization tests with inlet valve fully opened at-40℃ and 20℃,and testing the actual pressure of wheel cylinder with the target pressures at-40℃ and 6 000 kPa/s(pressurization rate).The results show that the pressure control temperature compensation algorithm proposed in this paper accurately corrects the influence of resistance temperature drift on the response accuracy of wheel cylinder pressure.After the correction,the pressure difference is less than 500 kPa,which can meet the control accuracy requirements of solenoid valve,enriching the linear control characteristic of solenoid valve.

New trajectory linearization control for nonlinear systems undergoing harmonic disturbance

This paper presents a new trajectory linearization control scheme for a class of nonlinear systems subject to harmonic disturbance. It is supposed that the frequency of the disturbance is known, but the amplitude and the phase are unknown. A disturbance observer dynamics is constructed to estimate the harmonic disturbance, and then the estimation is used to implement a compensation control law to cancel the disturbance. By Lyapunov＇s direct method, a rigorous poof shows that the composite error of the closed-loop system can approach zero exponentially. Finally, the proposed method is illustrated by the application to control of an inverted pendulum. Compared with two existing methods, the proposed method demonstrates better performance in tracking error and response time.

Linear Quadratic Integral Control for the Active Suspension of Vehicle

The quarter model of an active suspension is established in the form of controllable autoregressive moving average （CARMA） model. An accelerometer can be mounted on the wheel hub for measuring road disturbance; this signal is used to identify the CARMA model parameters by recursive forgetting factors least square method. The linear quadratic integral （LQI） control method for the active suspension is presented. The LQI control algorithm is fit for vehicle suspension control, for the control performance index can comprise multi controlled variables. The simulation results show that the vertical acceleration and suspension travel both are decreased with the LQI control in the low frequency band, and the suspension travel is increased with the LQI control in the middle or high frequency band. The suspension travel is very small in the middle or high frequency band, the suspension bottoming stop will not happen, so the vehicle ride quality can be improved apparently by the LQI control.

Reinforcement learning based parameter optimization of active disturbance rejection control for autonomous underwater vehicle

This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.

Decoupled nonsingular terminal sliding mode control for affine nonlinear systems

A decoupled nonsingular terminal sliding mode control（DNTSMC） approach is proposed to address the tracking control problem of affine nonlinear systems.A nonsingular terminal sliding mode control（NTSMC） method is presented,in which the nonsingular terminal sliding surface is defined as a special nonsingular terminal function and the convergence time of the system states can be specified.The affine nonlinear system is firstly decoupled into linear subsystems via feedback linearization.Then,a nonsingular terminal sliding surface is defined and the NTSMC method is applied to each subsystem separately to ensure the finite time convergence of the closed-loop system.The verification example is given to demonstrate the effectiveness and robustness of the proposed approach.The proposed approach exhibits a considerable advantage in terms of faster tracking error convergence and less chattering compared with the conventional sliding mode control（CSMC）.

ROBUST CONTROL OF GAS TUNGSTEN ARC WELDING SYSTEM

The robust control law for gas tungsten arc welding dynamic process, which is a typical sampled-data system and full of uncertainties, is presented. By using the Lyapunov, second method, the robust control and robust optimal control for a class of sampled-data systems whose underlying continuous-time systems are subjected to structured uncertainties are discussed in time-domain. As a result, some sufficient conditions of robust stability and the corresponding robust control laws are derived. All these results are designed by solving a class of linear matrix inequalities （LMIs） and a class of dynamic optimization problem with LMIs constraints respectively. An example adapted under some experimental conditions in the dynamic process of gas tungsten arc welding system in which the controlled variable is the backside width of weld pool and controlling variable pulse duty ratio, is worked out to illustrate the proposed results, it is shown that the sampling period is the crucial design oarameter.

Chaotic synchronization via linear controller

A technical framework of constructing a linear controller for chaotic synchronization by utilizing the stability theory of cascade-connected system is presented. Based on the method developed in the paper, two simple and linear feedback controllers, as examples, are derived for the synchronization of Liu chaotic system and Duffing oscillator, respectively. This method is quite flexible in constructing a control law. Its effectiveness is also illustrated by the simulation results.

Numerical solutions of linear quadratic control for time-varying systems via symplectic conservative perturbation

Optimal control system of state space is a conservative system, whose approximate method should be symplectic conservation. Based on the precise integration method, an algorithm of symplectic conservative perturbation is presented. It gives a uniform way to solve the linear quadratic control （LQ control） problems for linear timevarying systems accurately and efficiently, whose key points are solutions of differential Riccati equation （DRE） with variable coefficients and the state feedback equation. The method is symplectic conservative and has a good numerical stability and high precision. Numerical examples demonstrate the effectiveness of the proposed method.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

Robust Control Design of Wheeled Inverted Pendulum Assistant Robot

This paper examines the design concept and mobile control strategy of the human assistant robot I-PENTAR(inverted pendulum type assistant robot). The motion equation is derived considering the non-holonomic constraint of the twowheeled mobile robot. Different optimal control approaches are applied to a linearized model of I-PENTAR. These include linear quadratic regulator(LQR), linear quadratic Gaussian control(LQG), H_2 control and H_∞ control. Simulation is performed for all the approaches yielding good performance results.