Robust intelligent control design for marine diesel engine

This work deals with the nonlinear control of a marine diesel engine by use of a robust intelligent control strategy based on cerebellar model articulation controller （CMAC）. A mathematical model of diesel engine propulsion system is presented. In order to increase the accuracy of dynamical speed, the mathematical model of engagement process based on the law of energy conservation is proposed. Then, a robust cerebellar model articulation controller is proposed for uncertain nonlinear systems. The concept of active disturbance rejection control （ADRC） is adopted so that the proposed controller has more robustness against uncertainties. Finally, the proposed controller is applied to engine speed control system. Both the model of the diesel engine propulsion system and of the control law are validated by a virtual detailed simulation environment. The prediction capability of the model and the control efficiency are clearly shown.     

Sliding mode robust fault-tolerant control for uncertain systems with time delay

Considering the modeling uncertainties and external disturbance, a kind of sliding mode robust H∞fault-tolerant control method for time delay system with actuator fault is proposed. The upper-bound of the uncertainties is considered as a known constant, while the upper-bound of the actuator fault is unknown. A sufficient condition for the existence of an integral sliding mode dynamics is given in terms of linear matrix inequality(LMI). A novel adaptive law is given to estimate the unknown upper-bound of faults. On this basis, a type of sliding mode robust H∞fault-tolerant control law is designed to guarantee the asymptotic stability and the H_∞ performance index of the system. Finally, the simulation on quad-rotor semi-physical platform demonstrates the reliability and validity of the method.     

DISCRETE VARIABLE STRUCTURE CONTROL OF LINEAR TIME-INVARIANT SYSTEMS WITH TIME DELAY

IntroductionIn recentyears,many methods have been pro-posed for the design of time- delay control sys-tems[1,2 ] and criteria for the stability of time- delaysystems have been developed by many re-searchers[3 ,4] .Time delay in the control systemscan be divided into two classes on the whole.Oneis in measurement of system variables and calcula-tion for required control force,including physicalproperties of equipmentused in the systems or sig-nal transmission.The other is in control for actua-to…     

Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships

A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.     

Research on Network Delays of Networked Control Systems

In networked control systems (NCS), the main problem is time delays induced by communication network, which can deteriorate the performance of the systems, even cause the systems instability. If we know the exact network delays, we can compensate for their effect by modifying the parameters of the controller. Hence how to get the knowledge of these delays in the network is critical. This paper analyzed the different characteristics of network delays from sensor to controller and from controller to actuator and presented the methods of online evaluaticm of these delavs. The experiment shows these methods are valid.     

Distributed model predictive control with one-step delay communication for large-scale systems and a case study

A distributed model predictive control（MPC） scheme with one-step delay communication is proposed for on-line optimization and control of large-scale systems in this paper. Cooperation between subsystems is achieved by exchanging information with neighbor-to-neighbor communication and by optimizing the local problem with the improved performance index in the neighborhood. A distributed MPC algorithm with one-step delay communication is developed for the situation that there is a one-step delay in the information available from its neighbors when a subsystem solves the local optimization problem. The nominal stability is employed for the whole system under the distributed MPC algorithm without the inequality constraints. Finally, the case study of the reactor-storage-separator（RSS） system is illustrated to test the practicality of the presented control algorithm.     

Simulation platform for the underwater snake-like robot swimming based on Kane’s dynamic model and central pattern generator

A systematic method for swimming control of the underwater snake-like robot is still lacking. We construct a simulation platform of the underwater snake-like robot swimming based on Kane＇s dynamic model and central pattern generator （CPG）. The partial velocity is deduced. The forces which contribute to dynamics are determined by Kane＇s approach. Hydrodynamic coefficients are determined by experiments. Then, we design a CPG-based control architecture implemented as the system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. The relations between the CPG parameters and the speed of the underwater snake-like robot swimming are investigated. Swimming in a straight line, turning, and switching between swimming modes are implemented in our simulation platform to prove the feasibility of the proposed simulation platform. The results show that the simulation platform can imitate different swimming modes of the underwater snake-like robot.     

Control Lyapunov Stabilization of Nonlinear Systems with Structural Uncertainty

This paper deals with global stabilization problem for the nonlinear systems with structural uncertainty.Based on control Lyapunov function, a sufficient and necessary condition for the globally and asymptotically stabilizing the equailibrium of the closed system is given. Moreovery, an almost smooth state feedback control law is constructed. The simulation shows the effectiveness of the method.     

Stability Analysis of Uncertain Discrete Time-Delay Control Systems

Based on Lyapunov stability theory, a less conservative sufficient condilions for the stabih＇lies of uncertain discrete delayindependent and delay-dependent control systems are obtained by using the linear matrix inequality （LMI） approach. Judgement of the stability of time-delay systems is transformed to judgement of the feasible solution of an LMI, and hence is solved by use of MATLAB. Numerical simulations verify the validity of the proposed method.     

H_∞ Inverse Optimal Adaptive Fault-Tolerant Attitude Control for Flexible Spacecraft with Input Saturation

An adaptive inverse optimal attitude controller for flexible spacecraft with fault-free actuator is designed based on adaptive control Lyapunov function and inverse optimal methodology subjected to unknown parameter uncertainties,external disturbances and input saturation.The partial loss of actuator effectiveness and the additive faults are considered simultaneously to deal with actuator faults,and the prior knowledge of bounds on the effectiveness factors of the actuators is assumed to be unknown.A fault-tolerant control version is designed to handle the system with actuator fault by introducing a parameter update law to estimate the lower bound of the partial loss of actuator effectiveness faults.The proposed fault-tolerant attitude controller ensures robustness and stabilization,and it achieves H_∞ optimality with respect to a family of cost functionals.The usefulness of the proposed algorithms is assessed and compared with the conventional approaches through numerical simulations.     

THE EDDY LOSSES OF A MAGNETIC THRUST BEARING

Accurate calculations of losses associated with the operation of magnetic bearings are particularly important for high speed applications where the rotor losses are expected to be large and for some particular applications where even low power losses will be critical. Power losses in the magnetic thrust bearing is often neglected, but if there is misaligned in the rotor and bearing, the magnetic field in the thrust bearing is no longer axisymmetric one, or the dynamic control current in the winding is time dependent one, eddy currents are caused to flow inside the conducting material, then the power losses are very important for magnetic bearing design. This paper presents an analytical model of a thrust magnetic bearing, and the magnetic fields, forces and losses of thrust magnetic bearing are calculated. In the calculations the frequency of dynamic control current is up to 1 000 Hz, rotating speed is from 60 rpm to 1 200 rpm, and the non-linearity of material is also taken into consideration. The results shows that if the magnetic field is not saturation, the eddy losses is proportional to dynamic control current frequency and a square function of dynamic control current, and also 5/2 power function of shafts speed.     

Technique of Probability Density Function Shape Control for Nonlinear Stochastic Systems

The shape control of probability density function(PDF) of the system state is an important topic in stochastic systems. In this paper, we propose a control technique for PDF shape of the state variable in nonlinear stochastic systems. Firstly, we derive and prove the form of the controller by investigating the Fokker-PlanckKolmogorov(FPK) equation arising from the stochastic system. Secondly, an approach for getting approximate solution of the FPK equation is provided. A special function including some parameters is taken as the approximate stationary solution of the FPK equation. We use nonlinear least square method to solve the parameters in the function, and capture the approximate solution of the FPK equation. Substituting the approximate solution into the form of the controller, we can acquire the PDF shape controller. Lastly, some example simulations are conducted to verify the algorithm.     

Stochastic optimal control for first-passage failure of nonlinear oscillators with multi-degrees-of-freedom

To enhance the reliability of the stochastically excited structure,it is significant to study the problem of stochastic optimal control for minimizing first-passage failure.Combining the stochastic averaging method with dynamical programming principle,we study the optimal control for minimizing first-passage failure of multidegrees-of-freedom（MDoF）nonlinear oscillators under Gaussian white noise excitations.The equations of motion of the controlled system are reduced to time homogenous difusion processes by stochastic averaging.The optimal control law is determined by the dynamical programming equations and the control constraint.The backward Kolmogorov（BK）equation and the Pontryagin equation are established to obtain the conditional reliability function and mean first-passage time（MFPT）of the optimally controlled system,respectively.An example has shown that the proposed control strategy can increase the reliability and MFPT of the original system,and the mathematical treatment is also facilitated.     

H ∞ parameter identification and H 2 feedback control synthesizing for inflight aircraft icing

Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the principle of aircraft icing and its effects on flight performance. The onboard icing detection equipment can only give the qualitative icing information, but cannot effectively describe how serious the consequences would be. If the icing detection equipment fails, it will cause a serious threat to flight safety. This paper reviews the smart icing system and its fundamental principle. Then based on H∞ theory, an aircraft icing parameter identification method is introduced, and its feasibility is verified by simulation results. Moreover, this method can work normally under noise interference and measurement error. Icing parameter identification method can also test part of aircraft’s stability or control derivatives which would be changed obviously after aircraft icing. Classified by neural networks, the stability or control derivatives’ variation can be mapped to ice parameters’ variation that reflects the severity of aircraft icing. Then H2 state feedback control is designed originally to suppress the impact of noise interference, so aircraft can keep steady after it is iced. Seeing from simulation result of the whole system, it is clear that the system can effectively detect icing parameters and by using feedback control system, it can ensure the safety of aircraft in the flight envelope.     

Controllability, Observability and Stability for a Class of Fractional-Order Linear Time-Invariant Control Systems

IntroductionThe concepts of controllability and observabil-ity,introduced by Kalman[1] ,are of extreme im-portance in control theory and engineering. Thereal objects are generally fractional[2 ] ,however,the control systems used so far are all consideredas integer- order systems.Disregarding the real or-der of the systems was caused mainly by the com-plexity and the absence of adequate mathematicaltools.The fractional calculus theory was devel-oped by a lotof mathematicians and the applicatio…     

Research on an Urban Traffic Control System Based on DGPS

The basic principoles of GPS(Global Positioning System)and DGPS(Differential GPS) are described.The Principle and structure of vehicle navigation systems,and its application to the urban traffic flow guidance are analyzed.Then,an area-corrdinated adaptive control system based on DGPS and a traffic flow guidance information system based on DGPS are put forward,and their working principles and functions are researched.This is to provides a new way for the development of urban road traffic control systems.     

Adaptive robust control for an active heave compensation system

Active heave compensation systems are usually employed in offshore and deep-sea operations to reduce the adverse impact of unexpected vessel’s vertical motion on the response of underwater instruments.This paper presents a control strategy for an active heave compensation system consisting of an electro-hydraulic system driven by a double rod actuator,which is subjected to parametric uncertainties and unmeasured environmental disturbances.Adaptive observer and discontinuous projection type updating law with bounded adaption rate are presented firstly to estimate the uncertain system parameters.Then a similar estimation algorithm is designed by using a multiple delayed version of the system to enhance the performance of parameter observation.A reduced order observer is also introduced to estimate unknown wave disturbances.Using the obtained uncertainty information,the resulting control development and stability analysis are implemented based on the Lyapunov’s direct method and back-stepping technique.The proposed controller guarantees the heave compensation error convergent to a bounded neighborhood around the origin.Simulations illustrate the effectiveness of the proposed control system.     

Geometrical design of blade＇s surface and boundary control of Navier-Stokes equations

In this article a new principle of geometric design for blade＇s surface of an impeller is provided. This is an optimal control problem for the boundary geometric shape of flow and the control variable is the surface of the blade. We give a minimal functional depending on the geometry of the blade＇s surface and such that the flow＇s loss achieves minimum. The existence of the solution of the optimal control problem is proved and the Euler-Lagrange equations for the surface of the blade are derived. In addition, under a new curvilinear coordinate system, the flow domain between the two blades becomes a fixed hexahedron, and the surface as a mapping from a bounded domain in R2 into R3 , is explicitly appearing in the objective functional. The Navier-Stokes equations, which include the mapping in their coefficients, can be computed by using operator splitting algorithm. Furthermore, derivatives of the solution of Navier- Stokes equations with respect to the mapping satisfy linearized Navier-Stokes equations which can be solved by using operator splitting algorithms too. Hence, a conjugate gradient method can be used to solve the optimal control problem.     

Fault Detection Observer Design for LSFDJ： A Factorization Approach

Based on a new special co-inner-outer factorization, a factorization approach for design fault detection observer for LSFDJ was proposed. It is a simple state-space method and can deal with time varying LSFDJ with sensor noise and sensor faults. The performance of the fault detection observer is optimized in an H∞ setting,where the ratio between the gains from disturbance and fault to residual respectively is minimized. The design parameters of the detection observer were given in terms of the solution to the Riccati differential equation with jumps.     

Nonlinear Modeling and Neuro-Fuzzy Control of PEMFC

The proton exchange membrane generation technology is highly efficient, and clean and is considered as the most hopeful “green” power technology. The operating principles of proton exchange membrane fuel cell （PEMFC） system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model and control online. This paper analyzed the characters of the PEMFC; and used the approach and self-study ability of artificial neural networks to build the model of nonlinear system, and adopted the adaptive neural-networks fuzzy infer system to build the temperature model of PEMFC which is used as the reference model of the control system, and adjusted the model parameters to control online. The model and control were implemented in SIMULINK environment. The results of simulation show the test data and model have a good agreement. The model is useful for the optimal and real time control of PEMFC system.