Risk-Informed Model-Free Safe Control of Linear Parameter-Varying Systems

This paper presents a risk-informed data-driven safe control design approach for a class of stochastic uncertain nonlinear discrete-time systems.The nonlinear system is modeled using linear parameter-varying(LPV)systems.A model-based probabilistic safe controller is first designed to guarantee probabilisticλ-contractivity(i.e.,stability and invariance)of the LPV system with respect to a given polyhedral safe set.To obviate the requirement of knowing the LPV system model and to bypass identifying its open-loop model,its closed-loop data-based representation is provided in terms of state and scheduling data as well as a decision variable.It is shown that the variance of the closedloop system,as well as the probability of safety satisfaction,depends on the decision variable and the noise covariance.A minimum-variance direct data-driven gain-scheduling safe control design approach is presented next by designing the decision variable such that all possible closed-loop system realizations satisfy safety with the highest confidence level.This minimum-variance approach is a control-oriented learning method since it minimizes the variance of the state of the closed-loop system with respect to the safe set,and thus minimizes the risk of safety violation.Unlike the certainty-equivalent approach that results in a risk-neutral control design,the minimum-variance method leads to a risk-averse control design.It is shown that the presented direct risk-averse learning approach requires weaker data richness conditions than existing indirect learning methods based on system identification and can lead to a lower risk of safety violation.Two simulation examples along with an experimental validation on an autonomous vehicle are provided to show the effectiveness of the presented approach.

H∞ Tracking Control for Switched LPV Systems With an Application to Aero-Engines

This paper focuses on the H_∞ model reference tracking control for a switched linear parameter-varying(LPV)model representing an aero-engine. The switched LPV aeroengine model is built based on a family of linearized models.Multiple parameter-dependent Lyapunov functions technique is used to design a tracking control law for the desirable H_∞ tracking performance. A control synthesis condition is formulated in terms of the solvability of a matrix optimization problem.Simulation result on the aero-engine model shows the feasibility and validity of the switching tracking control scheme.

An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter

An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.

Novel l_2-l_∞ controller design for LPV discrete time-delay systems

One of the first attempts to derive energy-to-peak performance criteria and state-feedback controller design problem for linear parameter-varying discrete time systems with time delay is provided. Firstly, we present a parameter-dependent l 2-l ∞ performance criterion using a parameter-dependent Lyapunov function. Upon the conditions addressed, an improved parameter-dependent l 2-l ∞ performance criterion is established by the introduction of a slack variable, which exhibits a kind of decoupling between Lyapunov functions and system matrices. This kind of decoupling enables us to obtain more easily tractable conditions for analysis and synthesis problems. Then, the corresponding parameter-dependent state-feedback controller design is investigated upon these performance criteria, with sufficient conditions obtained for the existence of admissible controllers in terms of parameterized linear matrix inequalities. Finally, a numerical example is provided to illustrate the feasibility and advantage of the proposed controller design procedure.

Missile autopilot design based on robust LPV control

This paper proposes an effective algorithm to work out the linear parameter-varying (LPV) framework autopilot for the air defense missile so as to simultaneously guarantee the closed-loop system properties globally and locally, which evidently reduces the number of unknown variables and hence increases the computational efficiency. The notion of 'robust quadratic stability' is inducted to meet the global properties, including the robust stability and robust performance, while the regional pole placement scheme together with the adoption of a model matching structure is involved to satisfy the dynamic performance, including limiting the 'fast poles'. In order to reduce the conservatism, the full block multiplier is employed to depict the properties, with all specifications generalized in integral quadratic constraint frame and finally transformed into linear matrix inequalities for tractable solutions through convex optimization. Simulation results validate the performance of the designed robust LPV autopilot and the proposed framework control method integrating with the full block multiplier approach and the regional pole placement scheme, and demonstrate the efficiency of the algorithm. An efficient algorithm for the air defense missile is proposed to satisfy the required global stability and local dynamical properties by a varying controller according to the flight conditions, and shows sufficient promise in the computational efficiency and the real-time performance of the missile-borne computer system.

A systematic method of smooth switching LPV controllers design for a morphing aircraft

This paper is concerned with a systematic method of smooth switching linear parameter- varying （LPV） controllers design for a morphing aircraft with a variable wing sweep angle. The morphing aircraft is modeled as an LPV system, whose scheduling parameter is the variation rate of the wing sweep angle. By dividing the scheduling parameter set into subsets with overlaps, output feedback controllers which consider smooth switching are designed and the controllers in over- lapped subsets are interpolated from two adjacent subsets. A switching law without constraint on the average dwell time is obtained which makes the conclusion less conservative. Furthermore, a systematic algorithm is developed to improve the efficiency of the controllers design process. The parameter set is divided into the fewest subsets on the premise that the closed-loop system has a desired performance. Simulation results demonstrate the effectiveness of this approach.

LPV modeling and controller design for body freedom flutter suppression subject to actuator saturation

In recent years,the Active Flutter Suppression(AFS)employing Linear ParameterVarying(LPV)framework has become a hot spot in the research field.Nevertheless,the flutter suppression technique is facing two severe challenges.On the one hand,due to the fatal risk of flight test near critical airspeed,it is hard to obtain the accurate mathematical model of the aeroelastic system from the testing data.On the other hand,saturation of the actuator may degrade the closed-loop performance,which was often neglected in the past work.To tackle these two problems,a new active controller design procedure is proposed to suppress flutter in this paper.Firstly,with the aid of LPV model order reduction method and State-space Model Interpolation of Local Estimates(SMILE)technique,a set of high-fidelity Linear Time-Invariant(LTI)models which are usually derived from flight tests at different subcritical airspeeds are reduced and interpolated to construct an LPV model of an aeroelastic system.And then,the unstable aeroelastic dynamics beyond critical airspeed are‘predicted’by extrapolating the resulting LPV model.Secondly,based on the control-oriented LPV model,an AFS controller in LPV framework which is composed of a nominal LPV controller and an LPV anti-windup compensator is designed to suppress the aeroelastic vibration and overcome the performance degradation caused by actuator saturation.Although the nominal LPV controller may have superior performance in linear simulation in which the saturation effect is ignored,the results of the numerical simulations show that the nominal LPV controller fails to suppress the Body Freedom Flutter(BFF)when encountering the actuator saturation.However,the LPV anti-windup compensator not only enhances the nominal controller’s performance but also helps the nominal controller to stabilize the unstable aeroelastic system whenencountering serious actuator saturation.

Dynamic wheeled motion control of wheel-biped transformable robots

Most existing biped robots can only walk with their feet or move by wheels.To combine the best of both worlds,this paper introduces the dynamic wheeled control including wheeled locomotion and in-situ wheel-to-foot(WtF)transformation of a full-sized wheel-biped transformable robot SR600-II.It can traverse on flat surfaces by wheels and transform to footed stance through its switching modules when facing obstacles.For wheeled locomotion,the kinematics considering upper-body lumped center-of-mass(CoM)constraint is first derived.Then,the dynamics of wheeled locomotion is modeled as a wheeled inverted pendulum(WIP)with variables related to the pose of upper body.After that,a parameter-varying linear quadratic regulator(LQR)controller is utilized to enable dynamic wheeled locomotion.For WtF transformation,the WtF balance constraints are first revealed.Then,a WtF transformation strategy is proposed to tackle the problem when robot transforms from wheeled balance state to in-situ biped stance state.It enables the robot to pass by the transition stages in which both wheels and feet touch the ground and to maintain its balance at the same time.Simulations and experiments on the SR600-II prototype have validated the efficacy of proposed dynamic wheeled control strategies for both wheeled locomotion and in-situ WtF transformation.

Gain-scheduling control of a floating offshore wind turbine above rated wind speed

This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.