IET Control Theory & Applications
Volume 15, Issue 11
https://ietresearch.onlinelibrary.wiley.com/toc/17518652/2021/15/11
Research Article
Coordinated collision avoidance for multi-vehicle systems based on collision time
Yu, Hongjun, Wang; YingLiang, Lihua; Shi, Peng
https://doi.org/10.1049/cth2.12133
Vehicles have irregular shapes and inter-vehicle coordination is not a trivial task. Based on the distributed-system framework, this paper studies multi-vehicle control and coordinated obstacle avoidance for multiple autonomous vehicles with irregular shapes. The goal is to reach target points without collisions. The proposed approaches are based on collision time, which is calculated using vehicles' irregular shapes. The approaches have two parts. The first part enables a number of vehicles to reach the target points. The second part enables collision avoidance, which includes inter-vehicle collisions and vehicle-to-obstacle collisions. Speed regulation approach is proposed to change the speeds, and frequency-modulation approach is proposed to update control commands at varying steps, and a combined approach is also proposed. Simulation examples are set to verify the effectiveness of the proposed approaches.
Virtual tracking control of underwater vehicles based on error injection and adaptive gain
Liu, Xing; Zhang, Mingjun; Yao, Feng; Yin, Baoji
https://doi.org/10.1049/cth2.12134
An improved virtual tracking control scheme is proposed based on error injection and adaptive gain for underwater vehicles in the presence of a large initial tracking error and external disturbances. To relieve the effect caused by a large initial tracking error, the developed control scheme is achieved based on two closed-loop systems. Specifically, a virtual closed-loop system is constructed based on an approximate dynamic model of an underwater vehicle, while an actual closed-loop system is built with a real underwater vehicle. Firstly, in order to improve the tracking precision of the virtual tracking control scheme, an auxiliary variable produced by a first-order filter is injected into a virtual tracking error in the virtual closed-loop system. And then, the virtual trajectory provided by the virtual closed-loop system is followed by the actual closed-loop system. In the actual closed-loop system, a modified sliding mode surface is designed to achieve the finite-time stability, while the control gains can be on-line adjusted based on the tracking performance. Finally, the effectiveness and feasibility of the proposed control scheme are demonstrated by case studies on an underwater vehicle subject to different external disturbances.
Fault detection for asynchronous T–S fuzzy networked Markov jump systems with new event-triggered scheme
Aslam, Muhammad Shamrooz; Li, Qianmu; Hou, Jun
https://doi.org/10.1049/cth2.12136
In this article, an adaptive event-triggered fault detection problem for the asynchronous Takagi?Sugeno fuzzy networked Markov jump systems is investigated based upon the time-varying delays. The purpose of designing a fault detection filter is to detect the fault signal under the influence of disturbance with network transmission. In the design process, one essential factor, time-varying delay in the fuzzy filter with appearing in the residual signal, is taken into consideration. In order to rationally utilise network resources and elaborately avoid unnecessary continuous monitoring, an adaptive event-triggered scheme is designed to guarantee the Takagi?Sugeno fuzzy networked Markov jump systems. Thus it helps to lower the energy consumption of communication while ensuring the performance of the system. Different from the conventional triggering mechanism, in this article, the parameters of the triggering function are based on a new adaptive law which is obtained online rather than a predefined constant. Based on the associated Lyapunov stability theory and appropriate inequality, some sufficient criteria in the form of linear matrix inequalities are obtained to ensure the stability of the resulting error system. Finally, a tunnel diode example is employed to illustrate the effectiveness of the proposed methods.
A combined model reference adaptive control law for multirotor UAVs
Abdul Ghaffar, Alia Farhana; Richardson, Thomas; Greatwood, Collin
https://doi.org/10.1049/cth2.12137
Model reference adaptive control (MRAC) offers the potential to adapt in real-time to changes in the performance of small unmanned air vehicles. There are significant challenges with their use, however, primarily in the implementation and assurance of long-term system stability. This paper presents flight test results for a combined model reference adaptive control (CMRAC) law applied to the height control loop of a multirotor. Key features include the implementation of CMRAC with a baseline controller allowing for in-flight switching between the two; the use of an augmented state to improve the tracking performance and a CMRAC implementation that provides a shorter transient phase, faster parameter convergence, and closer tracking of the desired reference model response when compared with standard MRAC. With the current exponential growth of interest in unmanned air vehicles, the potential benefits of using CMRAC for control system development are significant, particularly for new vehicles with short development and testing phases and in cases where there are significant configuration changes in flight or prior to rapid deployment.
Observer-based fuzzy adaptive control for MIMO nonlinear systems with non-constant control gain and input delay
Zhao, Jipeng; Tong, Shaocheng; Li, Yongming
https://doi.org/10.1049/cth2.12138
In this work the fuzzy adaptive control issue is investigated for multiple-input multiple-output (MIMO) uncertain nonlinear systems in strict-feedback form. The controlled systems under consideration of this work contain the immeasurable states, unknown control gain functions and input time delays. The immeasurable states are estimated by constructing a fuzzy state observer, and the uncertain nonlinear functions are approximated by utilizing the fuzzy logic systems (FLSs). In addition, the Pade approximation method is employed to handle the input time delays problem. An observer-based fuzzy adaptive centralized control algorithm is presented by employing the adaptive backstepping control design technique and constructing the Logarithm Lyapunov functions. The designed fuzzy adaptive robust control algorithm can make sure that all signals in the closed-loop system are semi-globally uniformly ultimately boundedness (SGUUB). Finally, a numerical simulation example and a practical system example are considered to testify the availability of the designed centralized controllers.
Distance-based formation control for multi-lane autonomous vehicle platoons
Zheng, Yajun; Wang, Qingling; Cao, Dongpu; Fidan, Baris; Sun, Changyin
https://doi.org/10.1049/cth2.12139
This paper investigates the formation control of connected autonomous vehicle (CAV) platoons moving in multi lanes using distance-based formation control techniques based on rigid graphs and V2V communication. A hierarchical architecture is proposed to decompose the cooperative control into velocity planning and vehicle dynamic control. A new velocity planning method is first developed via a distributed distance-based formation controller so that each vehicle can keep platoon and change lane. Then, for the vehicle dynamics with nonlinearities and bounded disturbances, an adaptive controller is designed for regulating driving/braking torque to achieve the longitudinal velocity output of the velocity planner. The steering controller is designed to adjust the yaw angle of each vehicle to track and change lanes. Furthermore, stability analysis is conducted based on the Lyapunov theory. Finally, the applications of the proposed control designs to various of automated highway system (AHS) scenarios including lane-change, curve lane and platoon overtaking, are simulated and numerically analysed to validate the effectiveness of theoretical results.
A control structure for ambidextrous robot arm based on Multiple Adaptive Neuro-Fuzzy Inference System
Mukhtar, Mashood; Khudher, Dhayaa; Kalganova, Tatiana
https://doi.org/10.1049/cth2.12140
This paper presents the novel design of an ambidextrous robot arm that offers double range of motion as compared to dexterous arms. The arm is unique in terms of design (ambidextrous feature), actuation (use of two different actuators simultaneously: Pneumatic Artificial Muscle (PAM) and Electric Motors)) and control (combined use of Proportional Integral Derivative (PID) with Neural Network (NN) and Multiple Adaptive Neuro-fuzzy Inference System (MANFIS) controller with selector block). In terms of ambidextrous robot arm control, a solution based on forward kinematic and inverse kinematic approach is presented, and results are verified using the derived equation in MATLAB. Since solving inverse kinematics analytically is difficult, Adaptive Neuro Fuzzy Inference system (ANFIS) is developed using ANFIS MATLAB toolbox. When generic ANFIS failed to produce satisfactory results due to ambidextrous feature of the arm, MANFIS with a selector block is proposed. The efficiency of the ambidextrous arm has been tested by comparing its performance with a conventional robot arm. The results obtained from experiments proved the efficiency of the ambidextrous arm when compared with conventional arm in terms of power consumption and stability.
Data-driven urban traffic model-free adaptive iterative learning control with traffic data dropout compensation
Li, Dai; Hou, Zhongsheng
https://doi.org/10.1049/cth2.12141
In this paper, to fully utilize the urban traffic flow characteristics of similarity and repeatability without using a mathematical traffic model, a data-driven urban traffic control strategy based on model-free adaptive iterative learning control (MFAILC) scheme is put forward. Firstly, by dynamically linearizing the urban traffic dynamics along the iteration axis, the traffic network system is transformed into a MFAILC data model with the help of repetitive pattern of urban traffic flow. Then, the traffic controller is designed based on the derived MFAILC data model only using the I/O data of the traffic network. Finally, a traffic data compensation method is proposed to deal with data dropout problem. Simulation study verifies the feasibility and effectiveness of the proposed control method.
Supplemental state observer-based sliding mode control for a dynamic system
Chen, Kun-Yung
https://doi.org/10.1049/cth2.12142
A supplemental state observer-based sliding mode control (SSOBSMC) for a dynamic system is proposed in this paper. First, a supplemental state vector is formulated including system output and supplemental output. A supplemental state observer (SSOB) is proposed to estimate the unavailable states. Furthermore, the SSOBSMC consisting of SSOB and sliding mode control (SMC) is proposed to perform state estimation and robust tracking control for the dynamic system with some unavailable states. To demonstrate the application of the proposed methods, a mass-spring-damper (MSD) system is used as an application example to perform numerically. From the simulation results, the SSOB shows a good ability for state estimation, while the SSOBSMC simultaneously demonstrates accuracy in state estimation ability as well as a robust tracking control performance for the non-linear MSD system. The major contributions of this paper are the proposed SSOB that can accurately estimate the unavailable states for the non-linear dynamic system with time-varying disturbances; and the SSOBSMC, which simultaneously displays accuracy in state estimation ability and robust tracking control performance.
Robust static output feedback Nash strategy for uncertain Markov jump linear stochastic systems
Mukaidani, Hiroaki; Xu, Hua; Zhuang, Weihua
https://doi.org/10.1049/cth2.12143
In this article, robust static output feedback (SOF) Nash games for a class of uncertain Markovian jump linear stochastic systems (UMJLSSs) are investigated, in which each player may have access to local/private SOF information. It is proved that the robust SOF Nash strategy set can be obtained by minimizing the upper bounds of the cost functions based on a guaranteed cost control mechanism. By using the Karush?Kuhn?Tucker (KKT) condition, the necessary conditions for the existence of the robust SOF Nash strategy set are established in terms of the solvability conditions of nonlinear simultaneous algebraic equations (NSAEs). A heuristic algorithm is developed to solve the NSAEs. Particularly, it is shown that the robust convergence of the heuristic algorithm is guaranteed by combining the Krasnoselskii?Mann (KM) iterative algorithm with a new convergence condition. Finally, a simple practical example is presented to show the reliability and usefulness of the proposed algorithm.
