Control Based on Linear Algebra for Trajectory Tracking and Positioning of Second-Order Chained Form System

)e development of controllers for underactuated systems with nonholonomic constraints has been a topic of significant interest for many researchers in recent years. )ese systems are hard to control because their linearization transform them into uncontrollable systems. )e proposed approaches involve the use of a permanent excitation in the reference trajectory; coordinate transformation; discontinuities; or complex calculations. )is paper proposes the design of the controller of the second-order chained form system for trajectory tracking by using a simpler approach based on linear algebra. Up to the present time, no controllers based on this approach have been designed for that system. )e control problem is solved by setting two of the three systems variables as a reference, while the remaining variable is calculated imposing the condition that the equations system has an exact solution to ensure that tracking errors go to zero. )e stability of the proposed controller is theoretically demonstrated, and simulations results show a suitable control system performance. Also, no coordinate transformation is necessary.


Introduction
In recent years, the interest in the control of underactuated systems with nonholonomic constraints has increased [1]. Underactuated systems are mechanical systems with fewer control inputs than degrees of freedom and nonintegrable acceleration constraints [2]. is paper considers the control for trajectory tracking and positioning of second-order chained form systems. ese are hard to control because their linearization transform them into uncontrollable systems. e well-known paper of Brockett highlights the difficulty of solving these problems [3].
Several articles addressed the control of underactuated systems with nonholonomic constraints. Aneke et al. [4,5] resolved the problem of trajectory tracking by using a threestage method. In the first step, they transformed the original system into an extended chained form system with a cascade arrangement. ey applied a linear feedback controller to the first subsystem. After that, the second subsystem is exponentially stabilized by employing a backstepping procedure. In the third step, they showed the closed-loop tracking dynamics stability of the system. More recently, other authors used the backstepping procedure to develop control methodologies for trajectory tracking [6,7]. A permanent excitation in the reference trajectory is also necessary for system stability.
is implies that the signals must not converge to zero, limiting their applications.
Also, in [8], smooth time-varying controllers are proposed to address the exponential tracking of second-order nonholonomic systems. ese techniques use coordinate transformation based on time-varying dilation with a cascade-design strategy. In contrast to the previous approach, it does not require the excitation condition in the reference trajectory.
is kind of control laws frequently involves complex calculations; their design is not intuitive and only applies for special nonholonomic systems. Another method used a discontinuous coordinate transformation to map the initial system into the space of discontinuous nonholonomic systems. In this new space, the control problem can be solved [9,10]. An adaptive dynamic sliding mode controller with integrator was also found in the literature to control nonholonomic systems [11].
is scheme uses a modified backstepping kinematic controller for generating the kinematic trajectories and the velocity errors to drive the sliding surface.
e normalized least-square mean was used to control the switching of a sliding mode controller in the presence of uncertainties and parameter variations. Also, other authors developed sliding mode control methodologies for trajectory tracking and positioning of nonholonomic second-order chained form systems [12][13][14]. Sarfraz and ur Rehman [15] addressed the positioning problem of a particular nonholonomic planar underactuated mechanical system using adaptive sliding mode control. e control law assures the derivative of a suitable Lyapunov function becomes strictly negative. e aforementioned controllers use a permanent excitation in the reference trajectory [4,5]; coordinate transformation [8]; discontinuities [9,10]; and high computational load calculations [11][12][13][14][15] to solve the trajectory tracking problem. To overcome these drawbacks, this paper aims to solve the problem of trajectory tracking of a second-order chained form system with nonholonomic constraints by using a novel control law inspired by the design method Linear Algebra-Based Controller (LABC) [16]. is technique computes the control actions by solving a system of linear equations and has been applied to different nonlinear systems [17][18][19][20][21][22][23].
Until now, LABC has not been applied to second-order chained form systems with nonholonomic constraints in the space of the original variables. For this reason, the major contribution of this work is to extend the LABC technique to solve the tracking and positioning problem for these systems. e system should follow the reference coordinates of two of three variables while the other one is unknown. e key point of this strategy is to find the conditions for which the system of linear equations has an exact solution, ensuring the calculus of the remaining variable, named sacrificed variable. In this way, the reference trajectories of the selected variables and the sacrificed one form an admissible trajectory of the system and the tracking error goes to zero [16].
is paper is organized as follows. e Materials and Methods section describes the second-order chained form system with nonholonomic constraints and solves the problem of trajectory tracking and positioning using a controller based on linear algebra. e stability of the closedloop system is demonstrated by applying the Khalil lemma. In the Results and Discussion section, simulation results show the effectiveness of the proposed controllers. Conclusions are given at the end of this manuscript.

Problem Formulation.
is section presents the special canonical form of an underactuated system with nonholonomic constraints. e control of this system remains a problem under study [1]. One of the most important issues is the transformation to a chained form.
Consider the second-order chained form system, S ξ , given by following set of equations: where ξ � [ξ 1 ; ξ 2 ; ξ 3 ] T ∈ R 3 are the generalized coordinates of the second-order chained form system and u � [u 1 u 2 ] T represents the inputs such that u 1 ∈ R and u 2 ∈ R. Also, the reference trajectory is e tracking errors e � [e 1 ; e 2 ; e 3 ] T ∈ R 3 are the differences between the reference paths and the variables: is work proposes the design of a controller for trajectory tracking and positioning of a second-order nonholonomic system represented by (1)-(3).

Problem 1: Trajectory
Tracking. Given the system S ξ , the trajectory tracking control problem is solvable if it is possible to design an appropriate controller of the form such that the closed-loop system constituted by (1)-(3) and the control actions (5) and (6) is globally uniformly asymptotically stable.

Problem 2:
Positioning. Given the system S ξ , the positioning control problem is solvable if it is possible to design an appropriate controller of the form such that the closed-loop system constituted by (1)-(3) and the control actions (7) and (8) is globally uniformly and asymptotically stable. Here, the reference trajectory Φ ξ is zero.
To the best of our knowledge, LABC technique has not been applied directly to systems of second-order equations without considering a model in state variables; therefore, we extend its use to these systems. e control method is based on determining the conditions for which the system has an exact solution. Knowing the system model, it is only necessary to fix the desired trajectory of ξ 1 (ξ 1,ref ) and ξ 3 (ξ 3,ref ) to find the solution [16].

Controller Design for Trajectory Tracking.
Given an initial state ξ(0), the system represented by (1)-(3), S ξ , should follow the desired trajectory Φ ξ with a low tracking error. erefore, it is necessary to find a control law capable of generating a signal u � [u 1 u 2 ] T such that it satisfies this objective.
e system S ξ is expressed in matrix form as follows: To calculate the control actions u 1 and u 2 , (9) should have an exact solution, that is, If a proportional control approach is assumed, the tracking errors are the differences between the reference and real trajectories. us, the second-order derivatives of the variables ξ 1 and ξ 3 , i.e., € ξ 1 [16].
If the internal variable ξ 2,ez is set to the value of ξ 2 for which the above system has an exact solution, then (11) is rewritten as and the tracking errors in variables 1 and 3 tend to zero. Variable ξ 2,ez is computed according to Remark 1. Variable ξ 2 follows ξ 2,ez and this one tracks ξ 2,ref .
e first-order derivatives of the tracking errors are _ , and the control action u 1 is obtained using the linear least-squares approximation method to (12) is We can write the second-order derivative of the variable ξ 2 ( € ξ 2 ) as a function of the sacrificed variable ξ 2,ez : Furthermore, the first-order derivative of the tracking error of variable 2 is _ e 2 � _ ξ 2,ez − _ ξ 2 , and the control action u 2 is Remark 2. If the numerator and denominator of (13) tend to zero simultaneously, the division is undetermined and ξ 2,ez cannot be calculated. To avoid this problem, it is necessary to choose adequately the coefficients k 11 , k 10 , k 31 , and k 30 forcing the errors e 3 and _ e 3 to go to zero more quickly than e 1 and _ e 1 . is avoids that ξ 2,ez tends to infinity following trajectories whose second derivatives are zero (linear and constant reference trajectories).  (14)- (16),

Stability of the Tracking Error
Proof. e following steps are proposed to prove eorem 1.

Controller Design for Positioning.
e positioning problem for the system, S ξ , consists in computing the control inputs, u 1 � u 1 (t, ξ, Φ ξ ) and u 2 � u 2 (t, ξ, Φ ξ ), such that the origin of the system is stable for any initial state ξ(0 e system S ξ is expressed in matrix form as follows: To calculate the control actions u 1 and u 2 , (26) should have an exact solution; that is, If a proportional control approach is assumed, the tracking errors are the differences between the reference (zero) and real trajectories. us, the variables € ξ 1 and € ξ 3 are € ξ 1 � −k 11 _ ξ 1 + k 10 e 1 and € ξ 3 � −k 31 _ ξ 3 + k 30 e 3 . If ξ 2,ez is the value of ξ 2 for which the above system has an exact solution, then and the tracking errors in variables 1 and 3 tend to zero. Variable ξ 2,ez is computed according to Remark 4. Variable ξ 2 follows ξ 2,ez and this one tracks ξ 2,ref . e control action u 1 obtained using linear least-squares approximation method to (28) is Furthermore, the control action u 2 is a function of variables € ξ 2,ez , _ e 2 , and e 2 : Remark 5. Equations (30) and (31) for positioning are a particular case of (13) and (14) for trajectory tracking of the system, S ξ .

Stability of the Tracking Error Dynamics: Positioning Case.
In this section, the stability of the closed-loop system [(1)- (3) and (29) Proof.

Results and Discussion
e closed-loop system (1)- (3) and (13), (14), (16) for trajectory tracking is simulated and analyzed in the first test. In the same way, the closed-loop system (1)-(3) and (29)-(31) for positioning is simulated, and the results are discussed in the second test.

Trajectory Tracking Test.
e aim of this section is to show that given a reference trajectory, the proposed controller can calculate a control law that allows following effectively. e reference trajectories of ξ 1 ; ξ 2 ; and ξ 3 are simulated considering ξ 1 (0) � 40 and ξ 2 (0) � ξ 3 (0) � 0 as the initial state of the system, and ξ 1,ref   respectively. e first one, u 1 , evolves quickly from 0 to 10 −4 remaining constant. e second one, u 2 , follows a sine wave path with mean 0, amplitude 0.8, and frequency 1/8π.

Positioning Test.
e closed-loop system (1)    and k 31 � 0.95. Figures 6 and 7 show the trajectories of system variables ξ 1 and ξ 3 (blue solid lines). e red and magenta dashed lines indicate the zero reference. Figure 8 presents the control action u 1 , calculated by (30). In Figure 9, variables ξ 2 and ξ 2,ez are represented by a blue and orange solid lines, respectively. Finally, Figure 10 displays the trajectory of the control action u 2 calculated by (31).

Conclusion
e major contribution of this paper is to extend the LABC technique for trajectory tracking and positioning of a second-order nonholonomic system. is controller is based on determining the conditions for which the system model has an exact solution. Knowing the model equations, it is necessary only to fix the desired trajectory to find the control action. Variables 1 and 3 were set as references, while variable 2 is the sacrificed one to ensure that the tracking errors go to zero. An important advantage of the proposed controller is the low computational load of the required mathematical operations. e stability of the system is demonstrated by applying the Khalil lemma [24].
Simulation results show the performance of the proposed control algorithm. e controller parameters were empirically tuned. For trajectory tracking, these parameters ensure that the system variables quickly reach the reference and follow it without undesirable oscillations. In the case of the positioning problem, these parameters were tuned in such a way variable ξ 3 goes to zero more quickly than ξ 1 .

Data Availability
e data used to support the finding of this study are included within the article.

Conflicts of Interest
e authors declare that there are no conflicts of interest regarding the publication of this paper. Council for Scientific Research), Argentina. is work was partially funded by Consejo Nacional de Investigaciones    Mathematical Problems in Engineering 7