Integrated tire slip energy dissipation and lateral stability control of distributed drive electric vehicle with mechanical elastic wheel

Stability and energy consumption have always been important issues in electric vehicle research. Excessive slip energy not only aggravates tire wear, but also consumes energy of electric vehicle. In order to ensure the lateral stability and to reduce the slip energy dissipation of the distributed drive electric vehicle (DDEV) equipped with Mechanical Elastic Wheel (MEW), an integrated framework considering both tire slip energy dissipation and lateral stability control is proposed. The SESC (Slip Energy and Stability Control) is a hierarchical control framework for DDEV with MEW. A PID speed tracking controller and an (Integral Terminal Slide Mode) ITSM controller are designed at the upper-level controller. The ITSM controller can improve the lateral stability of the vehicle by obtaining the desired yaw moment. Speed tracking controller can stabilize the speed of the vehicle and obtain the desired longitudinal force. At the lower-level controller, the brush model of the MEW is proposed to express tire slip energy. In order to reduce the error of the vehicle dynamics and the slip energy dissipation, a mixed objective function including a holistic corner controller (HCC) and a minimum tire slip energy characterization is proposed. The proposed control framework is verified by Carsim and Matlab/Simulink under emergency simulation conditions. The simulation results show that the SESC based method can improve the lateral stability of DDEV with MEW effectively, and has better performance compared with fuzzyPID+AD based method. Meanwhile, the SESC achieves less slip energy than conventional torque distribution method.     

Robust smooth transfer for tilt-rotor aircraft under the asynchronous switching

To achieve the flight mode transfer of the tilt-rotor aircraft, this paper develops a smooth switching method for an weighted L₂ robust asynchronously switched system. Considering the asynchronous phenomenon that exists in the switching control of the tilt-rotor aircraft, first, a sufficient condition for the existence of the sub-controller is derived, which guarantees the exponential stability and weighted L₂ performance. Besides, the on-line system and the off-line system are separately employed to realize the continuity of the control input signals, which further improve the transient performance and smoothness of the asynchronously switched system. The simulations on the tilt-rotor aircraft verify the effectiveness and applicability of the proposed method.     

Stabilization of a class of nonlinear parametrized systems by a flexible switching adaptive backstepping

In this paper, we consider global adaptive feedback control of nonlinear systems with unknown parameters entering nonlinearly. Such unknown parameters are also not required to lie in a known compact set. Unlike previous results, our proposed adaptive controller is a new double dynamical switching-type controller in which the controller parameter is tuned in a flexible switching manner via a monotonically decreasing switching logic and the controller combines the traditional adaptive theorem with the switching scheme perfectly. Global stability results of the closed-loop system have been proved.     

Sampled-data predictive control for uncertain jump systems with partly unknown jump rates and time-varying delay

This paper presents a sampled-data predictive control strategy for a class of uncertain continuous-time Markovian jump linear system (MJLS) with time-varying delay. The system under consideration covers MJLS with completely known jump rates and arbitrary switched linear system. The predictive formulation utilizes both off-line and on-line optimization paradigms. The feasibility of the control scheme and the stability of the closed-loop system are investigated by introducing a modified stochastic invariant ellipsoid. The conditions for the existence of a stabilizing optimal controller for the underlying system are obtained via the semi-definite programming (SDP). A numerical example is given to verify efficiency and potential of the developed approach.     

Design and implementation of a new sliding mode controller on an underactuated wheeled inverted pendulum

In this paper, a sliding mode controller (SMC) is proposed for control of a wheeled inverted pendulum (WIP) system, which consists of a pendulum and two wheels in parallel. The control objective is to use only one actuator to perform setpoint control of the wheels while balance the pendulum around the upright position, which is an unstable equilibrium. When designing the SMC for the WIP system, various uncertainties are taken into consideration, including matched uncertainties such as the joint friction, and unmatched uncertainties such as the ground friction, payload variation, or road slope. The SMC proposed is capable of handling system uncertainties and applicable to general underactuated systems with or without input coupling. For switching surface design, the selection of the switching surface coefficients is in general a sophisticated design issue because those coefficients are nonaffine in the sliding manifold. In this work, the switching surface design is transformed into a linear controller design, which is simple and systematic. By virtue of the systematic design, various linear control techniques, such as linear quadratic regulator (LQR) or linear matrix inequality (LMI), can be incorporated in the switching surface design to achieve optimality or robustness for the sliding manifold. To further improve the WIP responses, the design of reference signals is addressed. The reference position for the pendulum is adjusted according to the actual equilibrium of the pendulum, which depends on the size of the friction and slope angle of the traveling surface. A smooth reference trajectory for the setpoint of the wheel is applied to avoid abrupt jumps in the system responses, meanwhile the reaching time of the switching surface can be reduced. The effectiveness of the SMC is validated using intensive simulations and experiment testings.     

Adaptive sliding mode trajectory tracking control of robotic airships with parametric uncertainty and wind disturbance

An adaptive sliding mode trajectory tracking controller is developed for fully-actuated robotic airships with parametric uncertainties and unknown wind disturbances. Based on the trajectory tracking model of robotic airships, an adaptive sliding mode control strategy is proposed to ensure the asymptotic convergence of trajectory tracking errors and adaptive estimations. The crucial thinking involves an adaptive scheme for the controller gains to avoid the off-line tuning. Specially, the uncertain physical parameters and unknown wind disturbances are rejected by variable structure control, and boundary layer technique is employed to avoid the undesired control chattering phenomenon. Computer experiments are performed to demonstrate the performance and advantage of the proposed control method.     

Distributed formation control for multiple quadrotor UAVs under Markovian switching topologies with partially unknown transition rates

This paper addresses distributed formation control for a group of quadrotor unmanned aerial vehicles (UAVs) under Markovian switching topologies with partially unknown transition rates. Instead of the general stochastic topology, the graph is governed by a set of Markov chains to the edges, which can recover the traditional Markovian switching topologies in line with the practical communication network. Extended high gain observers (EHGOs) are constructed with a two-time-scale format to deal with the issue of nonlinear input coefficients, so that there could be a higher estimation precision of the system uncertainties. To impel multiple quadrotor UAVs to achieve a predesigned formation shape, a modified integral sliding mode (ISM) control protocol is proposed here with a multi-time-scale structure, which allows independent analysis of the dynamics in each time scale. The stability proof for the system state space origin is derived from the singular perturbation method and Lyapunov stability theory. In addition, the introduced ISM controller can deal with the time varying desired references with the bounded accelerations and is robust to the disturbances. Finally, simulations on six quadrotor UAVs are given to verify the effectiveness of the theoretical results.     

Robust gain-scheduled output feedback yaw stability control for in-wheel-motor-driven electric vehicles with external yaw-moment

This paper presents a robust gain-scheduled output feedback yaw stability H_∞ controller design to improve vehicle yaw stability and handling performance for in-wheel-motor-driven electric vehicles. The main control objective is to track the desired yaw references by managing the external yaw moment. Since vehicle lateral states are difficult to obtain, the state feedback controller normally requires vehicle full-state feedback is a critical challenge for vehicle lateral dynamics control. To deal with the challenge, the robust gain-scheduled output feedback controller design only uses measurements from standard sensors in modern cars as feedback signals. Meanwhile, parameter uncertainties in vehicle lateral dynamics such as tire cornering stiffness and vehicle inertial parameters are considered and handled via the norm-bounded uncertainty, and linear parameter-varying polytope vehicle model with finite vertices is established through reducing conservative. The resulting robust gain-scheduled output feedback yaw stability controller is finally designed, and solved in term of a set of linear matrix inequalities. Simulations for single lane and double lane change maneuvers are implemented to verify the effectiveness of developed approach with a high-fidelity, CarSim^®, full-vehicle model. It is confirmed from the results that the proposed controller can effectively preserve vehicle yaw stability and lateral handling performance.     

Stability analysis and control synthesis for linear systems with non-symmetrical input saturation

This paper studies the stability and control problem of linear systems with non-symmetrical input saturation. A system with non-symmetrical input saturation is transformed into a system with switching symmetrical input saturation. A switching controller is designed based on a parametric algebra Riccati equation, dwell time and the equivalent switched system. Exponential stability is guaranteed with the proposed switching controller. The main advantages of the proposed method lie in reducing the conservatism caused by directly using symmetrical input saturation control and increasing the state convergent speed. The designed controller can be computed easily by solving the Riccati equation. Numerical examples are provided to demonstrate the effectiveness of the proposed method.     

Periodic sampled-data-based dynamic model control of switched linear systems

Sampled-data control as an effective mean of digital control has shown its prominent superiority in most practical industries and a zero-order holder (ZOH) is often introduced to maintain continuity of control in the field of sampled-data control system. However, it decreases the control accuracy in a certain extent since the state will be held invariably within each sampling interval. In order to improve the control accuracy, this paper proposes a dynamic model-based control strategy instead of ZOH for a class of switched sampled-data control systems. The model, which is built by abstracting the plant knowledge, is located at the controller side. The controller is set up based on the model state and it provides control input to the switched system. A fixed sampling period is adopted, under which a hybrid-dwell time switching condition is revealed by taking into account asynchronous switching. With reasonable design of switching condition, exponential stability of the closed-loop system can be guaranteed. Finally, advantages of our proposed method are presented through a numerical example by comparing with the result of ZOH-based control.     

Reliable control based on dual control for ARMAX system with abrupt faults

This paper studies the reliable control problem for abrupt faults of autoregressive moving average with exogenous input (ARMAX) system. A set of models are used to cover the potential dynamics of the system and for each model minimum variance control (MVC) is designed. By taking the a-posteriori probabilities of models as weight coefficients, a multi-model reliable control (MMRC) is proposed. If the system is normal, MMRC is MVC. When faults occur, the controller can quickly learn the true model of system and degenerate into the corresponding MVC by adjusting weight coefficients, which ensures the acceptable performance of the system. The effectiveness of MMRC is verified by a numerical simulation. In addition, since MMRC is a fusion of control law of each model, it indicates that soft switching is implemented and the jitter to system due to hard switching can be avoided.     

A yaw stability-guaranteed hierarchical coordination control strategy for four-wheel drive electric vehicles using an unscented Kalman filter

A novel hierarchical coordination control strategy (HCCS) is offered to guarantee the stability of four-wheel drive electric vehicles (4WD-EVs) combining the Unscented Kalman filter (UKF). First, a dynamics model of the 4WD-EVs is established, and the UKF-based estimator of sideslip angle and yaw rate is constructed concurrently. Second, the equivalent cornering stiffness coefficients are jointly estimated to consider the impact of vehicle uncertainty parameters on the estimator design. Afterwards, a HCCS with two-level controller is presented. The sideslip angle and yaw rate are controlled by an adaptive backstepping-based yaw moment controller, and the computational burden is relieved by an improved adaptive neural dynamic surface control technology in the upper-level controller. Simultaneously, the optimal torque distribution controller of hub motors is developed to optimize the adhesion utilization ratio of tire in the lower-level controller. Finally, the proposed HCCS has shown effective improvement in the trajectory tracking capability and yaw stability of the 4WD-EVs under various maneuver conditions compared with the traditional Luenberger observer-based and the federal-cubature Kalman filter-based hierarchical controller.     

Design of non-parametric process-specific optimal tuning rules for PID control of flow loops

The problem of designing optimal process-specific rules for non-parametric tuning is undertaken in the paper. It is shown that producing non-parametric process-specific optimal tuning rules for PID controllers leads to the problem that can be characterized as optimization under uncertainty. This happens due to the fact that tuning rules, unlike tuning constants, are produced not for a particular process or plant model but for a set of models from a certain domain. The novelty of the proposed approach is that the problem of obtaining optimal tuning rules for a flow process is formulated and solved as a problem of optimization of an integral performance criterion parametrized through values that define the domain of available process models. The considered non-parametric tuning assumes the use of the modified relay feedback test (MRFT) recently proposed in the literature. It allows one to tune the PID controller satisfying the requirements to gain or phase margins that is achieved through coordinated selection of tuning rules and test parameters. This approach constitutes a holistic approach to tuning. In the present paper, optimal tuning rules coupled with MRFT, for flow loops, are proposed. Final results are presented in the form of tables containing coefficients of optimal tuning rules for the PI controller, obtained for a number of specified gain margins. The produced non-parametric tuning rules well agree with the practice of loop tuning.     

基于模糊控制的PID控制器研究

在工业控制过程中,由于被控对象具有时变、非线性、不确定等因素,常规PID控制算法难以满足控制要求。本文设计了一种模糊PID控制器可实现对该类工业对象的控制,利用模糊推理在线整定PID控制器的3个参数Kp、Ki、Kd。通过仿真实验,表明该控制器取得了较好的快速性和稳定性。     

An off-line approach for output feedback robust model predictive control

For constrained linear parameter varying systems subject to bounded disturbances and noises, this article investigates an off-line output feedback robust model predictive control approach. The sub-observer gains with robust positively invariant sets, and sub-controller gains with robust control invariant sets are simultaneously off-line optimized and stored in a look-up table. According to real-time estimation error bounds and estimated states, the time-varying sub-observer gains and sub-controller gains are on-line searched. The proposed off-line output feedback robust model predictive control approach with the guarantee of nested robust positively invariant sets and robust control invariant sets in theory reduces the on-line computational burden.     

Stabilization of switched delay systems with polytopic uncertainties under asynchronous switching

In this paper, the problem of stabilization for a class of switched delay systems with polytopic type uncertainties under asynchronous switching is investigated. When the switching of the controllers has a lag to the switching of subsystems, i.e. the switching signal of the switched controller involves delay, parameter-dependent Lyapunov functionals are constructed, which are allowed to increase during the running time of active subsystems with the mismatched controller. Based on the average dwell time method, sufficient conditions for exponential stability are developed for a class of switching signals. Finally, a river pollution control problem is given to demonstrate the feasibility and effectiveness of the proposed design techniques.     

Adaptive control for uncertain nonlinear time-delay systems in a lower-triangular form

In the presence of uncertain time-varying control coefficients, structuring parameter uncertainty and unknown state time delay, this paper proposes a continuous feedback control scheme for highly nonlinear systems without extra nonlinear growth restriction. An expansion of the backstepping method is presented based on dynamic gains and tuning functions. By Lyapunov–Krasovskii functionals, a delay-free controller is designed to regulate the original system states to zero with the other states being globally bounded.     

Switching resilient control scheme for cyber-physical systems against DoS attacks

This paper investigates the problem of resilient control for cyber-physical systems (CPSs) described by T-S fuzzy models. In the presence of denial-of-service (DoS) attacks, information transmission over the communication network is prevented. Under this circumstance, the traditional control schemes which are proposed based on perfect measurements will be infeasible. To overcome this difficulty, with the utilization of an equivalent switching control method, a novel gain-switched observer-based resilient control scheme is proposed. According to whether the DoS attack is activated, two different controller synthesis conditions are given by combining the information of the tolerable DoS attacks. In addition, a quantitative relationship between the resilience against DoS attacks and the obtained disturbance attenuation level is revealed, which is helpful for balancing the tradeoff between the abilities to tolerate DoS attacks and attenuate the influence of external disturbance. Finally, simulation results are provided to verify the effectiveness of the proposed switching control scheme.     

Varying Zonotopic tube RMPC with switching logic for lateral path tracking of autonomous vehicle

Model mismatch caused by strong nonlinearity and other factors will severely impact the lateral path tracking control in Autonomous Vehicles (AVs) under extreme conditions. Previous studies have focused on guaranteeing robust stability under possible uncertainty realizations through Tube-based Robust Model Predictive Control (TRMPC). However, three deficiencies in TRMPC applications are revealed: unknown disturbance set, simple rigid tube, and excessive conservatism. In this paper, a novel scheme named Varying Zonotopic TRMPC with Switching Logic (SVTMPC) is developed to overcome these limitations. Firstly, a zero steady-state error dynamic model is established, and a new update mechanism of the nominal state is devised to determine the unknown internal disturbance set of the AV system. Secondly, zonotopic representation of all defined sets is used to construct the prediction model, as well as a flexible tube with varying cross-sections is naturally designed to overcome excessive conservation and non-solution of Quadratic Programming (QP). Finally, a switching logic between conservative and radical strategies improves tracking performance under conventional conditions without compromising robust stability. Numerical simulation through three scenarios shows that the SVTMPC controller can comprehensively improve robust stability and adaptability compared with MPC and TRMPC. Hardware-in-the-Loop (HIL) experiment verifies the effectiveness and real-time of the SVTMPC controller.