A Model-Free Control Algorithm Based on the Sliding Mode Control Method with Applications to Unmanned Aircraft Systems

Control methods require the use of a system model for the design and tuning of the controllers in meeting and/or exceeding the control system performance objectives. However, system models contain errors and uncertainties that also may be complex to develop and to generalize for a large class of systems such as those for unmanned aircraft systems. In particular, the sliding control method is a superior robust nonlinear control approach due to the direct handling of nonlinearities and uncertainties that can be used in tracking problems for unmanned aircraft system. However, the derivation of the sliding mode control law is tedious since a unique and distinct control law needs to be derived for every individual system and cannot be applied to general systems that may encompass all classifications of unmanned aircraft systems. In this work, a model-free control algorithm based on the sliding mode control method is developed and generalized for all classes of unmanned aircraft systems used in robust tracking control applications. The model-free control algorithm is derived with knowledge of the system’s order, state measurements, and control input gain matrix shape and bounds and is not dependent on a mathematical system model. The derived control law is tested using a high-fidelity simulation of a quadrotor-type unmanned aircraft system and the results are compared to a traditional linear controller for tracking performance and power consumption. Realistic type hardware inputs from joysticks and inertial measurement units were simulated for the analysis. Finally, the model-free control algorithm was implemented on a quadrotor-type unmanned aircraft system testbed used in real flight experimental testing. The experimental tracking performance and power consumption was analyzed and compared to a traditional linear-type controller. Results showed that the model-free approach is superior in tracking performance and power consumption compared to traditional linear-type control strategies

Investigations of Model-Free Sliding Mode Control Algorithms including Application to Autonomous Quadrotor Flight

Sliding mode control is a robust nonlinear control algorithm that has been used to implement tracking controllers for unmanned aircraft systems that are robust to modeling uncertainty and exogenous disturbances, thereby providing excellent performance for autonomous operation. A significant advance in the application of sliding mode control for unmanned aircraft systems would be adaptation of a model-free sliding mode control algorithm, since the most complex and time-consuming aspect of implementation of sliding mode control is the derivation of the control law with incorporation of the system model, a process required to be performed for each individual application of sliding mode control. The performance of four different model-free sliding mode control algorithms was compared in simulation using a variety of aerial system models and real-world disturbances (e.g. the effects of discretization and state estimation). The two best performing algorithms were shown to exhibit very similar behavior. These two algorithms were implemented on a quadrotor (both in simulation and using real-world hardware) and the performance was compared to a traditional PID-based controller using the same state estimation algorithm and control setup. Simulation results show the model-free sliding mode control algorithms exhibit similar performance to PID controllers without the tedious tuning process. Comparison between the two model-free sliding mode control algorithms showed very similar performance as measured by the quadratic means of tracking errors. Flight testing showed that while a model-free sliding mode control algorithm is capable of controlling realworld hardware, further characterization and significant improvements are required before it is a viable alternative to conventional control algorithms. Large tracking errors were observed for both the model-free sliding mode control and PID based flight controllers and the performance was characterized as unacceptable for most applications. The poor performance of both controllers suggests tracking errors could be attributed to errors in state estimation, which effectively introduce unknown dynamics into the feedback loop. Further testing with improved state estimation would allow for more conclusions to be drawn about the performance characteristics of the model-free sliding mode control algorithms

Model-Free Control of an Unmanned Aircraft Quadcopter Type System

A model-free control algorithm based on the sliding mode control method for unmanned aircraft systems is proposed. The mathematical model of the dynamic system is not required to derive the sliding mode control law for this proposed method. The knowledge of the system’s order, state measurements and control input gain matrix shape and bounds are assumed to derive the control law to track the required trajectories. Lyapunov’s Stability criteria is used to ensure closed-loop asymptotic stability and the error estimate between previous control inputs is used to stabilize the system. A smoothing boundary layer is introduced into the system to eliminate the high frequency chattering of the control input and the higher order states. The [B] matrix used in the model-free algorithm based on the sliding mode control is derived for a quadcopter system. A simulation of a quadcopter is built in Simulink and the model-free control algorithm based on sliding mode control is implemented and a PID control law is used to compare the performance of the model-free control algorithm based off of the RMS (Root-Mean-Square) of the difference between the actual state and the desired state as well as average power usage. The model-free algorithm outperformed the PID controller in all simulations with the quadcopter’s original parameters, double the mass, double the moments of inertia, and double both the mass and the moments of inertia while keep both controllers exactly the same for each simulation

Genetic programming for the automatic design of controllers for a surface ship

In this paper, the implementation of genetic programming (GP) to design a contoller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the command forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships

A robust control design approach for altitude control and trajectory tracking of a quadrotor

Introduction. Unmanned aerial vehicles as quadcopters, twin rotors, fixed-wing crafts, and helicopters are being used in many applications these days. Control approaches applied on the quadrotor after decoupling the model or separate altitude control and trajectory tracking have been reported in the literature. A robust linear H∞ controller has been designed for both altitude control and circular trajectory tracking at the desired altitude. Problem. The ability of the quadrotor system to hover at a certain height and track any desired trajectory makes their use in many industrial applications in both military and civil applications. Once a controller has been designed, it may not be able to maintain the desired performance in practical scenarios, i.e. in presence of wind gusts. Originality. This work presents the control strategy to ensure both altitude control and trajectory tracking using a single controller. Purpose. However, there is a need for a single controller that ensures both altitude control and trajectory tracking. Novelty. This paper presents a robust H∞ control for altitude control and trajectory tracking for a six degree of freedom of unmanned aerial vehicles quadrotor. Methodology. Multi input multi output robust H∞ controller has been proposed for the quadrotor for altitude control and tracking the desired reference. For the controller validation, a simulation environment is developed in which a 3D trajectory is tracked by the proposed control methodology. Results. Simulation results depict that the controller is efficient enough to achieve the desired objective at minimal control efforts. Practical value. To verify that the proposed approach is able to ensure stability, altitude control, and trajectory tracking under practical situations, the performance of the proposed control is tested in presence of wind gusts. The ability of the controller to cater to the disturbances within fractions of seconds and maintaining both transient and steady-state performance proves the effectiveness of the controller.Вступ. Безпілотні літальні апарати, такі як квадрокоптери, двороторні апарати, апарати з нерухомими крилами та гелікоптери сьогодні використовуються у багатьох сферах застосування. У літературі повідомляється про підходи до керування, застосовані на квадрокоптері після від’єднання моделі або окремого контролю висоти та відстеження траєкторії. Надійний лінійний регулятор H∞ був розроблений як для контролю висоти, так і для відстеження кругової траєкторії на потрібній висоті. Проблема. Здатність квадрокоптерної системи зависати на певній висоті та відстежувати будь-яку бажану траєкторію робить їх застосування можливим у багатьох сферах як у військових, так і в цивільних цілях. Розроблений контролер може не підтримувати бажані характеристики у реальних умовах, тобто за наявності поривів вітру. Оригінальність. У цій роботі представлена стратегія керування, яка забезпечує як контроль висоти, так і відстеження траєкторії за допомогою одного контролера. Мета. Однак існує потреба в єдиному контролері, який забезпечує як контроль висоти, так і відстеження траєкторії. Новизна. У цій статті представлено надійний регулятор H∞ для контролю висоти та відстеження траєкторії для шести ступенів свободи безпілотних літальних апаратів. Методологія. Для квадрокоптера запропоновано багатовхідний багатовихідний надійний контролер H∞ для контролю висоти та відстеження бажаного курсу. Для перевірки контролера розробляється середовище моделювання, в якому тривимірна траєкторія відстежується за запропонованою методологією керування. Результати. Результати моделювання показують, що контролер є досить ефективним для досягнення бажаної мети при мінімальних зусиллях контролю. Практична цінність. Щоб переконатися, що запропонований підхід здатний забезпечити стабільність, контроль висоти та відстеження траєкторії в реальних ситуаціях, параметри запропонованого контролю перевіряються за наявності поривів вітру. Здатність контролера усувати порушення протягом кількох секунд і підтримувати як перехідні, так і стабільні показники доводить ефективність контролера

Design of a Robust Controller Using Sliding Mode for Two Rotor Aero-Dynamic System: Design of a Robust Controller Using Sliding Mode for Two Rotor Aero-Dynamic System

This paper deals with two rotor aero-dynamic system (TRAS) which is a multi-input multi-output highly coupled nonlinear system, for creating a mathematical model based following the Lagrange’s Equations, and creating controllers for Sliding Mode Control and Linear Quadratic Regulator. The Sliding Manifold is designed by employing the reduced order representation. Linear Quadratic Regulator has been created by linearizing the nonlinear system acquired by creating the state space representation following the mathematical model. The signal tracking conditions of PID, SMC, and LQR have been discussed.  Although the proposed control methodology has perfect actuation time, the tracking efficiency was not satisfactory. Therefore, a rework on the parametrization and introduction of filters, i.e. types of Kalman Filters have been proposed as a conclusion

A Model-Free Control System Based on the Sliding Mode Control with Automatic Tuning Using as On-Line Parameter Estimation Approach

The sliding mode control algorithm and Lyapunov-based methods, have received much attention recently due to their ability to directly handle nonlinear systems while guaranteeing closed-loop tracking stability. In this work, a unique model-free sliding mode control technique has developed solely based on previous control inputs. The new method requires only knowledge of the system order and state measurements and does not require a theoretical model of the dynamic system. Lyapunov’s stability theorem is used in the controller formulation process to ensure closed-loop asymptotic stability. High frequency chattering of the control effort is reduced by using a smoothing boundary layer into the control law. Parameters variation during control operating and noise effect cannot be handled by the model-free controller if the controller tuning parameters are chosen arbitrarily since tracking performance becomes unacceptable. In addition, in previous work, the bounds of the input influence gain parameters were assumed to be known to derive the model-free controller. Therefore, in this work, a new approach is proposed for estimating the increment to the switching gain in real-time to ensure the sliding condition (which guarantees closed-loop tracking stability) is satisfied using a control law form that assumes a strictly unitary input influence gain. In formulation of estimation law, an exponential forgetting factor is combined with the least-squares estimator to ensure the updated data are used and past data are excluded. An automatic bounded forgetting tuning technique is developed to maintain the benefits of data forgetting while avoiding the possibility of gain unboundedness in absence of persistent excitation. The tuning estimator is assured that the resulting gain matrix is upper bounded regardless of the persistent excitation by suspending the data forgetting if the gain matrix reaches the specified upper bound. Simulations are performed on a series of linear and nonlinear SISO and MIMO systems with and without including actuator time-delay effects. Finally, a model is developed to simulate a quadcopter as a real-world application case. In all cases, the controller achieved perfect or near-perfect tracking performance using updated controller and on-line estimator tuning process