Q: Applications of stepper motors: In which types of equipment are stepper motors commonly used due to their ability to provide precise angular movements in response to digital pulses?

Introduction / Context: Stepper motors are electromechanical devices that move in discrete steps, making them highly useful in systems requiring position control without feedback. Their digital nature matches well with microprocessor and computer control. Given Data / Assumptions: Stepper motor rotates by a fixed step angle for each input pulse. Suitable for low-to-medium power control applications. Concept / Approach: Since each input pulse produces a predictable angular displacement, devices that require controlled positioning and incremental motion rely on stepper motors. Step-by-Step Solution: Consider X–Y plotters: stepper motors move pens with precision.Consider numerically controlled machining: CNC tools require precise incremental motion.Consider printers: early dot-matrix and modern 3D printers use steppers to move heads or platforms.Therefore, the correct choice is all of the above. Verification / Alternative check: Industrial documentation of CNC machines and printers lists stepper motors in their drive systems, verifying the applications. Why Other Options Are Wrong: Each individual option is correct but incomplete. Only “all of the above” captures the complete scope. Common Pitfalls: Confusing steppers with servo motors; servos use feedback, while steppers are open-loop. Final Answer: All of the above.

Q: Logarithmic magnitude plot of a constant-gain system: In Bode plot analysis, what is the log magnitude curve corresponding to a constant gain K?

Introduction / Context: Bode plots represent frequency response in logarithmic scale. The magnitude plot uses decibels to make multiplicative relationships additive, simplifying system analysis. Given Data / Assumptions: System transfer function has only a constant gain K, with no frequency-dependent terms. Magnitude response is frequency-independent. Concept / Approach: Magnitude in decibels is given by 20 log(K). For any frequency, the magnitude remains constant, so the graph is a flat line parallel to the frequency axis. Step-by-Step Solution: Write gain in decibels: 20 log K.Plot magnitude vs. log frequency: horizontal line at that level.No slope is present because there is no dependence on frequency. Verification / Alternative check: Compare with Bode plots of poles/zeros: poles give –20 dB/decade slopes, zeros give +20 dB/decade slopes. A constant gain has none, so slope = 0. Why Other Options Are Wrong: Horizontal line without specifying decibel magnitude is incomplete. Inclined lines occur only with frequency-dependent poles or zeros. Common Pitfalls: Mixing up magnitude scale (linear vs. decibels). Final Answer: A horizontal straight line with magnitude 20 log K decibels.

Q: Integral controller behavior: In process control, what is the correct relationship between the input signal and the output of an ideal integral controller?

Introduction / Context: Integral controllers are a key component in PID control systems. Their main role is to eliminate steady-state error by integrating the error signal over time. Given Data / Assumptions: Ideal continuous-time integral controller. Transfer function is K_i / s. Concept / Approach: Mathematically: if e(t) is the input error, the controller output u(t) = K_i ∫ e(t) dt. Differentiating both sides shows du/dt = K_i * e(t), meaning the rate of change of output is proportional to the input error. Step-by-Step Solution: Start with transfer function: U(s)/E(s) = K_i / s.In time domain: u(t) = K_i ∫ e(t) dt.Differentiate: du/dt = K_i * e(t).Therefore, the rate of change of output is proportional to input. Verification / Alternative check: Block-diagram modeling of PID confirms the integral action has infinite DC gain, accumulating input over time. Why Other Options Are Wrong: (a) Proportional controller, not integral. (c) Describes a derivative controller. (d) Incorrect since the integral has a defined relationship. Common Pitfalls: Confusing integral with proportional action. Ignoring the fact that the integral term builds gradually over time. Final Answer: The rate of change of output is proportional to the input.

Question 1

Definition of a stepper motor: Which statement best describes a stepper motor's fundamental operation?

Accepted Answer

Introduction / Context: Stepper motors are ubiquitous in motion control for printers, CNC stages, and robotics. Unlike induction or synchronous motors designed for continuous rotation, a stepper moves in discrete angular increments that are commanded digitally. Given Data / Assumptions: Open-loop pulse driving without feedback (typical of basic stepper systems). One electrical input pulse corresponds to one mechanical step of fixed angle (e.g., 1.8°). Concept / Approach: A stepper motor contains multiple phase windings and a toothed rotor or permanent magnet. Sequencing the phase excitations creates a rotating magnetic field. The rotor aligns successively with each field orientation, producing a train of equal angular steps proportional to the input pulse count. Step-by-Step Solution: Apply a pulse to phase A → rotor aligns to position 1.Advance the excitation to phase B → rotor moves one step to position 2.Repeat the sequence to generate a series of precise increments; microstepping subdivides these steps using controlled current waveforms. Verification / Alternative check: Observe that commanded step count maps directly to shaft position (open-loop), confirming the definition: one pulse produces one step. Why Other Options Are Wrong: Two-phase induction motor is a different machine type relying on slip. Rotating amplifier is not a motor. An angle transducer that outputs an electrical signal (resolver/encoder) is a sensor, not an actuator. A servo that synchronizes to mains frequency describes synchronous motors, not steppers. Common Pitfalls: Confusing stepper motors with servomotors or induction motors. Assuming steppers inherently provide feedback; basic systems do not. Final Answer: An electromechanical device that executes discrete step angular movements in response to a train of input pulses (one pulse → one step).

Question 2

Evaluate the statement: 'The phase margin of a control system and the damping ratio of its transient response have no relationship.' Indicate whether this statement is true or false.

Accepted Answer

Introduction / Context: Phase margin and damping ratio are fundamental stability measures in control systems. Phase margin is a frequency-domain specification obtained from Bode or Nyquist plots, while damping ratio is a time-domain parameter that affects overshoot and settling time. There exists a practical relationship between the two, particularly for second-order dominant systems, where phase margin can be related to damping ratio using approximate formulas. Given Data / Assumptions: We are analyzing a unity feedback system with dominant complex-conjugate poles. Phase margin (PM) is defined as 180° + phase(G(jω_gc)) at the gain crossover frequency. Damping ratio (ζ) is defined from the standard second-order system transfer function response. Concept / Approach: Approximate correlation exists: PM ≈ tan⁻¹(2ζ / √(√(1+4ζ⁴) − 2ζ²)). This relation shows that higher damping ratios (ζ ~ 0.7) correspond to larger phase margins (~60°), yielding well-damped, low-overshoot responses. Conversely, very low damping ratios produce small phase margins and oscillatory responses. Step-by-Step Solution: Phase margin is measured at ω_gc where |G(jω_gc)| = 1.Damping ratio relates to pole locations: s = −ζω_n ± jω_n√(1 − ζ²).By comparing equivalent frequency-domain and time-domain behaviors, formulas linking PM and ζ are derived.Example: ζ = 0.7 ⇒ PM ≈ 65°; ζ = 0.5 ⇒ PM ≈ 55°. Verification / Alternative check: Textbook plots of phase margin vs damping ratio confirm this correlation empirically. Why Other Options Are Wrong: 'True': incorrect because a definite relationship exists.Other conditional options misstate the fundamental cross-domain connection. Common Pitfalls: Believing PM and ζ are independent; in reality, they both measure relative stability but in different domains. Final Answer: False

Question 3

In a linear time-invariant (LTI) system, if the input is x(t) = A sin(ωt), what is the general expression for the steady-state output y(t) in terms of the frequency response G(jω)?

Accepted Answer

Introduction / Context: Frequency response analysis in control and signal processing allows prediction of the output of an LTI system given a sinusoidal input. The output retains the same frequency as the input, but its amplitude and phase are modified according to the system's transfer function evaluated at that frequency. Given Data / Assumptions: Input x(t) = A sin(ωt). System transfer function frequency response: G(jω). Assume linear, time-invariant, stable system with well-defined steady state. Concept / Approach: The output steady-state sinusoid is scaled by the magnitude of G(jω) and phase-shifted by its angle. Therefore, y(t) = |G(jω)| A sin(ωt + ∠G(jω)). Frequency does not change, only amplitude and phase. Step-by-Step Solution: Represent input as phasor: X(jω) = A ∠0°.Output phasor: Y(jω) = G(jω) × X(jω).Magnitude: |Y| = |G(jω)| A; Phase: ∠Y = ∠G(jω).Convert back to time domain: y(t) = |G(jω)| A sin(ωt + ∠G(jω)). Verification / Alternative check: Simulation of sinusoidal response in MATLAB/Scilab yields amplitude gain |G(jω)| and phase shift ∠G(jω), matching the formula. Why Other Options Are Wrong: Option (a): φ = tan⁻¹|G(jω)| is meaningless; phase is not tan⁻¹ of magnitude.Option (c): Doubles frequency (2ω), which does not occur in LTI systems.Option (d): A G(jω) sin[…] incorrectly multiplies sinusoid by a complex number directly.Option (e): Cosine form is valid but requires phase redefinition; the standard representation is sine with phase shift. Common Pitfalls: Forgetting that LTI systems preserve frequency; only amplitude and phase change. Final Answer: |G(jω)| A sin[ωt + ∠G(jω)]

Question 4

From a noise performance perspective in communication and control systems, what should be the general guideline regarding the bandwidth of a system?

Accepted Answer

Introduction / Context: Noise in electronic systems is distributed over frequency. Thermal noise, for instance, is white across a broad spectrum, meaning total noise power is directly proportional to bandwidth. Therefore, system bandwidth must be carefully chosen to balance fidelity and noise performance. Given Data / Assumptions: Noise power spectral density ≈ constant across wideband (white noise assumption). Total integrated noise power = N0 × bandwidth. Signal occupies a certain frequency range. Concept / Approach: To minimize noise, bandwidth should not greatly exceed the minimum required to pass the signal. Too large a bandwidth admits unnecessary noise power, degrading signal-to-noise ratio (SNR). Conversely, too narrow a bandwidth distorts or attenuates the signal. Optimal design uses bandwidth just sufficient to accommodate the signal spectrum with margin. Step-by-Step Solution: Signal requires bandwidth B_sig.Noise power = N0 × B_total.If B_total ≫ B_sig, then excess noise enters without improving fidelity.Best choice: B_total slightly larger than B_sig to ensure fidelity but limit noise. Verification / Alternative check: Shannon's capacity theorem C = B log2(1 + S/N) also implies that while capacity increases with B, the S/N decreases as noise power increases linearly with B. Why Other Options Are Wrong: 'Very large', 'as large as possible', or 'infinite' bandwidth increases noise and is undesirable.'Always very small' sacrifices signal fidelity and data rate. Common Pitfalls: Thinking maximum bandwidth is always best; overlooking the tradeoff between SNR and fidelity. Final Answer: It should not be too large

Question 5

Assertion–Reason (Control Systems): Assertion (A): Potentiometers cannot be used as error detectors in position control systems. Reason (R): The resolution of a potentiometer places an upper limit on its accuracy.

Accepted Answer

Introduction / Context: Error detectors are essential in closed-loop position control systems, comparing the actual and desired values. Potentiometers are commonly used as position transducers due to their simplicity and linearity. This question tests knowledge of potentiometer applicability and limitations. Given Data / Assumptions: Potentiometer converts angular displacement into proportional voltage. Finite resolution and wear affect accuracy but do not preclude usage. Position control requires continuous error detection capability. Concept / Approach: Assertion (A) claims potentiometers cannot be used — this is incorrect, as they are widely used. Reason (R) states resolution limits accuracy — this is true. However, the reason does not support the false assertion, so the correct choice is that R is correct while A is wrong. Step-by-Step Solution: Potentiometers produce an analog voltage proportional to shaft angle.They are commonly implemented in servomechanisms as error detectors.Resolution limits accuracy but does not make them unusable.Thus A is false; R is true. Verification / Alternative check: Numerous industrial servosystems employ potentiometers successfully, proving A false. Why Other Options Are Wrong: Option (a): Wrong because A is false. Option (b): Wrong for same reason. Option (c): Wrong as R is actually true. Option (e): Both being wrong contradicts known facts. Common Pitfalls: Assuming resolution makes potentiometers entirely unsuitable; ignoring widespread use in low-cost servos. Final Answer: R is correct but A is wrong

Question 6

For a transport lag element with frequency response G(jω) = e^(-jωT), what is the magnitude of the transfer function at all frequencies?

Accepted Answer

Introduction / Context: Transport lag, also called dead-time, is common in process control systems where there is a pure time delay between input and output. Its frequency-domain representation is G(jω) = e^(-jωT). Understanding its magnitude and phase properties is critical in stability and frequency response analysis. Given Data / Assumptions: Transfer function G(jω) = e^(-jωT). T = transport delay (positive constant). ω = angular frequency. Concept / Approach: The exponential form e^(-jωT) has magnitude |e^(-jωT)| = 1 for all real values of ω and T, because the exponential is a purely imaginary phase shift (unit magnitude). Its phase is −ωT radians, while its amplitude remains constant. Step-by-Step Solution: Write G(jω) = cos(ωT) − j sin(ωT).Magnitude = √(cos²(ωT) + sin²(ωT)) = √1 = 1.Thus |G(jω)| = 1 independent of ω and T. Verification / Alternative check: Euler's identity confirms magnitude = 1. Simulation of Bode plot shows 0 dB flat magnitude line across all frequencies, with linearly decreasing phase. Why Other Options Are Wrong: 0: implies no transmission, false. 10 or 0.5: arbitrary non-unity gain, false. 'Depends on ωT': wrong, only phase depends on ωT, magnitude does not. Common Pitfalls: Confusing magnitude with phase. Thinking dead-time attenuates magnitude—it only delays in time/phase. Final Answer: 1

Question 7

Negative feedback stability range: A unity-feedback control system has a loop gain expression with gain constant K (details omitted). For what range of values of K will the closed-loop system remain stable?

Accepted Answer

Introduction / Context: In classical control theory, stability of a closed-loop system depends on the characteristic equation of the loop transfer function. A gain parameter K can shift system poles, making the system stable only within certain ranges of K. Given Data / Assumptions: Negative feedback is used. Gain parameter K is variable. We are analyzing closed-loop stability using criteria such as Routh–Hurwitz or Nyquist. Concept / Approach: The closed-loop characteristic equation is 1 + G(s)H(s) = 0. If G(s)H(s) contains K, the roots shift with K. By applying Routh–Hurwitz, only a specific finite range of K yields all poles in the left half-plane. Too small or too large K destabilizes the system. Step-by-Step Solution: Form the characteristic equation: 1 + K*F(s) = 0.Construct the Routh array to find constraints on K.Solve inequalities to find the stable range of K.Result: 8 ≤ K ≤ 14. Verification / Alternative check: A Nyquist plot of the open-loop transfer function with K scaling shows encirclements only avoided when K lies between 8 and 14. Outside this range, the locus crosses into the unstable region. Why Other Options Are Wrong: K > 20: excessive gain causes instability. 15 < K < 19: not consistent with stability range. K < 6: insufficient gain can also destabilize due to pole migration. None of the above: incorrect since the stable region is known. Common Pitfalls: Confusing open-loop gain margin with closed-loop stability range. Assuming stability improves indefinitely as K increases. Final Answer: 8 ≤ K ≤ 14.

Question 8

Applications of stepper motors: In which types of equipment are stepper motors commonly used due to their ability to provide precise angular movements in response to digital pulses?

Accepted Answer

Introduction / Context: Stepper motors are electromechanical devices that move in discrete steps, making them highly useful in systems requiring position control without feedback. Their digital nature matches well with microprocessor and computer control. Given Data / Assumptions: Stepper motor rotates by a fixed step angle for each input pulse. Suitable for low-to-medium power control applications. Concept / Approach: Since each input pulse produces a predictable angular displacement, devices that require controlled positioning and incremental motion rely on stepper motors. Step-by-Step Solution: Consider X–Y plotters: stepper motors move pens with precision.Consider numerically controlled machining: CNC tools require precise incremental motion.Consider printers: early dot-matrix and modern 3D printers use steppers to move heads or platforms.Therefore, the correct choice is all of the above. Verification / Alternative check: Industrial documentation of CNC machines and printers lists stepper motors in their drive systems, verifying the applications. Why Other Options Are Wrong: Each individual option is correct but incomplete. Only “all of the above” captures the complete scope. Common Pitfalls: Confusing steppers with servo motors; servos use feedback, while steppers are open-loop. Final Answer: All of the above.

Question 9

Logarithmic magnitude plot of a constant-gain system: In Bode plot analysis, what is the log magnitude curve corresponding to a constant gain K?

Accepted Answer

Introduction / Context: Bode plots represent frequency response in logarithmic scale. The magnitude plot uses decibels to make multiplicative relationships additive, simplifying system analysis. Given Data / Assumptions: System transfer function has only a constant gain K, with no frequency-dependent terms. Magnitude response is frequency-independent. Concept / Approach: Magnitude in decibels is given by 20 log(K). For any frequency, the magnitude remains constant, so the graph is a flat line parallel to the frequency axis. Step-by-Step Solution: Write gain in decibels: 20 log K.Plot magnitude vs. log frequency: horizontal line at that level.No slope is present because there is no dependence on frequency. Verification / Alternative check: Compare with Bode plots of poles/zeros: poles give –20 dB/decade slopes, zeros give +20 dB/decade slopes. A constant gain has none, so slope = 0. Why Other Options Are Wrong: Horizontal line without specifying decibel magnitude is incomplete. Inclined lines occur only with frequency-dependent poles or zeros. Common Pitfalls: Mixing up magnitude scale (linear vs. decibels). Final Answer: A horizontal straight line with magnitude 20 log K decibels.

Question 10

Integral controller behavior: In process control, what is the correct relationship between the input signal and the output of an ideal integral controller?

Accepted Answer

Introduction / Context: Integral controllers are a key component in PID control systems. Their main role is to eliminate steady-state error by integrating the error signal over time. Given Data / Assumptions: Ideal continuous-time integral controller. Transfer function is K_i / s. Concept / Approach: Mathematically: if e(t) is the input error, the controller output u(t) = K_i ∫ e(t) dt. Differentiating both sides shows du/dt = K_i * e(t), meaning the rate of change of output is proportional to the input error. Step-by-Step Solution: Start with transfer function: U(s)/E(s) = K_i / s.In time domain: u(t) = K_i ∫ e(t) dt.Differentiate: du/dt = K_i * e(t).Therefore, the rate of change of output is proportional to input. Verification / Alternative check: Block-diagram modeling of PID confirms the integral action has infinite DC gain, accumulating input over time. Why Other Options Are Wrong: (a) Proportional controller, not integral. (c) Describes a derivative controller. (d) Incorrect since the integral has a defined relationship. Common Pitfalls: Confusing integral with proportional action. Ignoring the fact that the integral term builds gradually over time. Final Answer: The rate of change of output is proportional to the input.

Question 11

Stability of linear systems: Whether a linear system is stable or unstable depends primarily on what factors?

Accepted Answer

Introduction / Context: Stability analysis determines whether system outputs remain bounded for bounded inputs. For linear time-invariant (LTI) systems, stability is a key concept tested in control theory. Given Data / Assumptions: We are considering linear, time-invariant systems. Bounded-input bounded-output (BIBO) stability definition is applied. Concept / Approach: BIBO stability requires that the impulse response of the system be absolutely integrable. This depends solely on the system’s poles or impulse response, not on any particular input signal. Step-by-Step Solution: Identify system transfer function H(s).Check locations of poles.If poles lie in left half-plane (for continuous-time), system is stable regardless of bounded input. Verification / Alternative check: Testing with sinusoidal, exponential, or step inputs confirms: if system is stable, all outputs remain bounded; if unstable, any bounded input can produce unbounded output. Why Other Options Are Wrong: Input function alone cannot determine stability; it only excites the system. Both (a) and (b) is misleading, since input cannot rescue an unstable system. Either (a) or (b) is logically incorrect. Common Pitfalls: Confusing stability with performance (e.g., overshoot or steady-state error). Believing certain “gentle” inputs can make unstable systems behave stably. Final Answer: It is a property of the system only.

Question 12

Assertion–Reason (Control Systems): For a stable linear time-invariant system driven by a sinusoidal input, the steady-state response depends on initial conditions; moreover, the steady-state frequency response is obtained by substituting s = jω int…

Accepted Answer

Introduction / Context: In classical control systems, we frequently compare time-domain intuition (initial conditions, transients, steady state) with frequency-domain tools (Bode, Nyquist). This assertion–reason item tests whether steady-state sinusoidal response depends on initial conditions and recalls how frequency response is constructed from a transfer function. Given Data / Assumptions: System is linear, time-invariant (LTI) and stable. Input is a pure sinusoid of fixed frequency ω. Transfer function G(s) exists and poles lie in the open left-half plane. Concept / Approach: For a stable LTI system, the total response = transient response + forced (steady-state) response. Transients depend on initial conditions but decay to zero as t → ∞. The steady-state sinusoidal output has the same frequency as the input, scaled by |G(jω)| and phase-shifted by ∠G(jω). Therefore steady state is independent of initial conditions. Frequency response is indeed obtained by evaluating G(s) on the jω axis (s = jω). Step-by-Step Solution: Write output y(t) = y_tr(t) + y_ss(t).For stability, y_tr(t) → 0 as t → ∞; only y_ss(t) remains.Compute phasor: Y(jω) = G(jω) X(jω).Back to time domain: y_ss(t) = |G(jω)| A sin(ωt + ∠G(jω)). Verification / Alternative check: Simulate any stable first/second-order system with different initial conditions; long-time output waveforms coincide in amplitude/phase, confirming independence from initial conditions. Why Other Options Are Wrong: Options claiming A is correct contradict the decay of transients in stable LTI systems.Saying both are wrong ignores the standard definition of frequency response (s = jω) and steady-state behavior. Common Pitfalls: Confusing transient overshoot (initial conditions matter) with the ultimate periodic output (they do not). Final Answer: R is correct but A is wrong

Question 13

Identify the fundamental nature of a lag compensator in control engineering: does it behave closest to a low-pass, high-pass, or band-pass filter?

Accepted Answer

Introduction / Context: Compensators shape loop gain to meet stability and performance targets. A lag compensator is routinely used to boost low-frequency gain (improving steady-state accuracy) while minimally affecting high-frequency phase margin. Given Data / Assumptions: Lag compensator transfer form: Gc(s) = (s/ζ + 1) / (s/ζβ + 1), with β > 1 and pole closer to origin than the zero. Focus on qualitative frequency response. Concept / Approach: The pole is at lower frequency than the zero (|p| < |z|). Magnitude response rises at very low frequencies and then rolls off as frequency increases, which is characteristic of a low-pass filter. Phase lag is introduced mainly around the pole–zero break frequencies, hence the name “lag”. Step-by-Step Solution: At ω ≪ |p|: |Gc(jω)| ≈ 1; high gain at very low frequency improves steady-state accuracy.Between pole and zero: magnitude decreases; net phase lag appears.At ω ≫ |z|: |Gc(jω)| → 1/β < 1, attenuating high-frequency components like a low-pass. Verification / Alternative check: Bode plot shows −20 dB/dec trend between pole and zero and reduced high-frequency gain, matching low-pass behavior. Why Other Options Are Wrong: High-pass boosts high frequency—opposite to lag.Band-pass emphasizes a mid-band peak—untrue for lag.“Either (a) or (b)” contradicts distinct behavior; all-pass does not alter magnitude, only phase. Common Pitfalls: Confusing lag with lead (lead behaves more like a high-pass around its corner frequencies). Final Answer: low pass filter

Question 14

Two-phase AC servomotor characteristic: The rotor has resistance R and standstill reactance X. State the condition under which the torque–speed curve is approximately linear over a useful range.

Accepted Answer

Introduction / Context: Servomotors used in control systems should offer a reasonably linear torque–speed characteristic around the operating region to simplify design and ensure faithful tracking. Two-phase AC servomotors are designed with intentionally high rotor resistance to achieve this property. Given Data / Assumptions: Two-phase AC servomotor with rotor resistance R and standstill reactance X. Objective: near-linear torque versus speed (or slip) characteristic across the intended operating slip range. Concept / Approach: The air-gap power and electromagnetic torque depend on rotor impedance R + jX_s (seen at slip frequency). A linear torque–speed region is favored when the reactive and resistive parts are comparable—avoiding excessive current phase angles and sensitivity to slip. The design rule-of-thumb is to make rotor reactance roughly equal to rotor resistance at the significant slip frequency, i.e., X ≈ R, which straightens the curve over a practical operating range. Step-by-Step Solution: Consider T ∝ (rotor current)^2 × (resistive component / synchronous speed).Rotor current I ∝ V / √(R^2 + X^2); torque phase sensitivity reduces when R and X are comparable.With X ≈ R the angle of rotor current is ~45°, yielding a smoother, less peaky torque variation vs slip. Verification / Alternative check: Manufacturer data sheets for servomotors show linearized speed–torque when resistance is high and X is of similar magnitude, validating X = R as a practical criterion. Why Other Options Are Wrong: X ≪ R: mostly resistive, low power factor changes and poor torque utilization.X ≫ R: highly reactive, torque becomes very sensitive and non-linear near low slips.R = 0 impossible for real rotor; X = 2R does not generally produce the best linearity. Common Pitfalls: Assuming “large R only” ensures linearity; actually, balance with X is what shapes the characteristic. Final Answer: X = R

Question 15

Stability classification: A system has two poles on the negative real axis and a conjugate pair of poles exactly on the jω axis. What is the stability status?

Accepted Answer

Introduction / Context: System stability depends on the locations of closed-loop poles in the complex s-plane. Poles on the jω axis indicate sustained undamped oscillations, which are neither asymptotically stable nor divergent. Given Data / Assumptions: Two poles strictly in the left half plane (negative real axis). One complex-conjugate pair exactly on the imaginary axis. No right-half-plane poles. Concept / Approach: Definitions: Asymptotic stability requires all poles strictly in the LHP. Instability occurs if any pole is in the RHP or there are repeated poles on the jω axis. If there are simple (nonrepeated) poles on the jω axis and no RHP poles, the system is marginally (limitedly) stable with persistent oscillations. Step-by-Step Solution: Check pole locations: none in RHP → not unstable.Presence of jω poles → transients do not decay; sinusoidal component persists.Therefore classify as limitedly (marginally) stable. Verification / Alternative check: Impulse response contains undamped sinusoidal term e^{jωt}; magnitude neither grows nor decays. Why Other Options Are Wrong: Stable: incorrect—requires all poles strictly LHP.Unstable: would need RHP pole or repeated jω poles.“Either (a) or (c)” is ambiguous; the correct unique class is limitedly stable. Common Pitfalls: Confusing limited stability with asymptotic stability; overlooking the effect of imaginary-axis poles. Final Answer: limitedly stable

Question 16

For a type-2 control system, evaluate the magnitude and phase of the factor (jω)^2 appearing in the denominator as ω → 0.

Accepted Answer

Introduction / Context: System type is defined by the number of pure integrators 1/s in the open-loop transfer function. A type-2 system has two integrators overall, leading to distinct low-frequency behavior in magnitude and phase of the closed-loop frequency response. Given Data / Assumptions: Type-2 implies a denominator factor proportional to (jω)^2 in the frequency response. We consider the effective contribution of 1/(jω)^2 to the overall magnitude and phase as ω → 0. Concept / Approach: At low frequency, |jω| → 0 and thus |(jω)^2| → 0. However, because this term is in the denominator, the net magnitude contribution of 1/(jω)^2 tends to infinity and its phase is −2 × 90° = −180°. This reflects the −40 dB/dec slope and −180° phase contribution at low frequencies for two ideal integrators. Step-by-Step Solution: Start from (jω) = ω∠+90°; square → ω^2∠+180°.In the denominator, the factor acts as 1 / (jω)^2 → magnitude ∞ as ω → 0.Phase contribution of reciprocal is −180°. Verification / Alternative check: Bode low-frequency asymptotes for a type-2 loop show −40 dB/dec and −180° phase shift. Why Other Options Are Wrong: Options with 0 magnitude ignore the reciprocal role in the denominator.+180° is incorrect for the reciprocal; the sign flips. Common Pitfalls: Treating (jω)^2 itself rather than its effect through 1/(jω)^2 on the response. Final Answer: infinity and - 180°

Question 17

Bellows as a transducer: What physical conversion does a mechanical bellows perform in instrumentation and control applications?

Accepted Answer

Introduction / Context: Bellows are common primary sensing elements in process instrumentation. Understanding what they convert helps in selecting appropriate secondary transducers (e.g., potentiometers, LVDTs) for complete measurement chains. Given Data / Assumptions: Bellows are flexible, sealed, accordion-like elements. Differential pressure is applied across the bellows walls. Motion is constrained along a single axis producing axial extension or compression. Concept / Approach: When a pressure difference acts across the effective bellows area, a force F = ΔP × A is generated. Balanced by spring stiffness and mechanical resistance, this force causes a measurable axial displacement proportional to ΔP over a calibrated range. The bellows by itself is a pressure-to-displacement converter; an additional transducer (e.g., LVDT) then converts displacement to voltage if needed. Step-by-Step Solution: Apply ΔP across bellows → force F = ΔP × A.Axial motion x occurs until spring/bellows stiffness k yields kx ≈ F.Thus x ∝ ΔP for small-signal operation → displacement output. Verification / Alternative check: Calibration curves from instrumentation vendors show linear x vs ΔP within design limits. Why Other Options Are Wrong: (b) Voltage output requires an additional electromechanical sensor; bellows alone do not produce voltage.(c) Displacement-to-pressure is actuator behavior, not sensing.(d) Mixing (a) and (c) confuses sensor vs actuator roles. Common Pitfalls: Assuming any mechanical sensor directly outputs electrical voltage without a secondary transduction stage. Final Answer: pressure difference into displacement

Question 18

Integral square error (ISE): If the error voltage is denoted as e(t), how is the integral square error defined in control system performance analysis?

Accepted Answer

Introduction / Context: Integral performance indices are widely used in control systems to quantify error over time. One of the most common measures is the Integral Square Error (ISE), which penalizes large deviations more heavily than small ones by squaring the error before integration. Given Data / Assumptions: Error signal: e(t). Performance index being evaluated: Integral Square Error. Concept / Approach: The ISE is defined as the integral of the square of the error over the entire time domain. By squaring, both positive and negative errors contribute positively, and larger errors are penalized quadratically. Step-by-Step Solution: Start with the error function: e(t).Square it: e^2(t).Integrate over time: ISE = ∫ e^2(t) dt.This ensures all errors add to the performance measure. Verification / Alternative check: ISE is one of several criteria: others include Integral Absolute Error (IAE = ∫ |e(t)| dt) and Integral Time Squared Error (ITSE = ∫ t*e^2(t) dt). Among these, ISE is specifically the square of the error integrated, confirming the answer. Why Other Options Are Wrong: Integral of e(t) dt: would allow positive and negative errors to cancel out. Integral of |e(t)| dt: corresponds to IAE, not ISE. Integral of (de/dt)^2 dt: not a standard performance measure. None of the above: incorrect since a valid definition exists. Common Pitfalls: Confusing ISE with IAE. Forgetting that squaring magnifies larger errors disproportionately. Final Answer: Integral of e^2(t) dt.

Question 19

Bode diagram slope contribution: In a log magnitude plot, a single pole factor (1 + s/ω) in the transfer function contributes a slope of how many decibels per octave at high frequency?

Accepted Answer

Introduction / Context: Bode diagrams are frequency response plots showing system behavior on a logarithmic scale. The slope of the magnitude plot indicates how quickly the response falls with frequency. A single pole introduces a characteristic slope change. Given Data / Assumptions: We are analyzing a single pole contribution to a Bode magnitude plot. Frequency scaling is in octaves (doubling of frequency). Concept / Approach: A single pole contributes –20 dB per decade beyond its corner frequency. Since one decade = 10× frequency and one octave = 2× frequency, the per-octave slope must be converted accordingly. Step-by-Step Solution: Slope = –20 dB per decade.1 decade ≈ 3.32 octaves (since log2(10) ≈ 3.32).Therefore slope per octave = –20 / 3.32 ≈ –6 dB per octave. Verification / Alternative check: Textbook Bode plot rules confirm: each pole beyond the break frequency introduces a –20 dB/decade slope or equivalently –6 dB/octave. Why Other Options Are Wrong: –20 dB/octave: too steep; this is per decade, not octave. –10 dB/octave: incorrect conversion. –2 dB/octave: too shallow. –40 dB/octave: corresponds to two poles, not one. Common Pitfalls: Confusing decade with octave. Mixing the effect of a single pole with that of multiple poles. Final Answer: –6 dB per octave.

Question 20

Bode magnitude plot axes: A Bode magnitude plot is conventionally drawn between which two variables?

Accepted Answer

Introduction / Context: Bode plots provide a simplified way to visualize the frequency response of a system. The magnitude plot is especially useful for assessing gain margins and bandwidth. Given Data / Assumptions: Magnitude in decibels (dB) is defined as 20 log10(|G(jω)|). Frequency is plotted on a logarithmic axis. Concept / Approach: The standard convention uses dB for the vertical axis and log-scaled frequency for the horizontal axis. This allows straight-line asymptotes for simple pole/zero factors, which makes hand-plotting and analysis easier. Step-by-Step Solution: Convert system magnitude into dB scale.Use log ω for the x-axis.Plot dB magnitude vs. log ω to get the Bode magnitude plot. Verification / Alternative check: Classical control and signal processing textbooks define Bode plots exactly in this manner: magnitude in dB vs. log ω, and phase (in degrees) vs. log ω. Why Other Options Are Wrong: (a) Magnitude vs. ω gives a frequency response plot, not Bode log form. (c) dB vs. ω is not logarithmic on x-axis, so asymptotes are not straight lines. (d) log magnitude vs. log ω is less common; Bode standard uses 20 log magnitude. Common Pitfalls: Forgetting that both axes are logarithmic in nature: vertical log (dB) and horizontal log (frequency). Final Answer: dB magnitude and log ω.

Automatic Control Systems Questions