In this work, robusttrajectorytrackingcontrol of a quadrotor subject to external disturbances is developed using angular accelerationfeedback. The hierarchical control structure is used as a control framework. Acceleration based disturbanceobserver integrated with PID controllers is designed for the positional dynamics of the quadrotor where linear acceleration signals provide better stiffness against the disturbance forces. For attitude control, a nested angular position, velocity and accelerationcontrol structure is employed where PID and PI controllers are used. In order to get reliable angular position, velocity and acceleration signals, an estimation algorithm based on the cascaded structure of extended and classical Kalman filters is utilized. Furthermore, in this work, a nonlinear optimization technique is used to obtain the reference attitude angles form command signals generated from the high-level control of the hierarchical control structure. Unlike analytical method for calculating the reference attitude angles where nonsmooth and large Euler angles might be obtained, the constrained nonlinear optimization technique provides smooth and desired bounded values. Also in the analytical approach, the desired yaw angle (ψ) needs to be fixed to some value (ψ ∗ ), but in case of the proposed method, yaw angle need not be constant. The efficiency of the proposed control method is tested on a high fidelity model of the quadrotor where sensor bias and noise in measurements are also taken into account when 3-D circular helix type trajectory is considered. Results are compared with a
Recently unmanned aerial vehicles (UAVs) have wide area of applications either for military or civil purposes. Control of these systems has become popular due to their usefulness in rescue, surveillance, inspection, mapping, etc. UAV ﬂight control system should make these performance requirements achievable by improving tracking and disturbance rejection capability. So, robustness is one of the critical issues which must be considered in the control system design for such high-performance autonomous UAV. Quadrotor is one of the most preferred types of small unmanned aerial vehicles. It is capable of vertical take-off and landing (VTOL), but it does not require complex mechanical linkages, such as swash plates that commonly appear in typical helicopters . To achieve robustness and guarantee the stability of system, robustcontrol strategies have been applied and investigated by many researchers. In  a feedback linearization-based controller with a high order sliding mode observer running parallel, is applied to a quadrotor unmanned aerial vehicle in presence of parameter uncertainties and external disturbances. A sliding mode disturbanceobserver was presented in ; this controller yields continuous control that is robust to the bounded disturbances and uncertainties. There are some limitations in the range of uncertainty and noise power which can be handles by sliding mode controller; so quadrotorhelicopter has also been controlled using H ∞ controller. In  a mixed robustfeedback
rescue via hovering, tracking and coordination –. Re- cently, flapping-wing flying robotics have also attracted much attention by devising novel neuro-adaptive methods , . Compared with fixed-wing aircrafts, the rotary-wing UAV possesses the significant advantage that it can take-off and land vertically in limited spaces and is easy to hover over the target. Note that the quadrotor UAV (QUAV) is a typical VTOL-UAV with simple mechanical structure and favorable maneuverability. In this context, as a remarkable platform of the UAV, the QUAV has attracted numerous research –. The QUAV is a highly nonlinear system with underactuated constraints and strong couplings between actuator dynamics, and thereby leading to great challenges in controller design and synthesis. With the development of advanced control approaches including sliding mode control (SMC) –, dynamic surface control (DSC) , fuzzy/neural control –, and non-smooth approaches – etc., promis- ing control schemes for the QUAV are pursued ceaselessly. In the literature, control methods of the QUAV can be actually classified into two kinds, i.e., model-based approaches includ- ing feedback linearization  backstepping , SMC , adaptive control , model predictive control (MPC) , and robustcontrol  etc., and mode-free approaches includ- ing PID –, neural control  and fuzzy control ,
In contrast to the adaptive or robust methods, AADC technique reacts directly to the disturbances by feedforward compensation control design using measurements or disturbance estimations via disturbanceobserver. In , a feedback linearization-based controller with a high order sliding mode observer is proposed for trajectorytracking of a quadrotor in the presence of sinusoidal disturbances. In , feedback linearization with an observer is implemented to estimate constant external disturbances. In a more recent work , a time-domain disturbanceobserver based control (DOBC) is implemented to improve the robustness of feedback linearization control with respect to external disturbances which is generated by Dryden wind turbulence model. The time domain disturbanceobserver presented can asymptotically estimate constant disturbances. However, a bounded estimation error is produced by the observer for time-
Electro-hydrostatic actuators offer faster control speeds but suffer from higher static friction levels when com- pared with open hydraulic circuits. Therefore, EHAs require adequate controllers to compensate for the effects of static friction. In this study, FMs and DOBs were inte- grated to suppress the effects of static friction in EHAs. FMs guarantee precise and stable input quantization. As long as the input frequencies are far greater than the natural frequencies of the systems, quantization has lit- tle effect on the output. In this study, steady-state errors caused by linear disturbances were suppressed by the
In the automatic control field, the robustness is the ability of a control system to ensure an utmost constant closed loop characteristic, and more particularly to ensure small variation of the closed loop system stability-degree. Although the controlled plant is perturbed and its model is uncertain . CRONE is a French acronym which means: fractional order robustcontrol.
The second part of the development consists in the construction of a instrumented universal joint that allows the system two degrees of freedom, being coupled to it two encoders in order to measure the angular displacement of roll and pitchmovements. In general, the joint was made of lightweight materials giving a total weight of 733.45 grams, including the weight of the encoders. The last part developed is the basis for the didactic plant, which is used for joining and supporting the other parts of the structure, being composed of carbon steel and stainless steel, weighing approximately 12,935.17 grams. This high-weight material is used in the base to ensure that the quadrotor does not flight when it is in operation and does not present linear displacement in relation to the reference axes. Figure 1show the complete quadrotor plant developed in this project, highlighting each of the developmental parts. The system has a total weight of 14,453.29 grams and its main application is in control of 2-DOF quadrotor attitude, allowing the development of controllers that act on the roll and pitch angles of the aircraft.
lower integrator chain of Fig. 2.4. For the speed control, differentiating (3.6) twice and substituting for di q dt using (3.2) yields the other control variable, u , on the right hand q side and therefore the rank is 2 w.r.t. y . It is 2 3 w.r.t. y due to the kinematic integrator in 1 (3.4) and this would require three integrators in the lower chain of Fig. 2.4. The same controller will be used for y as the number 2 of integrators in the chain exceeds the plant rank w.r.t. this output by 1, which is acceptable. Fig. 3.1 shows a block diagram of the complete observer based robustcontrol system (switch S to y or 2 y ). The 1 subscripts, r and y, refer, respectively to reference inputs and measurements and the transformations are as follows, with intermediate stator-fixed α -β frame:
Abstract An adaptive dynamic surface control (DSC) scheme is proposed for the multi-input and multi-output (MIMO) attitude motion of near-space vehicles (NSVs) in the presence of external dis- turbance, system uncertainty and input saturation. The external disturbance and the system uncer- tainty are efﬁciently tackled using a Nussbaum disturbanceobserver (NDO), and the adaptive controller is constructed by combining the dynamic surface control technique to handle the problem of ‘‘explosion of complexity’’ inherent in the conventional backstepping method. For handling the input saturation, an auxiliary system is designed with the same order as that of the studied MIMO attitude system. Using the error between the saturation input and the desired control input as the input of the designed auxiliary system, a series of signals are generated to compensate for the effect of the saturation in the dynamic surface control design. It is proved that the developed control scheme can guarantee that all signals of the closed-loop control system are semi-globally uniformly bounded. Finally, simulation results illustrate that the proposed control scheme can achieve satis- factory tracking performance under the composite effects of the input saturation and the external disturbance.
The previous algorithms suggested to solve the trajectorytracking problem have shown some drawbacks in practical cases. In linear approaches the final structure for the controller is simple enough for hardware implementation but this simplicity might lead to increased tracking errors. Applying nonlinear approaches can improve the tracking performance but in many cases the closed-loop response is sensitive to the model parameters and also the external disturbances. Utilizing approaches such as MPC or neural networks, conclude a complex framework which might not be appropriate for hardware implementation. The main contribution of this paper is to propose a new robust and nonlinear algorithm which consists of a unified stable control framework which has low computational burden and is simple enough for hardware implementation to solve the position tracking and attitude stabilization problem of a quadcopter. Considering previous studies on various types of algorithms and architectures utilized for this problem, it can be concluded that a cascade structure can be used as an appropriate architecture to regulate the position tracking error and stabilize the attitude dynamics, simultaneously. In this architecture, the outer-loop renders the position tracking problem, which uses the nonlinear H ∞ algorithm to estimate
Unlike these advance and complicated controllers, a disturbanceobserver (DOB) appears to be simpler and easier to use. A DOB does not compensate the system directly . Instead, DOB estimates the disturbances arise from frictions, vibrations and/or parameters variations that occurs in a plant and feeds the error negatively back to perform compensation. Such compensation is usually done with controllers like H-infinity  and conventional PD or PID [5,13].
Abstract: This paper present the results of attitude, velocity, heave and yaw controller design for UTM autonomous model scaled helicopterusing identified model of vehicle dynamic from parameterized state-space model proposed by Mettler (2000) with quasi- steady attitude dynamic approximation (6 DOF model). Multivariable state-space control methodology such as pole placement was used to design the linear state-space feedback for the stabilization of helicopter because of its simple controller architecture. The design specification for controller design was selected according to Military Handling Qualities Specification ADS-33C. Results indicate that acceptable controller can be designed using pole placement method with quasi-steady attitude approximation and it has been shown that the controller design was complianced with design criteria of hover requirement in ADS-33C.
There has been a widespread interest in using advanced control techniques to improve the performance of vehicle suspension system. Performance of the suspension system has been greatly increased due to increasing vehicle capabilities. Several performance characteristics have to be considered in order to achieve a good suspension system. These characteristics deal with regulation of body movement, regulation of suspension movement and force distribution. Ideally the suspension should isolate the body from road disturbances and inertial disturbances associated with cornering and braking or acceleration . During the design of a suspension system, a number of conflicting requirements have to be met . The suspension must be able to minimize the vertical force transmitted to the passengers for passengers comfort. These objectives can be achieved by minimizing the vertical car body acceleration. Also, optimal contact between wheel and road surface is needed in various driving conditions in order to maximize safety . An early design for automobile suspension systems was focused on unconstrained optimizations for passive suspension system which indicate the desirability of low suspension stiffness, reduced unsprung mass, and an optimum damping ratio for the best controllability . Thus the passive suspension system, which
It is well known that imperfect robot model will lead to degradation of tracking performance. So it is necessary to approximate the un-modeled dynamics and external disturbance. Next, the neural network and disturbanceobserver are employed to approximate the un-modeled dynamic and external disturbance respectively
Besides that, S.K.Jong et al.  has proposed a robust digital position control, which is linear quadratic controller with load torque observer. The advantage of this controller is the disturbance can be rejected. However, torque observer contains current due to consider a load torque as the unknown input, it is too much noisy to be used in digital controller or observer [13, 14]. After that, a torque controller  is used to eliminate the torque ripple. The limitation of torque controller is approach quite complex and it just reduces the torque ripple. In addition, accelerationfeedbackcontrol is proposed by J.D.Han et al. . This controller can eliminate the torque disturbance, but the high gain accelerationfeedbackcontrol is needed. Sliding mode controller (SMC) also widely applies in the direct drive system. SMC has less sensitivity to the disturbance force and parameter variations. However, the noise caused by SMC will affect the system performance .
The control input u in the above definitions may be either called static if it depends on the measurements of the signals directly, or dynamic if it depends on the measurements through a set of differential equations. Tracking problems are Generally more difficult to solve than regulation problems. One reason is that, in the tracking problem, the controller has to drive the outputs close to the desired trajectories while maintaining stability of the whole state of the system. On the other hand, regulation problems can be regarded as special cases of tracking problems when the desired trajectory is constant with time.
In this work, to enhance the degree-of-accuracy from the point view of control, we propose a new disturbanceobserver based control scheme to solve the “mismatching” disturbance rejection problem in MAGLEV suspension system mainly for deterministic performance. As for our control design, the model uncertainties caused by parameter perturbation and unmodeled nonlinear dynamics are merged into disturbances. Thus the external disturbances together with the model uncertainties are regarded as a kind of lumped disturbance. A state-space disturbanceobserver is designed to estimate such lumped disturbance. However, the estimate can not be applied directly to compensate the disturbances since here the disturbance acts via different channel to the control input. The mainly contribution of this paper lies in that a disturbance compensation vector is investigated for the
Recent work in the eld of ANC has been focused on designing actuator set-ups that will enable active structural acoustic control (ASAC) of low frequency noise radiated by vibrating structures . The work described by these authors explores the development of thin panels that can be controlled electronically so as to provide surfaces with desired reection coecients. Such panels can be used as either perfect reectors or absorbers. The development of the control system is based on the use of wave separation algorithms that separate incident sound from reected sound. The reected sound is then controlled to desired levels. The incident sound is used as an acoustic reference for feedforward control and has the important property of being isolated from the action of the control system speaker. The suggested control procedure makes use of a half-power FxLMS algorithm and therefore requires installation of microphones in order to be applicable and the use of low pass lters, which adds signicant complexity to the solution of the primary problem.
Wavelet control scheme is built and implemented in matlab / simulink software package and it is succeeded to solve the trajectorytracking problem of mobile robot . A trackingcontrol problem for the speed and azimuth of a mobile robot driven by two independent wheels has been solved by using Mexican hat Wavelet Neural Network controller optimized by using PSO algorithm . The Particle Swarm Optimization method is utilized to tune the parameters and weights of WNN . It gives good results in short time relatively with other optimization methods. The effectiveness of the proposed method was illustrated by performing the simulation for circular, linear and square trajectory. Simulation results show good tracking performance with small Mean square error.