Fast and smooth clutch engagement control for dual-clutch transmissions

Automotive dual-clutch transmissions use two gear shafts and two clutches to perform automated gear shifts at a high comfort level. The two objectives of the clutch engagement controller are to realize a fast clutch engagement to reduce the gear shifting time, and a smooth clutch engagement to accurately track the demanded torque without a noticeable torque dip. This research work presents a new controller design that explicitly separates the control laws for each objective by introducing clutch engagement phases. Simulations and experiments in a test vehicle show that the control objectives are realized with a robust and relatively simple controller.     

Hybrid extended Fourier series for optimal control of nonlinear algebraic dynamical systems

The paper introduces a new method for finding optimal control of algebraic dynamic systems. The structure of algebraic dynamical systems is nonlinear with quadratic and bilinear terms. A new hybrid extended Fourier series is introduced, and state and control variables of the system are expanded by this series. Moreover, properties of new series are presented, and integration and product operational matrices are obtained. Using operational matrices, optimal control of the systems is converted to a set of simultaneous nonlinear algebraic relations. An illustrative example is included to compare our results with those in the literature.     

Stabilisation of infinite-dimensional bilinear systems using a quadratic feedback control

This article discusses feedback stabilisation of bilinear systems defined on a Hilbert state space. We show that stabilising such a system reduces stabilising only its projection on a suitable subspace. Then we give a new stabilising control that minimises a quadratic cost and allows the decay estimate of the optimal trajectories. An illustrating example is presented.     

Asymptotic methods in the optimal control of distributed systems

A short review of the various problems which arise in connection with the use of asymptotic methods in the optimal control of distributed systems is presented. We consider the cases when the asymptotic analysis comes from the state equation, or from the cost function, or both and also when the state equation is defined in perturbed domains.     

Stochastic optimal control of networked control systems with control packet dropouts

This paper considers the stochastic optimal control problem for networked control systems(NCSs)with control packet dropouts.The proportional plus up to the third-order derivative(PD3)compensation strategy is adopted to compensate for control packet dropouts at the actuator by using the past control packets stored in the buffer.Based on the strategy,a new NCS structure model with packet dropouts is provided,where the packet dropout is assumed to obey the Bernoulli random binary distribution.In terms of the given model,the stochastic optimal control law is proposed. Numerical examples illustrate the effectiveness of the results.     

Dynamic buffer management using optimal control of hybrid systems

This paper studies a dynamic buffer management problem with one buffer inserted between two interacting components. The component to be controlled is assumed to have multiple power modes corresponding to different data processing rates. The overall system is modeled as a hybrid system and the buffer management problem is formulated as an optimal control problem. Different from many previous studies, the objective function of the proposed problem depends on the switching cost and the size of the continuous state space, making its solution much more challenging. By exploiting some particular features of the problem, the best mode sequence and the optimal switching instants are characterized analytically using a variational approach. Simulation results based on real data shows that the proposed method can significantly reduce the energy consumption compared with another heuristic scheme in several typical situations.     

智能交通信号机的设计及其实现

针对我国混合交通流的特点,利用AVR128单片机设计了一种智能交通信号机,给出了信号机各模块的硬件设计方案和软件设计流程图。该信号机采用模块化设计思想,具有硬件自检测和软件抗干扰功能,可实现单点自适应控制和区域协调控制等多种控制方式。实际使用表明,该信号机具有较强的稳定性和通用性,可有效适应我国的混合流交通状况。     

Adaptive control of uncertain pure-feedback nonlinear systems

An adaptive control approach is proposed to solve the globally asymptotic state stabilisation problem for uncertain pure-feedback nonlinear systems which can be transformed into the pseudo-affine form. The pseudo-affine pure-feedback nonlinear system under consideration is with nonlinearly parameterised uncertainties and possibly unknown control coefficients. Based on the parameter separation technique, a novel backstepping controller is designed by adopting the adaptive high gain idea. The proposed control approach could avoid the drawbacks of the approximation-based approaches since no estimators are needed to estimate the virtual and the actual controllers. In addition, it could guarantee globally asymptotic state stabilisation even though there exist nonlinearly parameterised uncertainties in the considered system while comparing to the existing approximation-free approaches. A numerical and a realistic examples are employed to demonstrate the effectiveness of the proposed control method.     

Reliable decentralised control of delayed MIMO plants

Reliable decentralised proportional–integral–derivative controller synthesis methods are presented for closed-loop stabilisation of linear time-invariant plants with two multi-input, multi-output (MIMO) channels subject to time delays. The finite-dimensional part of plants in the classes considered here are either stable or they have at most two poles in the unstable region. Closed-loop stability is maintained with only one of the two controllers when the other controller is turned off and taken out of service.     

Event-triggered sliding mode control for a class of nonlinear systems

ABSTRACT

Event-triggering strategy is one of the real-time control implementation techniques which aims at achieving minimum resource utilisation while ensuring the satisfactory performance of the closed-loop system. In this paper, we address the problem of robust stabilisation for a class of nonlinear systems subject to external disturbances using sliding mode control (SMC) by event-triggering scheme. An event-triggering scheme is developed for SMC to ensure the sliding trajectory remains confined in the vicinity of sliding manifold. The event-triggered SMC brings the sliding mode in the system and thus the steady-state trajectories of the system also remain bounded within a predesigned region in the presence of disturbances. The design of event parameters is also given considering the practical constraints on control execution. We show that the next triggering instant is larger than its immediate past triggering instant by a given positive constant. The analysis is also presented with taking delay into account in the control updates. An upper bound for delay is calculated to ensure stability of the system. It is shown that with delay steady-state bound of the system is increased than that of the case without delay. However, the system trajectories remain bounded in the case of delay, so stability is ensured. The performance of this event-triggered SMC is demonstrated through a numerical simulation.     

The time-invariant linear-quadratic optimal control problem

This paper provides a review of one of the basic problems of systems theory—the general time-invariant optimal control problem involving linear systems and quadratic costs. The problem includes on one hand the regulator problem of optimal control and on the other, the theory of linear dissipative systems, itself central to network theory and to the stability theory of feedback systems. The theory is developed using simple properties of dynamical systems and involves a minimum of ‘hard’ analysis or algebra. It includes a full existence theory of the matrix quadratic equation, of interest in its own right.     

Control relevant identification for robust optimal control

This paper presents an approach to designing the input signal for an identification experiment, in which the process model estimate is to be used to formulate and solve for a robust (in a worst case sense) optimal controller. The input signal is designed to contain the information that is relevant for the end use of the model, that is for control purposes. The proposed approach uses sensitivity analysis to determine the input signal frequencies that are important with respect to a certain measure of achievable controller performance in conjunction with a frequency sampling filter model of the process. Based on the sensitivity analysis, an iterative experimental design methodology is suggested.     

Lossless convexification of a class of optimal control problems with non-convex control constraints

We consider a class of finite time horizon optimal control problems for continuous time linear systems with a convex cost, convex state constraints and non-convex control constraints. We propose a convex relaxation of the non-convex control constraints, and prove that the optimal solution of the relaxed problem is also an optimal solution for the original problem, which is referred to as the lossless convexification of the optimal control problem. The lossless convexification enables the use of interior point methods of convex optimization to obtain globally optimal solutions of the original non-convex optimal control problem. The solution approach is demonstrated on a number of planetary soft landing optimal control problems.     

A graph-theoretic optimal control problem for terminating discrete event processes

Most of the results to date in discrete event supervisory control assume a zero-or-infinity structure for the cost of controlling a discrete event system, in the sense that it costs nothing to disable controllable events while uncontrollable events cannot be disabled (i.e., their disablement entails infinite cost). In several applications however, a more refined structure of the control cost becomes necessary in order to quantify the tradeoffs between candidate supervisors. In this paper, we formulate and solve a new optimal control problem for a class of discrete event systems. We assume that the system can be modeled as a finite acylic directed graph, i.e., the system process has a finite set of event trajectories and thus is terminating. The optimal control problem explicitly considers the cost of control in the objective function. In general terms, this problem involves a tradeoff between the cost of system evolution, which is quantified in terms of a path cost on the event trajectories generated by the system, and the cost of impacting on the external environment, which is quantified as a dynamic cost on control. We also seek a least restrictive solution. An algorithm based on dynamic programming is developed for the solution of this problem. This algorithm is based on a graph-theoretic formulation of the problem. The use of dynamic programming allows for the efficient construction of an optimal subgraph (i.e., optimal supervisor) of the given graph (i.e., discrete event system) with respect to the cost structure imposed. We show that this algorithm is of polynomial complexity in the number of vertices of the graph of the system.Research supported in part by the National Science Foundation under grant ECS-9057967 with additional support from GE and DEC.     

Modification via averaging of partial-energy-shaping control for creating oscillations: cart-pendulum example

We consider the challenging problem of creating oscillations in underactuated mechanical systems. Target oscillatory motions of the indirectly actuated degree of freedom of a mechanical system can often be achieved via a straightforward to design feedback transformation. Moreover, the corresponding part of the dynamics can be forced to match a desired second-order system possessing the target periodic solution (Aracil, J., Gordillo, F., and Acosta, J.A. (2002), ‘Stabilization of Oscillations in the Inverted Pendulum’, in Proceedings of the 15th IFAC World Congress, Barcelona, Spain; Canudas-de-Wit, C., Espiau, B., and Urrea, C. (2002), ‘Orbital Stabilisation of Underactuated Mechanical Systems’, in Proceedings of the 15th IFAC World Congress, Barcelona, Spain). Sometimes, it is possible to establish the presence of periodic or bounded motions for the remaining degrees of freedom in the transformed system. However, typically this motion planning procedure leads to an open-loop unstable orbit and by necessity should be followed by a feedback control design. We propose a new approach for synthesis of a (practically) stabilising feedback controller, which ensures convergence of the solutions of the closed-loop system into a narrow tube around the preplanned orbit. The method is illustrated in detail by shaping oscillations in the inverted pendulum on a cart around its upright equilibrium. The complete analysis is based on application of a non-standard higher-order averaging technique assuming sufficiently high frequency of oscillations and is presented for this particular example.     

Cooperative control design for non-holonomic chained-form systems

Consensus and formation control problems for multiple non-holonomic chained-form systems are solved in this paper. For consensus problem, based on cascaded structure of the chained-form systems, it amounts to solving two consensus subproblems of two linear subsystems transformed from the original system. With the obtained consensus protocols and the method of virtual structure, decentralised formation controllers can then be designed. According to different desired motion patterns of the entire group, both the formation tracking and formation stabilisation problems can be considered. The significance of this paper lies in adapting theories from non-autonomous cascaded systems for cooperative control design for non-holonomic chained-form systems. A unique feature of our proposed solution is that all states can be cooperatively controlled to achieve the desired references for non-holonomic chained-form system. Simulation results are included to illustrate the effectiveness of the proposed methods in solving cooperative control problems of non-holonomic chained-form systems.     

Finite-time boundedness and stabilisation of networked control systems with bounded packet dropout

In this paper, the finite-time boundedness and stabilisation problems of a class of networked control systems (NCSs) with bounded packet dropout are investigated. The main results provided in the paper are sufficient conditions for finite-time boundedness and stability via state feedback. An iterative approach is proposed to model NCSs with bounded packet dropout as jump linear systems (JLSs). Based on Lyapunov stability theory and JLSs theory, the sufficient conditions for finite-time boundedness and stabilisation of the underlying systems are derived via linear matrix inequalities (LMIs) formulation. Moreover, both sensor-to-controller and controller-to-actuator packet dropouts are considered simultaneously. Lastly, an illustrative example is given to demonstrate the effectiveness of the proposed results.     

Distributed optimal control of multiple systems

This article considers distributed optimal control of multiple linear systems. Distributed approximately optimal controllers are proposed for each system with the aid of communications between systems. The proposed controllers make the states of the closed-loop systems exponentially converge to the states of the closed-loop systems with the centralised optimal controllers if the communication digraph is strongly connected. If the communication digraph is switching and there are communication delays, the proposed controllers also make the states of the closed-loop systems exponentially converge to the states of the closed-loop systems with the centralised optimal controllers. Simulation results show effectiveness of the proposed controllers.     

Near optimal decentralised control with a pre-specified degree of stability

In this paper we develop a method for computing near optimal decentralised control with a pre-specified degree of stability for large scale, linear, interconnected dynamical systems. All the calculations in the new method are performed off-line using a three level hierarchical structure. We provide a condition the satisfaction of which ensures that the system has a pre-specified degree of stability. We also show that the control developed using the new method is more stable than the optimal decentralised control obtained by neglecting all interactions between the subsystems.     

非线性离散时间系统的最优终端迭代学习控制

仅利用系统的终端输出误差而不是整个输出轨迹,提出了一种最优终端迭代学习控制方法.控制信号可直接通过终点的误差信息进行更新.主要创新点在于控制器的设计和分析只利用系统量测的I/O数据而不需要关于系统模型的任何信息,并可实现沿迭代轴的单调收敛.在此意义上,所提出的控制器是数据驱动的无模型控制方法.严格的数学分析和仿真结果均表明了所提出方法的适用性和有效性.