In this work, **robust** **trajectory** **tracking** **control** of a **quadrotor** subject to external disturbances is developed **using** angular **acceleration** **feedback**. The hierarchical **control** structure is used as a **control** framework. **Acceleration** based **disturbance** **observer** 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 **acceleration** **control** 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

Show more
127 Read more

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 [1]. To achieve robustness and guarantee the stability of system, **robust** **control** strategies have been applied and investigated by many researchers. In [2] 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 **disturbance** **observer** was presented in [3]; 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 **quadrotor** **helicopter** has also been controlled **using** H ∞ controller. In [4] a mixed **robust** **feedback**

Show more
rescue via **hovering**, **tracking** and coordination [1]–[4]. Re- cently, flapping-wing flying robotics have also attracted much attention by devising **novel** neuro-adaptive methods [5], [6]. 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 [7]–[10]. 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) [11]–[13], dynamic surface **control** (DSC) [14], fuzzy/neural **control** [15]–[23], and non-smooth approaches [24]–[26] 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 [27] backstepping [28], SMC [29], adaptive **control** [30], model predictive **control** (MPC) [31], and **robust** **control** [32] etc., and mode-free approaches includ- ing PID [33]–[35], neural **control** [36] and fuzzy **control** [37],

Show more
15 Read more

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 **disturbance** **observer**. In [16], a **feedback** linearization-based controller with a high order sliding mode **observer** is proposed for **trajectory** **tracking** of a **quadrotor** in the presence of sinusoidal disturbances. In [17], **feedback** linearization with an **observer** is implemented to estimate constant external disturbances. In a more recent work [18], a time-domain **disturbance** **observer** 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 **disturbance** **observer** presented can asymptotically estimate constant disturbances. However, a bounded estimation error is produced by the **observer** for time-

Show more
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

Show more
10 Read more

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 **robust** **control**.

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.

Show more
11 Read more

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 **robust** **control** 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:

Show more
10 Read more

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 **disturbance** **observer** (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**.

Show more
12 Read more

The previous algorithms suggested to solve the **trajectory** **tracking** 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

Show more
18 Read more

Unlike these advance and complicated controllers, a **disturbance** **observer** (DOB) appears to be simpler and easier to use. A DOB does not compensate the system directly [13]. 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 [14] and conventional PD or PID [5,13].

24 Read more

Abstract: This paper present the results of attitude, velocity, heave and yaw controller design for UTM autonomous model scaled **helicopter** **using** 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.

Show more
10 Read more

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** [1]. During the design of a suspension system, a number of conflicting requirements have to be met [2]. 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 [3]. 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 [4]. Thus the passive suspension system, which

Show more
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 **disturbance** **observer** are employed to approximate the un-modeled dynamic and external **disturbance** respectively

Besides that, S.K.Jong et al. [13] 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 [15] 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, **acceleration** **feedback** **control** is proposed by J.D.Han et al. [16]. This controller can eliminate the torque **disturbance**, but the high gain **acceleration** **feedback** **control** 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 [17].

Show more
24 Read more

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.

Show more
In this work, to enhance the degree-of-accuracy from the point view of **control**, we propose a new **disturbance** **observer** 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 **disturbance** **observer** 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

Show more
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 [4]. 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.

Show more
35 Read more

In QFT M contours are important for two reasons: i They are used to define the "high-frequency U-contour" which imposes robust minimum damping bounds to the design in the high-frequency [r]

248 Read more

Wavelet **control** scheme is built and implemented in matlab / simulink software package and it is succeeded to solve the **trajectory** **tracking** problem of mobile robot . A **tracking** **control** 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.

Show more