基于反演积分技术的无人驾驶水面飞行器的自动驾驶仪设计及其实验结果

Controller tuning is the correct setting of controller parameters to control complex dynamic systems appropriately and with high accuracy.Therefore,this study addressed the development of a method for tuning the heading controller of an unmanned surface vehicle(USV)based on the backstepping integral technique to enhance the vehicle behavior while tracking a desired position for water monitoring missions.The vehicle self-steering system(autopilot system)is designed theoretically and tested via a simulation.Based on the Lyapunov theory,the stability in the closed-loop system is guaranteed,and the convergence of the heading tracking errors is obtained.In addition,the designed control law is implemented via a microcontroller and tested experimentally in real time.Conclusion,experimental results were carried out to verify the robustness of the designed controller when disturbances and uncertainties are introduced into the system.

Controller Design of High Order Nonholonomic System with Nonlinear Drifts

A controller design is proposed for a class of high order nonholonomic systems with nonlinear drifts. The purpose is to ensure a solution for the closed-loop system regulated to zero. Adding a power integrator backstepping technique and the switching control strategy are employed to design the controller. The state scaling is applied to the recursive manipulation. The simulation example demonstrates the effectiveness and robust features of the proposed method.

A new nonlinear output tracking controller via output-feedback

In this paper, the output tracking control is investigated for a class of nonlinear systems when only output is available for feedback. Based on the multivariable analog of circle criterion, an observer is first introduced. Then, the observer-based output tracking controller is constructively designed by using the integral backstepping approach together with completing square. It is shown that, under relatively mild conditions, all the closed-loop signals are uniformly bounded. Meanwhile the system output asymptotically tracks the desired output. A simulation example is given to illustrate the effectiveness of the theoretical results.

Group Coevolution and Immigration Pigeon-Inspired Optimized Dual-layer Controller for Aerial Manipulator Trajectory Tracking

The aerial manipulator expands the scope of unmanned aerial vehicle(UAV)'s application as well as increases the di±culties in the design of the controller.To better control the aerial manipulator for di®erent trajectories tracking under di®erent conditions,a new dual-layer controller is designed in this paper.The integral backstepping sliding mode controller(IBSMC)is applied to the outer-loop controller and backstepping controller(BC)is applied to the innerloop controller.To improve the performance of the system,an improved pigeon-inspired optimization(PIO)algorithm called group coevolution and immigration pigeon-inspired optimization(GCIPIO)algorithm is proposed to optimize the controller parameters of IBSMC.GCIPIO algorithm utilizes the group coevolution and immigration mechanisms.A series of simulations are conducted to show the advantage of the proposed method.The results illustrate that the proposed method ensures the closed-loop system has less end-e®ector tracking error.

Output feedback stabilization for stochastic nonlinear systems in observer canonical form with stable zero-dynamics

In this paper, we study the problem of output feedback stabilization for stochastic nonlin-ear systems. We consider a class of stochastic nonlinear systems in observer canonical form with sta-ble zero-dynamics. We introduce a sequence of state transformations that transform the system into a lower triangular structure that is amenable for integrator backstepping design. Then we design the out-put-feedback controller and prove that the closed-loop system is bounded in probability. Furthermore, when the disturbance vector field vanishes at the origin, the closed-loop system is asymptotically stable in the large. With special care, the controller preserves the equilibrium of the nonlinear system. An ex-ample is included to illustrate the theoretical findings.

Design of satisfaction output feedback controls for stochastic nonlinear systems under quadratic tracking risk-sensitive index

In this paper, the design problem of satisfaction output feedback controls for stochastic nonlinear systems in strict feedback form under long-term tracking risk-sensitive index is investigated. The index function adopted here is of quadratic form usually encountered in practice, rather than of quartic one used to beg the essential difficulty on controller design and performance analysis of the closed-loop systems. For any given risk-sensitive parameter and desired index value, by using the integrator backstepping method, an output feedback control is constructively designed so that the closed-loop system is bounded in probability and the risk-sensitive index is upper bounded by the desired value.

Minimal-order observer and output-feedback stabilization control design of stochastic nonlinear systems

A minimal-order observer and output-feedback stabilization control are given for single-input multi-output stochastic nonlinear systems with unobservable states, un- modelled dynamics and stochastic disturbances. Based on the observer designed, the estimates of all observable states of the system are given, and the convergence of the es- timation errors are analyzed. In addition, by using the integrator backstepping approach, an output-feedback stabilization control is constructively designed, and sufficient condi- tions are obtained under which the closed-loop system is asymptotically stable in the large or bounded in probability, respectively.