This paper investigates the cooperative output regulation problem for heterogeneous linear multiagent systems under fixed communication graphs via event-triggered control. A fully distributed event-triggered dynamic output feedback control law is proposed based on the feedforward design approach. At the same time, a fully distributed dynamic event-triggering mechanism is designed so that each agent can determine when to broadcast its information to its neighbors. Compared with existing related results, both the control law and the event-triggering mechanism in this paper are independent of any global information. It is shown that with the proposed dynamic event-triggered control strategy, the cooperative output regulation problem can be solved in a fully distributed manner by intermittent communication. Moreover, Zeno behavior can be strictly ruled out for each agent. Finally, the effectiveness of the proposed dynamic event-triggered control strategy is validated by a numerical example.
This paper deals with the robust control problem for linear systems with both gain and time constants variations under fractional order PI λ D μ controller. A robustness specification to the parameters variations is proposed. For those systems with more than one uncertain time constant, the robustness specifications are analyzed and simplified. To minimize the phase offset nearby the crossover frequency, the PI λ D μ parameters tuning is formulated as a nonlinear optimization problem with the specifications and controller structure constraints, meanwhile the initial values of optimization is preprocessed by solving nonlinear equations. Numerical examples have illustrated the effectiveness of the tuning method and advantages of the proposed PI λ D μ controller.
Hierarchical control architectures are a common approach when hydraulic systems are under study; provided their multi-domain nature, the control scheme is commonly split into different hierarchical levels each one associated with a particular physical domain. This paper presents the application of a model-based control structure called Embedded Model Control (EMC) when a hierarchical scheme is implemented on an electro-hydraulic proportional valve. The overall control consists of two hierarchical loops: the inner loop is the solenoid current regulator with a closed loop bandwidth close to 1 kHz. The outer loop is a position tracking control, in charge of the accurate positioning of the spool with respect to valve openings. The paper addresses the outer loop, i.e., the tracking of mechanical spool position by using the EMC. Analysis and synthesis are presented as well as experimental results obtained from a test rig provided by an industrial manufacturer.
In order to realize tracking control for underactuated surface vessels with parameter uncertainties and external disturbances, a nonsingular terminal sliding mode method was proposed. The controller was divided by backstepping method into the kinetic part and the dynamic part. In the kinetic process, the reference surge and sway velocities are employed as the virtual control law in stabilizing the position errors. In the dynamic process, the virtual control law was considered the new tracking target, and the real control law was designed by the nonsingular terminal sliding-mode method to realize the tracking control of the reference velocities. This method can not only guarantee the position tracking error converge finite time, but also ensure yawing motion is BIBO stable. Eventually, simulation experiment of real ship is performed. Results validate the proposed controller can achieve fast tracking control of USV in finite time under parameter uncertainties and external disturbances.
In order to realize tracking control for underactuated surface vessels with parameter uncertainties and external disturbances, a command filter feedback combined with sliding mode method is proposed. The tracking error equations are established based on CFB, which puts tracking control into stabilize surge speed and course angle error using transformation equation. Then, a nonlinear sliding mode controller is designed based on integration ideas. The problem of analytical and numerical differentiation of the virtual control laws is overcome, chattering of control input is circumvented, and the static error and overshoot are decreased. The results of simulation experiments indicate that the controller is robust against the systemic variations and time-varying external disturbances. Moreover, the tracking control with high tracking precision can be achieved by the proposed control method.
Recently, the double generating function method for finite-time linear optimal control problems was proposed. It gives a family of optimal trajectories for different boundary conditions directly. This paper applies it to a compass gait biped robot to generate optimal gaits on the level ground. It allows the robot to obtain optimal gaits to reach the designed location with the designed velocity for every step with almost none online computation. It can also give optimal cycle gaits for different step lengths and different time periods. Furthermore, some simulation results show the effectiveness of the double generating function method for optimal gaits generation of biped walking robots.
An adaptive compensation control law is designed for a class of multi-input multi-output (MIMO) nonlinear minimum phase systems with actuator failures. Based on the differential geometry feedback linearization method, PPB and backstepping technique, an adaptive compensation tracking control scheme is designed for the system with actuators lock in space and loss of effectiveness failures. The proposed control law can guarantee that the closed-loop system with actuator failures is stability and asymptotically tracks the given reference signals, and the system transient performance is guaranteed. Simulation results demonstrate the effectiveness of the proposed method.
The exponential passive filtering problem is studied for neutral-type neural networks with time-varying discrete and distributed delays. Based on the passive theory, the sufficient condition for the existence of the exponential passive filter is given. By introducing an appropriate Lyapunov-Krasovskii functional and using Jensen's inequality techniques to deal with its derivative, the criterion which ensures error dynamic system to be strictly exponentially passive is presented in the form of nonlinear matrix inequality. In order to solve the nonlinear problem, a cone complementarity linearization (CCL) algorithm is proposed. An example is given to demonstrate the effectiveness of the proposed criterion.
This paper proposes a modified subspace aided data-driven fault detection method for linear time-invariant systems. The main merit of this method lies in the avoidance of identifying the mechanism-based model of a system. Inspired by subspace identification method, we construct parameterized matrices of residual signal directly from input and output data without any prior knowledge about mechanisms of a plant. Modified measures are adopted to reduce computational complexity of the algorithm. Fault detection then can be implemented successfully. Simulation studies on the benchmark of Tennessee Eastman process demonstrate the validity of the proposed approach.
Linear active disturbance rejection control (LADRC) method is investigated for the load frequency control (LFC) of power systems. Considering the model and the structure of the system, a second-order LADRC is adopted and the design procedure is introduced. It is found that LADRC is a model-independent control method with only two tuning parameters, thus it is very practical in industrial control. Simulation examples show that LADRC can damp the load disturbance very well but there are some limitations in the LADRC method.
In this paper, we consider an acyclic rigid formation control problem with a group of mobile autonomous agents. The formation is generated via a Henneberg sequence operation, where there is one global leader which does not follow any other agents, one first-follower which only follows the global leader, and besides each agent has at most two leaders. Under the acceleration constraint of the global leader, distributed formation control laws are proposed for the followers which only utilize the relative distance measurement. The control law of the first-follower is also proposed which needs to know the velocity of the global leader and the relative distance between the global leader and itself. The asymptotical stability of the formation is also proved via Lyapunov function method. Simulation experiments are conducted and the results illustrate the effectiveness of the proposed formation control approach.
This paper addresses stabilization issue of switched nonlinear systems where each mode may undergo both stable and unstable behaviors over the time due to the variation of uncertain parameters. Two stabilizability conditions as well as a state-dependent stabilization switching law are proposed. The new result is applied to the control of nonlinear plant via switching of multiple redundant controllers in the presence of uncertain time-varying parameters in each controller. A spacecraft attitude control example verifies the practical motivation and the efficiency of the proposed approaches.
Feature selection and extraction is one of the most important and essential problems in pattern classification. The basic task of feature selection and extraction is how to obtain the most useful and important features by selection or transformation, so the evaluation of feature spaces is needed. The traditional feature space evaluation approaches are always based on the discernibility measures directly defined over the feature spaces of samples. A new feature space evaluation approach is proposed. The original feature spaces of samples are first transformed to the evidential spaces. Then by using distance of evidence, the evidential discernibility measure is defined to indirectly describe the discernibility of the original feature spaces. Experimental results show the rationality and efficiency of the proposed approach.
This paper focuses on the problem of adaptive output feedback stabilization for a class of stochastic nonlinear system with unknown control directions. By using a linear state transformation, the unknown control coefficients are lumped together, such that the original system is transformed to a new system for which control design becomes feasible. By employing the input-driven observer, a novel adaptive neural network (NN) output-feedback controller which only contains one adaptive parameter is developed for such systems by using backstepping technique and NNs' parameterization. The proposed control design guarantees that all the signals in the closed-loop systems are 4-moment semi-globally uniformly ultimately bounded.
The attitude tracking control problem for satellites with constrained control inputs, external disturbances and uncertain inertia parameters is investigated in this paper. A bounded robust adaptive state feedback controller is designed by using properties of the hyperbolic tangent function. It is proved via Lyapunov stability theory that angular velocity errors of the closed-loop system tend to zero asymptotically, attitude errors converge to a preset small neighborhood of the origin by choosing controller parameters properly and designed inputs satisfy the constraint. The simulation results demonstrate that the effects of unknown inertia and external disturbances can be suppressed by the proposed approach under constrained control inputs.
Improving divert capability of interceptor in high altitude situation with the help of thrusters is quite important way to increase the agility and hit accuracy. This paper concerns direct force assignment logic and method for well coordinating with aerodynamic force. A predictive miss distance computation method was introduced by taking target constant acceleration maneuvering into consideration. Direct force commend was computed from miss distance in the light of reducing predictive miss distance leading missile to hit target, and aero force was used to correct remainder miss distance based on predictive guidance law. Thus, a thrust-aerodynamic-force blended guidance strategy was developed by assigning direct and aero force in different way. The proposed method was compared with aerodynamic force controller with classic proportional navigation guidance (PNG) and thrust-aerodynamic-force blended control strategy. Simulation results show that direct forces is very helpful to acquire high hit precision, and strategy developed is more fuel-saving comparing to thrust-aerodynamic-force blended control strategy.
This paper studies the problems of stability for sampled-data control systems and networked control systems (NCSs) with state feedback. First, a new approach to stability analysis of sampled-data systems is proposed, which is based on defining a new type of Lyapunov-Krasovskii functional (LKF), and combining an iterative convex combination technique with a new enlargement scheme. A less conservative stability criterion depending on both lower and upper bounds of sampling intervals is obtained. Then, the approach is extended to NCSs. By clarifying the relationship of the network-induced delay and the executive duration, less conservative and less complex stability criterion is also obtained. Finally, some illustrative examples are given to show the effectiveness and the improvement of the proposed method.
Unmanned Ground Platform (UGP) is a fundamental part of future transportation and military system. However, it still faces lots of difficulties in obtaining a real-time and precise understanding on non-structured natural environment. In this paper, to assist UGP for a better perception of non-structured natural environment, we propose a dynamical clustering algorithm based on model-hierarchy to construct the real map from non-structured environment features. The proposed algorithm first classifies data points based on a simplified model of environment features. Then, various features are extracted for each class. Finally, a dynamic hierarchical clustering algorithm is utilized where an evaluation metric is introduced to control the cluster number automatically. The proposed algorithm can not only eliminate the influences brought by 3D laser point cloud, but also retain the advantages of classic CURE algorithm that can recognize non-balled area. Moreover, this algorithm is self-adaptive to irregular terrace features and independent of settings for initial number of clusters. In the experimental section, the algorithm is tested on the point cloud data obtained from 3D laser radar. The result demonstrates the effectiveness and feasibility of the algorithm.
This paper presents a method to graphically compute all feasible gain margin (GM) and phase margin (PM) specifications-oriented PID controllers for two-input and two-output interactive and time delay (TITOTD) control systems. The considered TITOTD control system is first decomposed into two decoupled single input and single output time delay (SISOTD) systems. Two gain-phase margin testers are added in the forward parts of the two SISOTDs. The gain-phase margin tester method, the stability equation method, and the parameter plane method are exploited to perform GM and PM analysis in the parameter plane. Boundaries for stability and for pre-specified GM and PM can be portrayed in the parameter plane. All feasible GM and PM specifications-oriented PID controllers can be graphically computed. For validity verification, two independent PI/ PID controllers are designed for each decoupled subsystem to achieve the desired GM and PM, and the performance is verified on the original interactive TITOTD control system. An illustrative example cited from the literature is given to show the effectiveness of the proposed method.
